Quantitative multiplex detection of pathogen biomarkers

Energy Technology Data Exchange (ETDEWEB)

Mukundan, Harshini; Xie, Hongzhi; Swanson, Basil I.; Martinez, Jennifer; Grace, Wynne K.

2016-02-09

The present invention addresses the simultaneous detection and quantitative measurement of multiple biomolecules, e.g., pathogen biomarkers through either a sandwich assay approach or a lipid insertion approach. The invention can further employ a multichannel, structure with multi-sensor elements per channel.

Quantitative multiplex detection of pathogen biomarkers

Science.gov (United States)

Mukundan, Harshini; Xie, Hongzhi; Swanson, Basil I; Martinez, Jennifer; Grace, Wynne K

2014-10-14

The present invention addresses the simultaneous detection and quantitative measurement of multiple biomolecules, e.g., pathogen biomarkers through either a sandwich assay approach or a lipid insertion approach. The invention can further employ a multichannel, structure with multi-sensor elements per channel.

MO-DE-303-03: Session on quantitative imaging for assessment of tumor response to radiation therapy

International Nuclear Information System (INIS)

Bowen, S.

2015-01-01

This session will focus on quantitative imaging for assessment of tumor response to radiation therapy. This is a technically challenging method to translate to practice in radiation therapy. In the new era of precision medicine, however, delivering the right treatment, to the right patient, and at the right time, can positively impact treatment choices and patient outcomes. Quantitative imaging provides the spatial sensitivity required by radiation therapy for precision medicine that is not available by other means. In this Joint ESTRO -AAPM Symposium, three leading-edge investigators will present specific motivations for quantitative imaging biomarkers in radiation therapy of esophageal, head and neck, locally advanced non-small cell lung cancer, and hepatocellular carcinoma. Experiences with the use of dynamic contrast enhanced (DCE) MRI, diffusion- weighted (DW) MRI, PET/CT, and SPECT/CT will be presented. Issues covered will include: response prediction, dose-painting, timing between therapy and imaging, within-therapy biomarkers, confounding effects, normal tissue sparing, dose-response modeling, and association with clinical biomarkers and outcomes. Current information will be presented from investigational studies and clinical practice. Learning Objectives: Learn motivations for the use of quantitative imaging biomarkers for assessment of response to radiation therapy Review the potential areas of application in cancer therapy Examine the challenges for translation, including imaging confounds and paucity of evidence to date Compare exemplary examples of the current state of the art in DCE-MRI, DW-MRI, PET/CT and SPECT/CT imaging for assessment of response to radiation therapy Van der Heide: Research grants from the Dutch Cancer Society and the European Union (FP7) Bowen: RSNA Scholar grant

MO-DE-303-03: Session on quantitative imaging for assessment of tumor response to radiation therapy

Energy Technology Data Exchange (ETDEWEB)

Bowen, S. [University of Washington, School of Medicine: PET/CT and SPECT/CT for Lung and Liver Radiation Therapy Response Assessment of Tumor and Normal Tissue (United States)

2015-06-15

This session will focus on quantitative imaging for assessment of tumor response to radiation therapy. This is a technically challenging method to translate to practice in radiation therapy. In the new era of precision medicine, however, delivering the right treatment, to the right patient, and at the right time, can positively impact treatment choices and patient outcomes. Quantitative imaging provides the spatial sensitivity required by radiation therapy for precision medicine that is not available by other means. In this Joint ESTRO -AAPM Symposium, three leading-edge investigators will present specific motivations for quantitative imaging biomarkers in radiation therapy of esophageal, head and neck, locally advanced non-small cell lung cancer, and hepatocellular carcinoma. Experiences with the use of dynamic contrast enhanced (DCE) MRI, diffusion- weighted (DW) MRI, PET/CT, and SPECT/CT will be presented. Issues covered will include: response prediction, dose-painting, timing between therapy and imaging, within-therapy biomarkers, confounding effects, normal tissue sparing, dose-response modeling, and association with clinical biomarkers and outcomes. Current information will be presented from investigational studies and clinical practice. Learning Objectives: Learn motivations for the use of quantitative imaging biomarkers for assessment of response to radiation therapy Review the potential areas of application in cancer therapy Examine the challenges for translation, including imaging confounds and paucity of evidence to date Compare exemplary examples of the current state of the art in DCE-MRI, DW-MRI, PET/CT and SPECT/CT imaging for assessment of response to radiation therapy Van der Heide: Research grants from the Dutch Cancer Society and the European Union (FP7) Bowen: RSNA Scholar grant.

Fundamentals of quantitative dynamic contrast-enhanced MR imaging.

Science.gov (United States)

Paldino, Michael J; Barboriak, Daniel P

2009-05-01

Quantitative analysis of dynamic contrast-enhanced MR imaging (DCE-MR imaging) has the power to provide information regarding physiologic characteristics of the microvasculature and is, therefore, of great potential value to the practice of oncology. In particular, these techniques could have a significant impact on the development of novel anticancer therapies as a promising biomarker of drug activity. Standardization of DCE-MR imaging acquisition and analysis to provide more reproducible measures of tumor vessel physiology is of crucial importance to realize this potential. The purpose of this article is to review the pathophysiologic basis and technical aspects of DCE-MR imaging techniques.

Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.

Science.gov (United States)

Wilson, Jennifer L; Altman, Russ B

2018-02-01

Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

Quantitative phase-digital holographic microscopy: a new imaging modality to identify original cellular biomarkers of diseases

KAUST Repository

Marquet, P.; Rothenfusser, K.; Rappaz, B.; Depeursinge, Christian; Jourdain, P.; Magistretti, Pierre J.

2016-01-01

parallelization and automation processes, represents an appealing imaging modality to both identify original cellular biomarkers of diseases as well to explore the underlying pathophysiological processes.

Quantitative imaging features: extension of the oncology medical image database

Science.gov (United States)

Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

2015-03-01

Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

Development of imaging biomarkers and generation of big data.

Science.gov (United States)

Alberich-Bayarri, Ángel; Hernández-Navarro, Rafael; Ruiz-Martínez, Enrique; García-Castro, Fabio; García-Juan, David; Martí-Bonmatí, Luis

2017-06-01

Several image processing algorithms have emerged to cover unmet clinical needs but their application to radiological routine with a clear clinical impact is still not straightforward. Moving from local to big infrastructures, such as Medical Imaging Biobanks (millions of studies), or even more, Federations of Medical Imaging Biobanks (in some cases totaling to hundreds of millions of studies) require the integration of automated pipelines for fast analysis of pooled data to extract clinically relevant conclusions, not uniquely linked to medical imaging, but in combination to other information such as genetic profiling. A general strategy for the development of imaging biomarkers and their integration in the cloud for the quantitative management and exploitation in large databases is herein presented. The proposed platform has been successfully launched and is being validated nowadays among the early adopters' community of radiologists, clinicians, and medical imaging researchers.

Metabolic Imaging Biomarkers of Postradiotherapy Xerostomia

Energy Technology Data Exchange (ETDEWEB)

Cannon, Blake [Department of Radiation Physics, University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); Schwartz, David L., E-mail: dschwartz3@nshs.edu [Department of Radiation Oncology, University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); Department of Radiation Medicine, Hofstra North Shore-LIJ School of Medicine, New Hyde Park, New York (United States); Feinstein Institute for Medical Research, Manhasset, New York (United States); Dong Lei [Department of Radiation Physics, University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States)

2012-08-01

Purpose: Xerostomia is a major complication of head and neck radiotherapy (RT). Available xerostomia measures remain flawed. [{sup 18}F]fluorodeoxyglucose-labeled positron emission tomography-computed tomography (FDG-PET-CT) is routinely used for staging and response assessment of head and neck cancer. We investigated quantitative measurement of parotid gland FDG uptake as a potential biomarker for post-RT xerostomia. Methods and Materials: Ninety-eight locally advanced head and neck cancer patients receiving definitive RT underwent baseline and post-RT FDG-PET-CT on a prospective imaging trial. A separate validation cohort of 14 patients underwent identical imaging while prospectively enrolled in a second trial collecting sialometry and patient-reported outcomes. Radiation dose and pre- and post-RT standard uptake values (SUVs) for all voxels contained within parotid gland ROI were deformably registered. Results: Average whole-gland or voxel-by-voxel models incorporating parotid D{sub Met} (defined as the pretreatment parotid SUV weighted by dose) accurately predicted posttreatment changes in parotid FDG uptake (e.g., fractional parotid SUV). Fractional loss of parotid FDG uptake closely paralleled early parotid toxicity defined by posttreatment salivary output (p < 0.01) and Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer xerostomia scores (p < 0.01). Conclusions: In this pilot series, loss of parotid FDG uptake was strongly associated with acute clinical post-RT parotid toxicity. D{sub Met} may potentially be used to guide function-sparing treatment planning. Prospective validation of FDG-PET-CT as a convenient, quantifiable imaging biomarker of parotid function is warranted and ongoing.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

Science.gov (United States)

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

Low-frequency quantitative ultrasound imaging of cell death in vivo

International Nuclear Information System (INIS)

Sadeghi-Naini, Ali; Falou, Omar; Czarnota, Gregory J.; Papanicolau, Naum; Tadayyon, Hadi; Lee, Justin; Zubovits, Judit; Sadeghian, Alireza; Karshafian, Raffi; Al-Mahrouki, Azza; Giles, Anoja; Kolios, Michael C.

2013-01-01

Purpose: Currently, no clinical imaging modality is used routinely to assess tumor response to cancer therapies within hours to days of the delivery of treatment. Here, the authors demonstrate the efficacy of ultrasound at a clinically relevant frequency to quantitatively detect changes in tumors in response to cancer therapies using preclinical mouse models.Methods: Conventional low-frequency and corresponding high-frequency ultrasound (ranging from 4 to 28 MHz) were used along with quantitative spectroscopic and signal envelope statistical analyses on data obtained from xenograft tumors treated with chemotherapy, x-ray radiation, as well as a novel vascular targeting microbubble therapy.Results: Ultrasound-based spectroscopic biomarkers indicated significant changes in cell-death associated parameters in responsive tumors. Specifically changes in the midband fit, spectral slope, and 0-MHz intercept biomarkers were investigated for different types of treatment and demonstrated cell-death related changes. The midband fit and 0-MHz intercept biomarker derived from low-frequency data demonstrated increases ranging approximately from 0 to 6 dBr and 0 to 8 dBr, respectively, depending on treatments administrated. These data paralleled results observed for high-frequency ultrasound data. Statistical analysis of ultrasound signal envelope was performed as an alternative method to obtain histogram-based biomarkers and provided confirmatory results. Histological analysis of tumor specimens indicated up to 61% cell death present in the tumors depending on treatments administered, consistent with quantitative ultrasound findings indicating cell death. Ultrasound-based spectroscopic biomarkers demonstrated a good correlation with histological morphological findings indicative of cell death (r 2 = 0.71, 0.82; p < 0.001).Conclusions: In summary, the results provide preclinical evidence, for the first time, that quantitative ultrasound used at a clinically relevant frequency, in

Low-frequency quantitative ultrasound imaging of cell death in vivo

Energy Technology Data Exchange (ETDEWEB)

Sadeghi-Naini, Ali; Falou, Omar; Czarnota, Gregory J. [Imaging Research – Physical Science, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Papanicolau, Naum; Tadayyon, Hadi [Imaging Research – Physical Science, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5, Canada and Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Lee, Justin [Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5, Canada and Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Zubovits, Judit [Department of Pathology, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Sadeghian, Alireza [Department of Computer Science, Ryerson University, Toronto, Ontario M5B 2K3 (Canada); Karshafian, Raffi [Department of Physics, Ryerson University, Toronto, Ontario M5B 2K3 (Canada); Al-Mahrouki, Azza; Giles, Anoja [Imaging Research – Physical Science, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5, Canada and Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Kolios, Michael C. [Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M4N 3M5, Canada and Department of Physics, Ryerson University, Toronto, Ontario M5B 2K3 (Canada)

2013-08-15

Purpose: Currently, no clinical imaging modality is used routinely to assess tumor response to cancer therapies within hours to days of the delivery of treatment. Here, the authors demonstrate the efficacy of ultrasound at a clinically relevant frequency to quantitatively detect changes in tumors in response to cancer therapies using preclinical mouse models.Methods: Conventional low-frequency and corresponding high-frequency ultrasound (ranging from 4 to 28 MHz) were used along with quantitative spectroscopic and signal envelope statistical analyses on data obtained from xenograft tumors treated with chemotherapy, x-ray radiation, as well as a novel vascular targeting microbubble therapy.Results: Ultrasound-based spectroscopic biomarkers indicated significant changes in cell-death associated parameters in responsive tumors. Specifically changes in the midband fit, spectral slope, and 0-MHz intercept biomarkers were investigated for different types of treatment and demonstrated cell-death related changes. The midband fit and 0-MHz intercept biomarker derived from low-frequency data demonstrated increases ranging approximately from 0 to 6 dBr and 0 to 8 dBr, respectively, depending on treatments administrated. These data paralleled results observed for high-frequency ultrasound data. Statistical analysis of ultrasound signal envelope was performed as an alternative method to obtain histogram-based biomarkers and provided confirmatory results. Histological analysis of tumor specimens indicated up to 61% cell death present in the tumors depending on treatments administered, consistent with quantitative ultrasound findings indicating cell death. Ultrasound-based spectroscopic biomarkers demonstrated a good correlation with histological morphological findings indicative of cell death (r{sup 2}= 0.71, 0.82; p < 0.001).Conclusions: In summary, the results provide preclinical evidence, for the first time, that quantitative ultrasound used at a clinically relevant frequency

Quantitative redox imaging biomarkers for studying tissue metabolic state and its heterogeneity

Directory of Open Access Journals (Sweden)

He N. Xu

2014-03-01

Full Text Available NAD+/NADH redox state has been implicated in many diseases such as cancer and diabetes as well as in the regulation of embryonic development and aging. To fluorimetrically assess the mitochondrial redox state, Dr. Chance and co-workers measured the fluorescence of NADH and oxidized flavoproteins (Fp including flavin–adenine–dinucleotide (FAD and demonstrated their ratio (i.e. the redox ratio is a sensitive indicator of the mitochondrial redox states. The Chance redox scanner was built to simultaneously measure NADH and Fp in tissue at submillimeter scale in 3D using the freeze-trap protocol. This paper summarizes our recent research experience, development and new applications of the redox scanning technique in collaboration with Dr. Chance beginning in 2005. Dr. Chance initiated or actively involved in many of the projects during the last several years of his life. We advanced the redox scanning technique by measuring the nominal concentrations (in reference to the frozen solution standards of the endogenous fluorescent analytes, i.e., [NADH] and [Fp] to quantify the redox ratios in various biological tissues. The advancement has enabled us to identify an array of the redox indices as quantitative imaging biomarkers (including [NADH], [Fp], [Fp]/([NADH]+[Fp], [NADH]/[Fp], and their standard deviations for studying some important biological questions on cancer and normal tissue metabolism. We found that the redox indices were associated or changed with (1 tumorigenesis (cancer versus non-cancer of human breast tissue biopsies; (2 tumor metastatic potential; (3 tumor glucose uptake; (4 tumor p53 status; (5 PI3K pathway activation in pre-malignant tissue; (6 therapeutic effects on tumors; (7 embryonic stem cell differentiation; (8 the heart under fasting. Together, our work demonstrated that the tissue redox indices obtained from the redox scanning technique may provide useful information about tissue metabolism and physiology status in normal

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

Science.gov (United States)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

Imaging blood-brain barrier dysfunction as a biomarker for epileptogenesis.

Science.gov (United States)

Bar-Klein, Guy; Lublinsky, Svetlana; Kamintsky, Lyn; Noyman, Iris; Veksler, Ronel; Dalipaj, Hotjensa; Senatorov, Vladimir V; Swissa, Evyatar; Rosenbach, Dror; Elazary, Netta; Milikovsky, Dan Z; Milk, Nadav; Kassirer, Michael; Rosman, Yossi; Serlin, Yonatan; Eisenkraft, Arik; Chassidim, Yoash; Parmet, Yisrael; Kaufer, Daniela; Friedman, Alon

2017-06-01

A biomarker that will enable the identification of patients at high-risk for developing post-injury epilepsy is critically required. Microvascular pathology and related blood-brain barrier dysfunction and neuroinflammation were shown to be associated with epileptogenesis after injury. Here we used prospective, longitudinal magnetic resonance imaging to quantitatively follow blood-brain barrier pathology in rats following status epilepticus, late electrocorticography to identify epileptic animals and post-mortem immunohistochemistry to confirm blood-brain barrier dysfunction and neuroinflammation. Finally, to test the pharmacodynamic relevance of the proposed biomarker, two anti-epileptogenic interventions were used; isoflurane anaesthesia and losartan. Our results show that early blood-brain barrier pathology in the piriform network is a sensitive and specific predictor (area under the curve of 0.96, P brain barrier pathology as a clinically relevant predictive, diagnostic and pharmaco!dynamics biomarker for acquired epilepsy. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Development of on-chip multi-imaging flow cytometry for identification of imaging biomarkers of clustered circulating tumor cells.

Directory of Open Access Journals (Sweden)

Hyonchol Kim

Full Text Available An on-chip multi-imaging flow cytometry system has been developed to obtain morphometric parameters of cell clusters such as cell number, perimeter, total cross-sectional area, number of nuclei and size of clusters as "imaging biomarkers", with simultaneous acquisition and analysis of both bright-field (BF and fluorescent (FL images at 200 frames per second (fps; by using this system, we examined the effectiveness of using imaging biomarkers for the identification of clustered circulating tumor cells (CTCs. Sample blood of rats in which a prostate cancer cell line (MAT-LyLu had been pre-implanted was applied to a microchannel on a disposable microchip after staining the nuclei using fluorescent dye for their visualization, and the acquired images were measured and compared with those of healthy rats. In terms of the results, clustered cells having (1 cell area larger than 200 µm2 and (2 nucleus area larger than 90 µm2 were specifically observed in cancer cell-implanted blood, but were not observed in healthy rats. In addition, (3 clusters having more than 3 nuclei were specific for cancer-implanted blood and (4 a ratio between the actual perimeter and the perimeter calculated from the obtained area, which reflects a shape distorted from ideal roundness, of less than 0.90 was specific for all clusters having more than 3 nuclei and was also specific for cancer-implanted blood. The collected clusters larger than 300 µm2 were examined by quantitative gene copy number assay, and were identified as being CTCs. These results indicate the usefulness of the imaging biomarkers for characterizing clusters, and all of the four examined imaging biomarkers-cluster area, nuclei area, nuclei number, and ratio of perimeter-can identify clustered CTCs in blood with the same level of preciseness using multi-imaging cytometry.

Informatics methods to enable sharing of quantitative imaging research data.

Science.gov (United States)

Levy, Mia A; Freymann, John B; Kirby, Justin S; Fedorov, Andriy; Fennessy, Fiona M; Eschrich, Steven A; Berglund, Anders E; Fenstermacher, David A; Tan, Yongqiang; Guo, Xiaotao; Casavant, Thomas L; Brown, Bartley J; Braun, Terry A; Dekker, Andre; Roelofs, Erik; Mountz, James M; Boada, Fernando; Laymon, Charles; Oborski, Matt; Rubin, Daniel L

2012-11-01

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers. Copyright © 2012 Elsevier Inc. All rights reserved.

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Science.gov (United States)

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

Imaging biomarker roadmap for cancer studies

NARCIS (Netherlands)

O'Connor, James P. B.; Aboagye, Eric O.; Adams, Judith E.; Aerts, Hugo J. W. L.; Barrington, Sally F.; Beer, Ambros J.; Boellaard, Ronald; Bohndiek, Sarah E.; Brady, Michael; Brown, Gina; Buckley, David L.; Chenevert, Thomas L.; Clarke, Laurence P.; Collette, Sandra; Cook, Gary J.; Desouza, Nandita M.; Dickson, John C.; Dive, Caroline; Evelhoch, Jeffrey L.; Faivre-Finn, Corinne; Gallagher, Ferdia A.; Gilbert, Fiona J.; Gillies, Robert J.; Goh, Vicky; Griffiths, J. R.; Groves, Ashley M.; Halligan, Steve; Harris, Adrian L.; Hawkes, David J.; Hoekstra, Otto S.; Huang, Erich P.; Hutton, Brian F.; Jackson, Edward F.; Jayson, Gordon C.; Jones, Andrew; Koh, Dow-Mu; Lacombe, Denis; Lambin, Philippe; Lassau, Nathalie; Leach, Martin O.; Lee, Ting-Yim; Leen, Edward L.; Lewis, Jason S.; Liu, Yan; Lythgoe, Mark F.; Manoharan, Prakash; Maxwell, Ross J.; Miles, Kenneth A.; Morgan, Bruno; Morris, Steve; Ng, Tony; Padhani, Anwar R.; Parker, Geoff J. M.; Partridge, Mike; Pathak, Arvind P.; Peet, Andrew C.; Punwani, Shonit; Reynolds, Andrew R.; Robinson, Simon P.; Shankar, Lalitha K.; Sharma, Ricky A.; Soloviev, Dmitry; Stroobants, Sigrid G.; Sullivan, Daniel C.; Taylor, Stuart A.; Tofts, Paul S.; Tozer, Gillian M.; van Herk, Marcel B.; Walker-Samuel, Simon; Wason, James; Williams, Kaye J.; Workman, Paul; Yankeelov, Thomas E.; Brindle, Kevin M.; McShane, Lisa M.; Jackson, Alan; Waterton, John C.

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and

MO-C-BRB-06: Translating NIH / NIBIB funding to clinical reality in quantitative diagnostic imaging

Energy Technology Data Exchange (ETDEWEB)

Jackson, E. [University of Wisconsin (United States)

2015-06-15

Diagnostic radiology and radiation oncology are arguably two of the most technologically advanced specialties in medicine. The imaging and radiation medicine technologies in clinical use today have been continuously improved through new advances made in the commercial and academic research arenas. This symposium explores the translational path from research through clinical implementation. Dr. Pettigrew will start this discussion by sharing his perspectives as director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB). The NIBIB has focused on promoting research that is technological in nature and has high clinical impact. We are in the age of precision medicine, and the technological innovations and quantitative tools developed by engineers and physicists working with physicians are providing innovative tools that increase precision and improve outcomes in health care. NIBIB funded grants lead to a very high patenting rate (per grant dollar), and these patents have higher citation rates by other patents, suggesting greater clinical impact, as well. Two examples of clinical translation resulting from NIH-funded research will be presented, in radiation therapy and diagnostic imaging. Dr. Yu will describe a stereotactic radiotherapy device developed in his laboratory that is designed for treating breast cancer with the patient in the prone position. It uses 36 rotating Cobalt-60 sources positioned in an annular geometry to focus the radiation beam at the system’s isocenter. The radiation dose is delivered throughout the target volume in the breast by constantly moving the patient in a planned trajectory relative to the fixed isocenter. With this technique, the focal spot dynamically paints the dose distribution throughout the target volume in three dimensions. Dr. Jackson will conclude this symposium by describing the RSNA Quantitative Imaging Biomarkers Alliance (QIBA), which is funded in part by NIBIB and is a synergistic collaboration

MO-C-BRB-06: Translating NIH / NIBIB funding to clinical reality in quantitative diagnostic imaging

International Nuclear Information System (INIS)

Jackson, E.

2015-01-01

Diagnostic radiology and radiation oncology are arguably two of the most technologically advanced specialties in medicine. The imaging and radiation medicine technologies in clinical use today have been continuously improved through new advances made in the commercial and academic research arenas. This symposium explores the translational path from research through clinical implementation. Dr. Pettigrew will start this discussion by sharing his perspectives as director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB). The NIBIB has focused on promoting research that is technological in nature and has high clinical impact. We are in the age of precision medicine, and the technological innovations and quantitative tools developed by engineers and physicists working with physicians are providing innovative tools that increase precision and improve outcomes in health care. NIBIB funded grants lead to a very high patenting rate (per grant dollar), and these patents have higher citation rates by other patents, suggesting greater clinical impact, as well. Two examples of clinical translation resulting from NIH-funded research will be presented, in radiation therapy and diagnostic imaging. Dr. Yu will describe a stereotactic radiotherapy device developed in his laboratory that is designed for treating breast cancer with the patient in the prone position. It uses 36 rotating Cobalt-60 sources positioned in an annular geometry to focus the radiation beam at the system’s isocenter. The radiation dose is delivered throughout the target volume in the breast by constantly moving the patient in a planned trajectory relative to the fixed isocenter. With this technique, the focal spot dynamically paints the dose distribution throughout the target volume in three dimensions. Dr. Jackson will conclude this symposium by describing the RSNA Quantitative Imaging Biomarkers Alliance (QIBA), which is funded in part by NIBIB and is a synergistic collaboration

FDG PET/CT imaging as a biomarker in lymphoma

Energy Technology Data Exchange (ETDEWEB)

Meignan, Michel; Itti, Emmanuel [Hopitaux Universitaires Henri Mondor, Paris-Est Creteil University, LYSA Imaging, Department of Nuclear Medicine, Creteil (France); Gallamini, Andrea [Nice University, Research, Innovation and Statistic Department, Antoine Lacassagne Cancer Center, Nice (France); Scientific Research Committee, S. Croce Hospital, Cuneo (Italy); Younes, Anas [Memorial Sloan Kettering Cancer Center, Lymphoma Service, New York, NY (United States)

2015-04-01

FDG PET/CT has changed the management of FDG-avid lymphoma and is now recommended as the imaging technique of choice for staging and restaging. The need for tailoring therapy to reduce toxicity in patients with a favourable outcome and for improving treatment in those with high-risk factors requires accurate diagnostic methods and a new prognostic algorithm to identify different risk categories. New drugs are used in relapsed/refractory patients. The role of FDG PET/CT as a biomarker in this context is summarized in this review. New trends in FDG metabolic imaging in lymphoma are addressed including metabolic tumour volume measurement at staging and integrative PET which combines PET data with clinical and molecular markers or other imaging techniques. The quantitative approach for response assessment which is under investigation and is used in large ongoing trials is compared with visual criteria. The place of FDG in the era of targeted therapy is discussed. (orig.)

Fluorescence-based Western blotting for quantitation of protein biomarkers in clinical samples.

Science.gov (United States)

Zellner, Maria; Babeluk, Rita; Diestinger, Michael; Pirchegger, Petra; Skeledzic, Senada; Oehler, Rudolf

2008-09-01

Since most high throughput techniques used in biomarker discovery are very time and cost intensive, highly specific and quantitative analytical alternative application methods are needed for the routine analysis. Conventional Western blotting allows detection of specific proteins to the level of single isotypes while its quantitative accuracy is rather limited. We report a novel and improved quantitative Western blotting method. The use of fluorescently labelled secondary antibodies strongly extends the dynamic range of the quantitation and improves the correlation with the protein amount (r=0.997). By an additional fluorescent staining of all proteins immediately after their transfer to the blot membrane, it is possible to visualise simultaneously the antibody binding and the total protein profile. This allows for an accurate correction for protein load. Applying this normalisation it could be demonstrated that fluorescence-based Western blotting is able to reproduce a quantitative analysis of two specific proteins in blood platelet samples from 44 subjects with different diseases as initially conducted by 2D-DIGE. These results show that the proposed fluorescence-based Western blotting is an adequate application technique for biomarker quantitation and suggest possibilities of employment that go far beyond.

Quantitative Analysis of "1"8F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

International Nuclear Information System (INIS)

Cui, Yi; Song, Jie; Pollom, Erqi; Alagappan, Muthuraman; Shirato, Hiroki; Chang, Daniel T.; Koong, Albert C.; Li, Ruijiang

2016-01-01

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT "1"8F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162 robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Cui, Yi [Department of Radiation Oncology, Stanford University, Palo Alto, California (United States); Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan); Song, Jie; Pollom, Erqi; Alagappan, Muthuraman [Department of Radiation Oncology, Stanford University, Palo Alto, California (United States); Shirato, Hiroki [Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan); Chang, Daniel T.; Koong, Albert C. [Department of Radiation Oncology, Stanford University, Palo Alto, California (United States); Stanford Cancer Institute, Stanford, California (United States); Li, Ruijiang, E-mail: rli2@stanford.edu [Department of Radiation Oncology, Stanford University, Palo Alto, California (United States); Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan); Stanford Cancer Institute, Stanford, California (United States)

2016-09-01

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162 robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

Science.gov (United States)

Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Imaging Biomarkers for Adult Medulloblastomas

DEFF Research Database (Denmark)

Keil, V C; Warmuth-Metz, M; Reh, C

2017-01-01

BACKGROUND AND PURPOSE: The occurrence of medulloblastomas in adults is rare; nevertheless, these tumors can be subdivided into genetic and histologic entities each having distinct prognoses. This study aimed to identify MR imaging biomarkers to classify these entities and to uncover differences ...

Imaging Biomarkers for Adult Medulloblastomas: Genetic Entities May Be Identified by Their MR Imaging Radiophenotype.

Science.gov (United States)

Keil, V C; Warmuth-Metz, M; Reh, C; Enkirch, S J; Reinert, C; Beier, D; Jones, D T W; Pietsch, T; Schild, H H; Hattingen, E; Hau, P

2017-10-01

The occurrence of medulloblastomas in adults is rare; nevertheless, these tumors can be subdivided into genetic and histologic entities each having distinct prognoses. This study aimed to identify MR imaging biomarkers to classify these entities and to uncover differences in MR imaging biomarkers identified in pediatric medulloblastomas. Eligible preoperative MRIs from 28 patients (11 women; 22-53 years of age) of the Multicenter Pilot-study for the Therapy of Medulloblastoma of Adults (NOA-7) cohort were assessed by 3 experienced neuroradiologists. Lesions and perifocal edema were volumetrized and multiparametrically evaluated for classic morphologic characteristics, location, hydrocephalus, and Chang criteria. To identify MR imaging biomarkers, we correlated genetic entities sonic hedgehog ( SHH ) TP53 wild type, wingless ( WNT ), and non -WNT/ non -SHH medulloblastomas (in adults, Group 4), and histologic entities were correlated with the imaging criteria. These MR imaging biomarkers were compared with corresponding data from a pediatric study. There were 19 SHH TP53 wild type (69%), 4 WNT -activated (14%), and 5 Group 4 (17%) medulloblastomas. Six potential MR imaging biomarkers were identified, 3 of which, hydrocephalus ( P = .03), intraventricular macrometastases ( P = .02), and hemorrhage ( P = .04), when combined, could identify WNT medulloblastoma with 100% sensitivity and 88.3% specificity (95% CI, 39.8%-100.0% and 62.6%-95.3%). WNT -activated nuclear β-catenin accumulating medulloblastomas were smaller than the other entities (95% CI, 5.2-22.3 cm 3 versus 35.1-47.6 cm 3 ; P = .03). Hemorrhage was exclusively present in non -WNT/ non -SHH medulloblastomas ( P = .04; n = 2/5). MR imaging biomarkers were all discordant from those identified in the pediatric cohort. Desmoplastic/nodular medulloblastomas were more rarely in contact with the fourth ventricle (4/15 versus 7/13; P = .04). MR imaging biomarkers can help distinguish histologic and genetic

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics.

Science.gov (United States)

Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana; Hu, Shen

2017-01-01

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients' saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects ( p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity.

The quantitative imaging network: the role of quantitative imaging in radiation therapy

International Nuclear Information System (INIS)

Tandon, Pushpa; Nordstrom, Robert J.; Clark, Laurence

2014-01-01

The potential value of modern medical imaging methods has created a need for mechanisms to develop, translate and disseminate emerging imaging technologies and, ideally, to quantitatively correlate those with other related laboratory methods, such as the genomics and proteomics analyses required to support clinical decisions. One strategy to meet these needs efficiently and cost effectively is to develop an international network to share and reach consensus on best practices, imaging protocols, common databases, and open science strategies, and to collaboratively seek opportunities to leverage resources wherever possible. One such network is the Quantitative Imaging Network (QIN) started by the National Cancer Institute, USA. The mission of the QIN is to improve the role of quantitative imaging for clinical decision making in oncology by the development and validation of data acquisition, analysis methods, and other quantitative imaging tools to predict or monitor the response to drug or radiation therapy. The network currently has 24 teams (two from Canada and 22 from the USA) and several associate members, including one from Tata Memorial Centre, Mumbai, India. Each QIN team collects data from ongoing clinical trials and develops software tools for quantitation and validation to create standards for imaging research, and for use in developing models for therapy response prediction and measurement and tools for clinical decision making. The members of QIN are addressing a wide variety of cancer problems (Head and Neck cancer, Prostrate, Breast, Brain, Lung, Liver, Colon) using multiple imaging modalities (PET, CT, MRI, FMISO PET, DW-MRI, PET-CT). (author)

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis.

Directory of Open Access Journals (Sweden)

Claudia Bühnemann

Full Text Available Driven by genomic somatic variation, tumour tissues are typically heterogeneous, yet unbiased quantitative methods are rarely used to analyse heterogeneity at the protein level. Motivated by this problem, we developed automated image segmentation of images of multiple biomarkers in Ewing sarcoma to generate distributions of biomarkers between and within tumour cells. We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF machine learning. Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. Ki67, pS6, Foxo3a, EGR1, MAPK localised relative to nuclear and cytoplasmic regions of each cell in order to generate image feature distributions. The image distribution features were analysed with RSF in relation to known overall patient survival from three separate cohorts (185 informative cases. Variation in pre-analytical processing resulted in elimination of a high number of non-informative images that had poor DAPI localisation or biomarker preservation (67 cases, 36%. The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. A prognostic classifier for Ewing sarcoma with low cross-validation error rates (0.36 was comprised of multiple features, including the Ki67 proliferative marker and a sub-population of cells with low cytoplasmic/nuclear ratio of CD99. Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis.

Science.gov (United States)

Bühnemann, Claudia; Li, Simon; Yu, Haiyue; Branford White, Harriet; Schäfer, Karl L; Llombart-Bosch, Antonio; Machado, Isidro; Picci, Piero; Hogendoorn, Pancras C W; Athanasou, Nicholas A; Noble, J Alison; Hassan, A Bassim

2014-01-01

Driven by genomic somatic variation, tumour tissues are typically heterogeneous, yet unbiased quantitative methods are rarely used to analyse heterogeneity at the protein level. Motivated by this problem, we developed automated image segmentation of images of multiple biomarkers in Ewing sarcoma to generate distributions of biomarkers between and within tumour cells. We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF) machine learning. Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. Ki67, pS6, Foxo3a, EGR1, MAPK) localised relative to nuclear and cytoplasmic regions of each cell in order to generate image feature distributions. The image distribution features were analysed with RSF in relation to known overall patient survival from three separate cohorts (185 informative cases). Variation in pre-analytical processing resulted in elimination of a high number of non-informative images that had poor DAPI localisation or biomarker preservation (67 cases, 36%). The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case) were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. A prognostic classifier for Ewing sarcoma with low cross-validation error rates (0.36) was comprised of multiple features, including the Ki67 proliferative marker and a sub-population of cells with low cytoplasmic/nuclear ratio of CD99. Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour

Mass spectrometry imaging enriches biomarker discovery approaches with candidate mapping.

Science.gov (United States)

Scott, Alison J; Jones, Jace W; Orschell, Christie M; MacVittie, Thomas J; Kane, Maureen A; Ernst, Robert K

2014-01-01

Integral to the characterization of radiation-induced tissue damage is the identification of unique biomarkers. Biomarker discovery is a challenging and complex endeavor requiring both sophisticated experimental design and accessible technology. The resources within the National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Consortium, Medical Countermeasures Against Radiological Threats (MCART), allow for leveraging robust animal models with novel molecular imaging techniques. One such imaging technique, MALDI (matrix-assisted laser desorption ionization) mass spectrometry imaging (MSI), allows for the direct spatial visualization of lipids, proteins, small molecules, and drugs/drug metabolites-or biomarkers-in an unbiased manner. MALDI-MSI acquires mass spectra directly from an intact tissue slice in discrete locations across an x, y grid that are then rendered into a spatial distribution map composed of ion mass and intensity. The unique mass signals can be plotted to generate a spatial map of biomarkers that reflects pathology and molecular events. The crucial unanswered questions that can be addressed with MALDI-MSI include identification of biomarkers for radiation damage that reflect the response to radiation dose over time and the efficacy of therapeutic interventions. Techniques in MALDI-MSI also enable integration of biomarker identification among diverse animal models. Analysis of early, sublethally irradiated tissue injury samples from diverse mouse tissues (lung and ileum) shows membrane phospholipid signatures correlated with histological features of these unique tissues. This paper will discuss the application of MALDI-MSI for use in a larger biomarker discovery pipeline.

Imaging biomarkers as surrogate endpoints for drug development

International Nuclear Information System (INIS)

Richter, Wolf S.

2006-01-01

The employment of biomarkers (including imaging biomarkers, especially PET) in drug development has gained increasing attention during recent years. This has been partly stimulated by the hope that the integration of biomarkers into drug development programmes may be a means to increase the efficiency and effectiveness of the drug development process by early identification of promising drug candidates - thereby counteracting the rising costs of drug development. More importantly, however, the interest in biomarkers for drug development is the logical consequence of recent advances in biosciences and medicine which are leading to target-specific treatments in the framework of ''personalised medicine''. A considerable proportion of target-specific drugs will show effects in subgroups of patients only. Biomarkers are a means to identify potential responders, or patient subgroups at risk for specific side-effects. Biomarkers are used in early drug development in the context of translational medicine to gain information about the drug's potential in different patient groups and disease states. The information obtained at this stage is mainly important for designing subsequent clinical trials and to identify promising drug candidates. Biomarkers in later phases of clinical development may - if properly validated - serve as surrogate endpoints for clinical outcomes. Regulatory agencies in the EU and the USA have facilitated the use of biomarkers early in the development process. The validation of biomarkers as surrogate endpoints is part of FDA's ''critical path initiative''. (orig.)

Quantitative imaging methods in osteoporosis.

Science.gov (United States)

Oei, Ling; Koromani, Fjorda; Rivadeneira, Fernando; Zillikens, M Carola; Oei, Edwin H G

2016-12-01

Osteoporosis is characterized by a decreased bone mass and quality resulting in an increased fracture risk. Quantitative imaging methods are critical in the diagnosis and follow-up of treatment effects in osteoporosis. Prior radiographic vertebral fractures and bone mineral density (BMD) as a quantitative parameter derived from dual-energy X-ray absorptiometry (DXA) are among the strongest known predictors of future osteoporotic fractures. Therefore, current clinical decision making relies heavily on accurate assessment of these imaging features. Further, novel quantitative techniques are being developed to appraise additional characteristics of osteoporosis including three-dimensional bone architecture with quantitative computed tomography (QCT). Dedicated high-resolution (HR) CT equipment is available to enhance image quality. At the other end of the spectrum, by utilizing post-processing techniques such as the trabecular bone score (TBS) information on three-dimensional architecture can be derived from DXA images. Further developments in magnetic resonance imaging (MRI) seem promising to not only capture bone micro-architecture but also characterize processes at the molecular level. This review provides an overview of various quantitative imaging techniques based on different radiological modalities utilized in clinical osteoporosis care and research.

Image Biomarkers and Precision Medicine: need for validation; Los biomarcadores de imagen y la Medicina de Precision: necesidad de validacion

Energy Technology Data Exchange (ETDEWEB)

Marti-Bonmati, L.; Alberich-Bayarri, A.; Garcia Castro, F.

2016-08-01

Personalized medicine aims to improve the diagnosis, classification and the best treatment for a particular patient. Today, radiologists are challenged to translate new biological discoveries, the different mechanisms of disease and advances in preclinical research, into a clinical reality through patients, images and their associated parameters. In this article we show how digital medical imaging and computational data processing extract numerous quantitative parameters from the obtained images as virtual biopsies. To be implemented in clinical practice, biomarkers should provide useful and relevant information, improving processes diagnostic, therapeutic and monitoring, for the benefit of patients. (Author)

Identification and Quantitation of Biomarkers for Radiation-Induced Injury via Mass Spectrometry

Science.gov (United States)

Jones, Jace W.; Scott, Alison J.; Tudor, Gregory; Xu, Pu-Ting; Jackson, Isabel L.; Vujaskovic, Zeljko; Booth, Catherine; MacVittie, Thomas J.; Ernst, Robert K.; Kane, Maureen A.

2013-01-01

Biomarker identification and validation for radiation exposure is a rapidly expanding field encompassing the need for well-defined animal models and advanced analytical techniques. The resources within the consortium, Medical Countermeasures Against Radiological Threats (MCART), provide a unique opportunity for accessing well-defined animal models that simulate the key sequelae of the acute radiation syndrome and the delayed effects of acute radiation exposure. Likewise, the use of mass spectrometry-based analytical techniques for biomarker discovery and validation enables a robust analytical platform that is amenable to a variety of sample matrices and considered the benchmark for bio-molecular identification and quantitation. Herein, we demonstrate the use of two targeted mass spectrometry approaches to link established MCART animal models to identified metabolite biomarkers. Circulating citrulline concentration was correlated to gross histological gastrointestinal tissue damage and retinoic acid production in lung tissue was established to be reduced at early and late time points post high dose irradiation. Going forward, the use of mass spectrometry-based metabolomics coupled to well-defined animal models provides the unique opportunity for comprehensive biomarker discovery. PMID:24276554

PET imaging biomarkers in head and neck cancer

Energy Technology Data Exchange (ETDEWEB)

Differding, Sarah; Gregoire, Vincent [Universite Catholique de Louvain, St-Luc University Hospital, Department of Radiation Oncology, and Center for Molecular Imaging, Radiotherapy and Oncology (MIRO), Institut de Recherche Experimentale et Clinique (IREC), Brussels (Belgium); Hanin, Francois-Xavier [Universite Catholique de Louvain, St-Luc University Hospital, Department of Nuclear Medicine, and Center for Molecular Imaging, Radiotherapy and Oncology (MIRO), Institut de Recherche Experimentale et Clinique (IREC), Brussels (Belgium)

2015-04-01

In locally advanced head and neck squamous cell carcinoma (HNSCC), the role of imaging becomes more and more critical in the management process. In this framework, molecular imaging techniques such as PET allow noninvasive assessment of a range of tumour biomarkers such as metabolism, hypoxia and proliferation, which can serve different purposes. First, in a pretreatment setting they can influence therapy selection strategies and target delineation for radiation therapy. Second, their predictive and/or prognostic value could help enhance the therapeutic ratio in the management of HNSCC. Third, treatment modification can be performed through the generation of a molecular-based heterogeneous dose distribution with dose escalation to the most resistant parts of the tumour, a concept known as dose painting. Fourth, they are increasingly becoming a tool for monitoring response to therapy. In this review, PET imaging biomarkers used in the routine management of HNSCC or under investigation are discussed. (orig.)

Use of quantitative SPECT/CT reconstruction in 99mTc-sestamibi imaging of patients with renal masses.

Science.gov (United States)

Jones, Krystyna M; Solnes, Lilja B; Rowe, Steven P; Gorin, Michael A; Sheikhbahaei, Sara; Fung, George; Frey, Eric C; Allaf, Mohamad E; Du, Yong; Javadi, Mehrbod S

2018-02-01

Technetium-99m ( 99m Tc)-sestamibi single-photon emission computed tomography/computed tomography (SPECT/CT) has previously been shown to allow for the accurate differentiation of benign renal oncocytomas and hybrid oncocytic/chromophobe tumors (HOCTs) apart from other malignant renal tumor histologies, with oncocytomas/HOCTs showing high uptake and renal cell carcinoma (RCC) showing low uptake based on uptake ratios from non-quantitative single-photon emission computed tomography (SPECT) reconstructions. However, in this study, several tumors fell close to the uptake ratio cutoff, likely due to limitations in conventional SPECT/CT reconstruction methods. We hypothesized that application of quantitative SPECT/CT (QSPECT) reconstruction methods developed by our group would provide more robust separation of hot and cold lesions, serving as an imaging framework on which quantitative biomarkers can be validated for evaluation of renal masses with 99m Tc-sestamibi. Single-photon emission computed tomography data were reconstructed using the clinical Flash 3D reconstruction and QSPECT methods. Two blinded readers then characterized each tumor as hot or cold. Semi-quantitative uptake ratios were calculated by dividing lesion activity by background renal activity for both Flash 3D and QSPECT reconstructions. The difference between median (mean) hot and cold tumor uptake ratios measured 0.655 (0.73) with the QSPECT method and 0.624 (0.67) with the conventional method, resulting in increased separation between hot and cold tumors. Sub-analysis of 7 lesions near the separation point showed a higher absolute difference (0.16) between QPSECT and Flash 3D mean uptake ratios compared to the remaining lesions. Our finding of improved separation between uptake ratios of hot and cold lesions using QSPECT reconstruction lays the foundation for additional quantitative SPECT techniques such as SPECT-UV in the setting of renal 99m Tc-sestamibi and other SPECT/CT exams. With robust

Dual-energy CT iodine maps as an alternative quantitative imaging biomarker to abdominal CT perfusion: determination of appropriate trigger delays for acquisition using bolus tracking.

Science.gov (United States)

Skornitzke, Stephan; Fritz, Franziska; Mayer, Philipp; Koell, Marco; Hansen, Jens; Pahn, Gregor; Hackert, Thilo; Kauczor, Hans-Ulrich; Stiller, Wolfram

2018-05-01

Quantitative evaluation of different bolus tracking trigger delays for acquisition of dual energy (DE) CT iodine maps as an alternative to CT perfusion. Prior to this retrospective analysis of prospectively acquired data, DECT perfusion sequences were dynamically acquired in 22 patients with pancreatic carcinoma using dual source CT at 80/140 kV p with tin filtration. After deformable motion-correction, perfusion maps of blood flow (BF) were calculated from 80 kV p image series of DECT, and iodine maps were calculated for each of the 34 DECT acquisitions per patient. BF and iodine concentrations were measured in healthy pancreatic tissue and carcinoma. To evaluate potential DECT acquisition triggered by bolus tracking, measured iodine concentrations from the 34 DECT acquisitions per patient corresponding to different trigger delays were assessed for correlation to BF and intergroup differences between tissue types depending on acquisition time. Average BF measured in healthy pancreatic tissue and carcinoma was 87.6 ± 28.4 and 38.6 ± 22.2 ml/100 ml min -1 , respectively. Correlation between iodine concentrations and BF was statistically significant for bolus tracking with trigger delay greater than 0 s (r max = 0.89; p alternative to CT perfusion measurements of BF. Advances in knowledge: After clinical validation, DECT iodine maps of pancreas acquired using bolus tracking with appropriate trigger delay as determined in this study could offer an alternative quantitative imaging biomarker providing functional information for tumor assessment at reduced patient radiation exposure compared to CT perfusion measurements of BF.

A Delphic consensus assessment: imaging and biomarkers in gastroenteropancreatic neuroendocrine tumor disease management

Directory of Open Access Journals (Sweden)

Kjell Oberg

2016-09-01

Full Text Available The complexity of the clinical management of neuroendocrine neoplasia (NEN is exacerbated by limitations in imaging modalities and a paucity of clinically useful biomarkers. Limitations in currently available imaging modalities reflect difficulties in measuring an intrinsically indolent disease, resolution inadequacies and inter-/intra-facility device variability and that RECIST (Response Evaluation Criteria in Solid Tumors criteria are not optimal for NEN. Limitations of currently used biomarkers are that they are secretory biomarkers (chromogranin A, serotonin, neuron-specific enolase and pancreastatin; monoanalyte measurements; and lack sensitivity, specificity and predictive capacity. None of them meet the NIH metrics for clinical usage. A multinational, multidisciplinary Delphi consensus meeting of NEN experts (n = 33 assessed current imaging strategies and biomarkers in NEN management. Consensus (>75% was achieved for 78% of the 142 questions. The panel concluded that morphological imaging has a diagnostic value. However, both imaging and current single-analyte biomarkers exhibit substantial limitations in measuring the disease status and predicting the therapeutic efficacy. RECIST remains suboptimal as a metric. A critical unmet need is the development of a clinico-biological tool to provide enhanced information regarding precise disease status and treatment response. The group considered that circulating RNA was better than current general NEN biomarkers and preliminary clinical data were considered promising. It was resolved that circulating multianalyte mRNA (NETest had clinical utility in both diagnosis and monitoring disease status and therapeutic efficacy. Overall, it was concluded that a combination of tumor spatial and functional imaging with circulating transcripts (mRNA would represent the future strategy for real-time monitoring of disease progress and therapeutic efficacy.

Radiological interpretation 2020: Toward quantitative image assessment

International Nuclear Information System (INIS)

Boone, John M.

2007-01-01

The interpretation of medical images by radiologists is primarily and fundamentally a subjective activity, but there are a number of clinical applications such as tumor imaging where quantitative imaging (QI) metrics (such as tumor growth rate) would be valuable to the patient’s care. It is predicted that the subjective interpretive environment of the past will, over the next decade, evolve toward the increased use of quantitative metrics for evaluating patient health from images. The increasing sophistication and resolution of modern tomographic scanners promote the development of meaningful quantitative end points, determined from images which are in turn produced using well-controlled imaging protocols. For the QI environment to expand, medical physicists, physicians, other researchers and equipment vendors need to work collaboratively to develop the quantitative protocols for imaging, scanner calibrations, and robust analytical software that will lead to the routine inclusion of quantitative parameters in the diagnosis and therapeutic assessment of human health. Most importantly, quantitative metrics need to be developed which have genuine impact on patient diagnosis and welfare, and only then will QI techniques become integrated into the clinical environment.

The Functional Diffusion Map: An Imaging Biomarker for the Early Prediction of Cancer Treatment Outcome

Directory of Open Access Journals (Sweden)

Bradford A. Moffat

2006-04-01

Full Text Available Functional diffusion map (fDM has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This MRI approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival. Serial T2-weighted and diffusion MRI were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.. All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dosedependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival. Therefore, the fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.

Quantitative analysis of receptor imaging

International Nuclear Information System (INIS)

Fu Zhanli; Wang Rongfu

2004-01-01

Model-based methods for quantitative analysis of receptor imaging, including kinetic, graphical and equilibrium methods, are introduced in detail. Some technical problem facing quantitative analysis of receptor imaging, such as the correction for in vivo metabolism of the tracer and the radioactivity contribution from blood volume within ROI, and the estimation of the nondisplaceable ligand concentration, is also reviewed briefly

Applying Data-driven Imaging Biomarker in Mammography for Breast Cancer Screening: Preliminary Study

OpenAIRE

Kim, Eun-Kyung; Kim, Hyo-Eun; Han, Kyunghwa; Kang, Bong Joo; Sohn, Yu-Mee; Woo, Ok Hee; Lee, Chan Wha

2018-01-01

We assessed the feasibility of a data-driven imaging biomarker based on weakly supervised learning (DIB; an imaging biomarker derived from large-scale medical image data with deep learning technology) in mammography (DIB-MG). A total of 29,107 digital mammograms from five institutions (4,339 cancer cases and 24,768 normal cases) were included. After matching patients’ age, breast density, and equipment, 1,238 and 1,238 cases were chosen as validation and test sets, respectively, and the remai...

Urinary bladder cancer T-staging from T2-weighted MR images using an optimal biomarker approach

Science.gov (United States)

Wang, Chuang; Udupa, Jayaram K.; Tong, Yubing; Chen, Jerry; Venigalla, Sriram; Odhner, Dewey; Guzzo, Thomas J.; Christodouleas, John; Torigian, Drew A.

2018-02-01

Magnetic resonance imaging (MRI) is often used in clinical practice to stage patients with bladder cancer to help plan treatment. However, qualitative assessment of MR images is prone to inaccuracies, adversely affecting patient outcomes. In this paper, T2-weighted MR image-based quantitative features were extracted from the bladder wall in 65 patients with bladder cancer to classify them into two primary tumor (T) stage groups: group 1 - T stage T2, with primary tumor locally confined to the bladder, and group 2 - T stage T2, with primary tumor locally extending beyond the bladder. The bladder was divided into 8 sectors in the axial plane, where each sector has a corresponding reference standard T stage that is based on expert radiology qualitative MR image review and histopathologic results. The performance of the classification for correct assignment of T stage grouping was then evaluated at both the patient level and the sector level. Each bladder sector was divided into 3 shells (inner, middle, and outer), and 15,834 features including intensity features and texture features from local binary pattern and gray-level co-occurrence matrix were extracted from the 3 shells of each sector. An optimal feature set was selected from all features using an optimal biomarker approach. Nine optimal biomarker features were derived based on texture properties from the middle shell, with an area under the ROC curve of AUC value at the sector and patient level of 0.813 and 0.806, respectively.

Prostate Cancer Imaging and Biomarkers Guiding Safe Selection of Active Surveillance

Directory of Open Access Journals (Sweden)

Zachary A. Glaser

2017-10-01

Full Text Available BackgroundActive surveillance (AS is a widely adopted strategy to monitor men with low-risk, localized prostate cancer (PCa. Current AS inclusion criteria may misclassify as many as one in four patients. The advent of multiparametric magnetic resonance imaging (mpMRI and novel PCa biomarkers may offer improved risk stratification. We performed a review of recently published literature to characterize emerging evidence in support of these novel modalities.MethodsAn English literature search was conducted on PubMed for available original investigations on localized PCa, AS, imaging, and biomarkers published within the past 3 years. Our Boolean criteria included the following terms: PCa, AS, imaging, biomarker, genetic, genomic, prospective, retrospective, and comparative. The bibliographies and diagnostic modalities of the identified studies were used to expand our search.ResultsOur review identified 222 original studies. Our expanded search yielded 244 studies. Among these, 70 met our inclusion criteria. Evidence suggests mpMRI offers improved detection of clinically significant PCa, and MRI-fusion technology enhances the sensitivity of surveillance biopsies. Multiple studies demonstrate the promise of commercially available screening assays for prediction of AS failure, and several novel biomarkers show promise in this setting.ConclusionIn the era of AS for men with low-risk PCa, improved strategies for proper stratification are needed. mpMRI has dramatically enhanced the detection of clinically significant PCa. The advent of novel biomarkers for prediction of aggressive disease and AS failure has shown some initial promise, but further validation is warranted.

Quantitative phase imaging of arthropods

Science.gov (United States)

Sridharan, Shamira; Katz, Aron; Soto-Adames, Felipe; Popescu, Gabriel

2015-11-01

Classification of arthropods is performed by characterization of fine features such as setae and cuticles. An unstained whole arthropod specimen mounted on a slide can be preserved for many decades, but is difficult to study since current methods require sample manipulation or tedious image processing. Spatial light interference microscopy (SLIM) is a quantitative phase imaging (QPI) technique that is an add-on module to a commercial phase contrast microscope. We use SLIM to image a whole organism springtail Ceratophysella denticulata mounted on a slide. This is the first time, to our knowledge, that an entire organism has been imaged using QPI. We also demonstrate the ability of SLIM to image fine structures in addition to providing quantitative data that cannot be obtained by traditional bright field microscopy.

DWI as an Imaging Biomarker for Bladder Cancer

NARCIS (Netherlands)

Yoshida, Soichiro; Takahara, Taro; Kwee, Thomas C.; Waseda, Yuma; Kobayashi, Shuichiro; Fujii, Yasuhisa

OBJECTIVE. DWI has been increasingly applied in the management of bladder cancer. In this article, we discuss the role of DWI as an imaging biomarker for bladder cancer. CONCLUSION. The DWI signal is derived from the motion of water molecules, which represents the physiologic characteristics of the

Quantitative fluorescence microscopy and image deconvolution.

Science.gov (United States)

Swedlow, Jason R

2013-01-01

Quantitative imaging and image deconvolution have become standard techniques for the modern cell biologist because they can form the basis of an increasing number of assays for molecular function in a cellular context. There are two major types of deconvolution approaches--deblurring and restoration algorithms. Deblurring algorithms remove blur but treat a series of optical sections as individual two-dimensional entities and therefore sometimes mishandle blurred light. Restoration algorithms determine an object that, when convolved with the point-spread function of the microscope, could produce the image data. The advantages and disadvantages of these methods are discussed in this chapter. Image deconvolution in fluorescence microscopy has usually been applied to high-resolution imaging to improve contrast and thus detect small, dim objects that might otherwise be obscured. Their proper use demands some consideration of the imaging hardware, the acquisition process, fundamental aspects of photon detection, and image processing. This can prove daunting for some cell biologists, but the power of these techniques has been proven many times in the works cited in the chapter and elsewhere. Their usage is now well defined, so they can be incorporated into the capabilities of most laboratories. A major application of fluorescence microscopy is the quantitative measurement of the localization, dynamics, and interactions of cellular factors. The introduction of green fluorescent protein and its spectral variants has led to a significant increase in the use of fluorescence microscopy as a quantitative assay system. For quantitative imaging assays, it is critical to consider the nature of the image-acquisition system and to validate its response to known standards. Any image-processing algorithms used before quantitative analysis should preserve the relative signal levels in different parts of the image. A very common image-processing algorithm, image deconvolution, is used

Quantitative image analysis of intra-tumoral bFGF level as a molecular marker of paclitaxel resistance

Directory of Open Access Journals (Sweden)

Wientjes M Guillaume

2008-01-01

on the merit of using plasma or urine bFGF level as a prognostic indicator. Conclusion The present study established a quantitative image analysis method that enabled the measurement of intratumoral bFGF level in archived tissues. The ability to quantify a potential biomarker provided the opportunity to study the relationship between the biomarker and chemosensitivity in tumor subgroups and thereby enabled hypothesis generation for additional translational research.

Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema

DEFF Research Database (Denmark)

Lassere, Marissa N; Johnson, Kent R; Boers, Maarten

2007-01-01

endpoints, and leading indicators, a quantitative surrogate validation schema was developed and subsequently evaluated at a stakeholder workshop. RESULTS: The search identified several classification schema and definitions. Components of these were incorporated into a new quantitative surrogate validation...... level of evidence schema that evaluates biomarkers along 4 domains: Target, Study Design, Statistical Strength, and Penalties. Scores derived from 3 domains the Target that the marker is being substituted for, the Design of the (best) evidence, and the Statistical strength are additive. Penalties...... of the National Institutes of Health definitions of biomarker, surrogate endpoint, and clinical endpoint was useful. CONCLUSION: Further development and application of this schema provides incentives and guidance for effective biomarker and surrogate endpoint research, and more efficient drug discovery...

TH-A-207B-01: Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity

International Nuclear Information System (INIS)

Chen, S.

2016-01-01

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will target these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging

TH-A-207B-01: Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity

Energy Technology Data Exchange (ETDEWEB)

Chen, S. [Mayo Clinic (United States)

2016-06-15

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will target these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging

UK quantitative WB-DWI technical workgroup: consensus meeting recommendations on optimisation, quality control, processing and analysis of quantitative whole-body diffusion-weighted imaging for cancer.

Science.gov (United States)

Barnes, Anna; Alonzi, Roberto; Blackledge, Matthew; Charles-Edwards, Geoff; Collins, David J; Cook, Gary; Coutts, Glynn; Goh, Vicky; Graves, Martin; Kelly, Charles; Koh, Dow-Mu; McCallum, Hazel; Miquel, Marc E; O'Connor, James; Padhani, Anwar; Pearson, Rachel; Priest, Andrew; Rockall, Andrea; Stirling, James; Taylor, Stuart; Tunariu, Nina; van der Meulen, Jan; Walls, Darren; Winfield, Jessica; Punwani, Shonit

2018-01-01

Application of whole body diffusion-weighted MRI (WB-DWI) for oncology are rapidly increasing within both research and routine clinical domains. However, WB-DWI as a quantitative imaging biomarker (QIB) has significantly slower adoption. To date, challenges relating to accuracy and reproducibility, essential criteria for a good QIB, have limited widespread clinical translation. In recognition, a UK workgroup was established in 2016 to provide technical consensus guidelines (to maximise accuracy and reproducibility of WB-MRI QIBs) and accelerate the clinical translation of quantitative WB-DWI applications for oncology. A panel of experts convened from cancer centres around the UK with subspecialty expertise in quantitative imaging and/or the use of WB-MRI with DWI. A formal consensus method was used to obtain consensus agreement regarding best practice. Questions were asked about the appropriateness or otherwise on scanner hardware and software, sequence optimisation, acquisition protocols, reporting, and ongoing quality control programs to monitor precision and accuracy and agreement on quality control. The consensus panel was able to reach consensus on 73% (255/351) items and based on consensus areas made recommendations to maximise accuracy and reproducibly of quantitative WB-DWI studies performed at 1.5T. The panel were unable to reach consensus on the majority of items related to quantitative WB-DWI performed at 3T. This UK Quantitative WB-DWI Technical Workgroup consensus provides guidance on maximising accuracy and reproducibly of quantitative WB-DWI for oncology. The consensus guidance can be used by researchers and clinicians to harmonise WB-DWI protocols which will accelerate clinical translation of WB-DWI-derived QIBs.

TU-AB-BRA-05: Repeatability of [F-18]-NaF PET Imaging Biomarkers for Bone Lesions: A Multicenter Study

International Nuclear Information System (INIS)

Lin, C; Bradshaw, T; Perk, T; Harmon, S; Jeraj, R; Liu, G

2015-01-01

Purpose: Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While therapeutic efficacy has been traditionally quantified by SUV metrics, imaging texture features have shown potential for use as quantitative biomarkers. In this study we evaluated the repeatability of quantitative "1"8F-NaF PET-derived SUV metrics and texture features in bone lesions from patients in a multicenter study. Methods: Twenty-nine metastatic castrate-resistant prostate cancer patients received whole-body test-retest NaF PET/CT scans from one of three harmonized imaging centers. Bone lesions of volume greater than 1.5 cm"3 were identified and automatically segmented using a SUV>15 threshold. From each lesion, 55 NaF PET-derived texture features (including first-order, co-occurrence, grey-level run-length, neighbor gray-level, and neighbor gray-tone difference matrix) were extracted. The test-retest repeatability of each SUV metric and texture feature was assessed with Bland-Altman analysis. Results: A total of 315 bone lesions were evaluated. Of the traditional SUV metrics, the repeatability coefficient (RC) was 12.6 SUV for SUVmax, 2.5 SUV for SUVmean, and 4.3 cm"3 for volume. Their respective intralesion coefficients of variation (COVs) were 12%, 17%, and 6%. Of the texture features, COV was lowest for entropy (0.03%) and highest for kurtosis (105%). Lesion intraclass correlation coefficient (ICC) was lowest for maximum correlation coefficient (ICC=0.848), and highest for entropy (ICC=0.985). Across imaging centers, repeatability of texture features and SUV varied. For example, across imaging centers, COV for SUVmax ranged between 11–23%. Conclusion: Many NaF PET-derived SUV metrics and texture features for bone lesions demonstrated high repeatability, such as SUVmax, entropy, and volume. Several imaging texture features demonstrated poor repeatability, such as SUVtotal and SUVstd. These results can be used to establish response criteria

Identification of circulating miRNA biomarkers based on global quantitative real-time PCR profiling

Directory of Open Access Journals (Sweden)

Kang Kang

2012-02-01

Full Text Available Abstract MicroRNAs (miRNAs are small noncoding RNAs (18-25 nucleotides that regulate gene expression at the post-transcriptional level. Recent studies have demonstrated the presence of miRNAs in the blood circulation. Deregulation of miRNAs in serum or plasma has been associated with many diseases including cancers and cardiovascular diseases, suggesting the possible use of miRNAs as diagnostic biomarkers. However, the detection of the small amount of miRNAs found in serum or plasma requires a method with high sensitivity and accuracy. Therefore, the current study describes polymerase chain reaction (PCR-based methods for measuring circulating miRNAs. Briefly, the procedure involves four major steps: (1 sample collection and preparation; (2 global miRNAs profiling using quantitative real-time PCR (qRT-PCR; (3 data normalization and analysis; and (4 selection and validation of miRNA biomarkers. In conclusion, qRT-PCR is a promising method for profiling of circulating miRNAs as biomarkers.

Quantitative image analysis of synovial tissue

NARCIS (Netherlands)

van der Hall, Pascal O.; Kraan, Maarten C.; Tak, Paul Peter

2007-01-01

Quantitative image analysis is a form of imaging that includes microscopic histological quantification, video microscopy, image analysis, and image processing. Hallmarks are the generation of reliable, reproducible, and efficient measurements via strict calibration and step-by-step control of the

Quantitative information in medical imaging

International Nuclear Information System (INIS)

Deconinck, F.

1985-01-01

When developing new imaging or image processing techniques, one constantly has in mind that the new technique should provide a better, or more optimal answer to medical tasks than existing techniques do 'Better' or 'more optimal' imply some kind of standard by which one can measure imaging or image processing performance. The choice of a particular imaging modality to answer a diagnostic task, such as the detection of coronary artery stenosis is also based on an implicit optimalisation of performance criteria. Performance is measured by the ability to provide information about an object (patient) to the person (referring doctor) who ordered a particular task. In medical imaging the task is generally to find quantitative information on bodily function (biochemistry, physiology) and structure (histology, anatomy). In medical imaging, a wide range of techniques is available. Each technique has it's own characteristics. The techniques discussed in this paper are: nuclear magnetic resonance, X-ray fluorescence, scintigraphy, positron emission tomography, applied potential tomography, computerized tomography, and compton tomography. This paper provides a framework for the comparison of imaging performance, based on the way the quantitative information flow is altered by the characteristics of the modality

A multiplex quantitative proteomics strategy for protein biomarker studies in urinary exosomes.

Science.gov (United States)

Raj, Delfin A A; Fiume, Immacolata; Capasso, Giovambattista; Pocsfalvi, Gabriella

2012-06-01

Urinary exosomes have received considerable attention as a potential biomarker source for the diagnosis of renal diseases. Notwithstanding, their use in protein biomarker research is hampered by the lack of efficient methods for vesicle isolation, lysis, and protein quantification. Here we report an improved ultracentrifugation-based method that facilitates the solubilization and removal of major impurities associated with urinary exosomes. A double-cushion sucrose/D(2)O centrifugation step was used after a two-step differential centrifugation to separate exosomes from the heavier vesicles. After the removal of uromodulin, 378 and 79 unique proteins were identified, respectively, in low- and high-density fractions. Comparison of our data with two previously published data sets helped to define proteins commonly found in urinary exosomes. Lysis, protein extraction, and in-solution digestion of exosomes were then optimized for MudPIT application. More than a hundred exosomal proteins were quantified by four-plex iTRAQ analysis of single and pooled samples from two different age groups. For healthy men, six proteins (TSN1, PODXL, IDHC, PPAP, ACBP, and ANXA5) showed significant expression differences between exosome pools of those aged 25-50 and 50-70 years old. Thus, exosomes isolated by our method provide the basis for the development of robust quantitative methods for protein biomarker research.

Biomarker discovery in high grade sarcomas by mass spectrometry imaging

OpenAIRE

Lou, S.

2017-01-01

This thesis demonstrates a detailed biomarker discovery Mass Spectrometry Imaging workflow for histologically heterogeneous high grade sarcomas. Panels of protein and metabolite signatures were discovered either distinguishing different histological subtypes or stratifying high risk patients with poor survival.

Quantitative reconstruction from a single diffraction-enhanced image

International Nuclear Information System (INIS)

Paganin, D.M.; Lewis, R.A.; Kitchen, M.

2003-01-01

Full text: We develop an algorithm for using a single diffraction-enhanced image (DEI) to obtain a quantitative reconstruction of the projected thickness of a single-material sample which is embedded within a substrate of approximately constant thickness. This algorithm is used to quantitatively map inclusions in a breast phantom, from a single synchrotron DEI image. In particular, the reconstructed images quantitatively represent the projected thickness in the bulk of the sample, in contrast to DEI images which greatly emphasise sharp edges (high spatial frequencies). In the context of an ultimate aim of improved methods for breast cancer detection, the reconstructions are potentially of greater diagnostic value compared to the DEI data. Lastly, we point out that the methods of analysis presented here are also applicable to the quantitative analysis of differential interference contrast (DIC) images

Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema.

Science.gov (United States)

Lassere, Marissa N; Johnson, Kent R; Boers, Maarten; Tugwell, Peter; Brooks, Peter; Simon, Lee; Strand, Vibeke; Conaghan, Philip G; Ostergaard, Mikkel; Maksymowych, Walter P; Landewe, Robert; Bresnihan, Barry; Tak, Paul-Peter; Wakefield, Richard; Mease, Philip; Bingham, Clifton O; Hughes, Michael; Altman, Doug; Buyse, Marc; Galbraith, Sally; Wells, George

2007-03-01

There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Our objective was to review the literature on biomarkers and surrogates to develop a hierarchical schema that systematically evaluates and ranks the surrogacy status of biomarkers and surrogates; and to obtain feedback from stakeholders. After a systematic search of Medline and Embase on biomarkers, surrogate (outcomes, endpoints, markers, indicators), intermediate endpoints, and leading indicators, a quantitative surrogate validation schema was developed and subsequently evaluated at a stakeholder workshop. The search identified several classification schema and definitions. Components of these were incorporated into a new quantitative surrogate validation level of evidence schema that evaluates biomarkers along 4 domains: Target, Study Design, Statistical Strength, and Penalties. Scores derived from 3 domains the Target that the marker is being substituted for, the Design of the (best) evidence, and the Statistical strength are additive. Penalties are then applied if there is serious counterevidence. A total score (0 to 15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. It was proposed that the term "surrogate" be restricted to markers attaining Levels 1 or 2 only. Most stakeholders agreed that this operationalization of the National Institutes of Health definitions of biomarker, surrogate endpoint, and clinical endpoint was useful. Further development and application of this schema provides incentives and guidance for effective biomarker and surrogate endpoint research, and more efficient drug discovery, development, and approval.

Quantitative background parenchymal uptake on molecular breast imaging and breast cancer risk: a case-control study.

Science.gov (United States)

Hruska, Carrie B; Geske, Jennifer R; Swanson, Tiffinee N; Mammel, Alyssa N; Lake, David S; Manduca, Armando; Conners, Amy Lynn; Whaley, Dana H; Scott, Christopher G; Carter, Rickey E; Rhodes, Deborah J; O'Connor, Michael K; Vachon, Celine M

2018-06-05

measurement of BPU, defined as the ratio of average counts in fibroglandular tissue relative to that in fat, can be reliably performed by nonradiologist operators with a simple region-of-interest analysis tool. Similar to results obtained with subjective BPU categories, quantitative BPU is a functional imaging biomarker of breast cancer risk, independent of mammographic density and hormonal factors.

Some exercises in quantitative NMR imaging

International Nuclear Information System (INIS)

Bakker, C.J.G.

1985-01-01

The articles represented in this thesis result from a series of investigations that evaluate the potential of NMR imaging as a quantitative research tool. In the first article the possible use of proton spin-lattice relaxation time T 1 in tissue characterization, tumor recognition and monitoring tissue response to radiotherapy is explored. The next article addresses the question whether water proton spin-lattice relaxation curves of biological tissues are adequately described by a single time constant T 1 , and analyzes the implications of multi-exponentiality for quantitative NMR imaging. In the third article the use of NMR imaging as a quantitative research tool is discussed on the basis of phantom experiments. The fourth article describes a method which enables unambiguous retrieval of sign information in a set of magnetic resonance images of the inversion recovery type. The next article shows how this method can be adapted to allow accurate calculation of T 1 pictures on a pixel-by-pixel basis. The sixth article, finally, describes a simulation procedure which enables a straightforward determination of NMR imaging pulse sequence parameters for optimal tissue contrast. (orig.)

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

KAUST Repository

Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J.

2014-01-01

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent

Age and neurodegeneration imaging biomarkers in persons with Alzheimer disease dementia.

Science.gov (United States)

Knopman, David S; Jack, Clifford R; Wiste, Heather J; Weigand, Stephen D; Vemuri, Prashanthi; Lowe, Val J; Kantarci, Kejal; Gunter, Jeffrey L; Senjem, Matthew L; Mielke, Michelle M; Machulda, Mary M; Roberts, Rosebud O; Boeve, Bradley F; Jones, David T; Petersen, Ronald C

2016-08-16

To examine neurodegenerative imaging biomarkers in Alzheimer disease (AD) dementia from middle to old age. Persons with AD dementia and elevated brain β-amyloid with Pittsburgh compound B (PiB)-PET imaging underwent [(18)F]-fluorodeoxyglucose (FDG)-PET and structural MRI. We evaluated 3 AD-related neurodegeneration biomarkers: hippocampal volume adjusted for total intracranial volume (HVa), FDG standardized uptake value ratio (SUVR) in regions of interest linked to AD, and cortical thickness in AD-related regions of interest. We examined associations of each biomarker with age and evaluated age effects on cutpoints defined by the 90th percentile in AD dementia. We assembled an age-, sex-, and intracranial volume-matched group of 194 similarly imaged clinically normal (CN) persons. The 97 participants with AD dementia (aged 49-93 years) had PiB SUVR ≥1.8. A nonlinear (inverted-U) relationship between FDG SUVR and age was seen in the AD group but an inverse linear relationship with age was seen in the CN group. Cortical thickness had an inverse linear relationship with age in AD but a nonlinear (flat, then inverse linear) relationship in the CN group. HVa showed an inverse linear relationship with age in both AD and CN groups. Age effects on 90th percentile cutpoints were small for FDG SUVR and cortical thickness, but larger for HVa. In persons with AD dementia with elevated PiB SUVR, values of each neurodegeneration biomarker were associated with age. Cortical thickness had the smallest differences in 90th percentile cutpoints from middle to old age, and HVa the largest differences. © 2016 American Academy of Neurology.

The evolution of medical imaging from qualitative to quantitative: opportunities, challenges, and approaches (Conference Presentation)

Science.gov (United States)

Jackson, Edward F.

2016-04-01

Over the past decade, there has been an increasing focus on quantitative imaging biomarkers (QIBs), which are defined as "objectively measured characteristics derived from in vivo images as indicators of normal biological processes, pathogenic processes, or response to a therapeutic intervention"1. To evolve qualitative imaging assessments to the use of QIBs requires the development and standardization of data acquisition, data analysis, and data display techniques, as well as appropriate reporting structures. As such, successful implementation of QIB applications relies heavily on expertise from the fields of medical physics, radiology, statistics, and informatics as well as collaboration from vendors of imaging acquisition, analysis, and reporting systems. When successfully implemented, QIBs will provide image-derived metrics with known bias and variance that can be validated with anatomically and physiologically relevant measures, including treatment response (and the heterogeneity of that response) and outcome. Such non-invasive quantitative measures can then be used effectively in clinical and translational research and will contribute significantly to the goals of precision medicine. This presentation will focus on 1) outlining the opportunities for QIB applications, with examples to demonstrate applications in both research and patient care, 2) discussing key challenges in the implementation of QIB applications, and 3) providing overviews of efforts to address such challenges from federal, scientific, and professional organizations, including, but not limited to, the RSNA, NCI, FDA, and NIST. 1Sullivan, Obuchowski, Kessler, et al. Radiology, epub August 2015.

Quantitative metagenomics reveals unique gut microbiome biomarkers in ankylosing spondylitis.

Science.gov (United States)

Wen, Chengping; Zheng, Zhijun; Shao, Tiejuan; Liu, Lin; Xie, Zhijun; Le Chatelier, Emmanuelle; He, Zhixing; Zhong, Wendi; Fan, Yongsheng; Zhang, Linshuang; Li, Haichang; Wu, Chunyan; Hu, Changfeng; Xu, Qian; Zhou, Jia; Cai, Shunfeng; Wang, Dawei; Huang, Yun; Breban, Maxime; Qin, Nan; Ehrlich, Stanislav Dusko

2017-07-27

The assessment and characterization of the gut microbiome has become a focus of research in the area of human autoimmune diseases. Ankylosing spondylitis is an inflammatory autoimmune disease and evidence showed that ankylosing spondylitis may be a microbiome-driven disease. To investigate the relationship between the gut microbiome and ankylosing spondylitis, a quantitative metagenomics study based on deep shotgun sequencing was performed, using gut microbial DNA from 211 Chinese individuals. A total of 23,709 genes and 12 metagenomic species were shown to be differentially abundant between ankylosing spondylitis patients and healthy controls. Patients were characterized by a form of gut microbial dysbiosis that is more prominent than previously reported cases with inflammatory bowel disease. Specifically, the ankylosing spondylitis patients demonstrated increases in the abundance of Prevotella melaninogenica, Prevotella copri, and Prevotella sp. C561 and decreases in Bacteroides spp. It is noteworthy that the Bifidobacterium genus, which is commonly used in probiotics, accumulated in the ankylosing spondylitis patients. Diagnostic algorithms were established using a subset of these gut microbial biomarkers. Alterations of the gut microbiome are associated with development of ankylosing spondylitis. Our data suggest biomarkers identified in this study might participate in the pathogenesis or development process of ankylosing spondylitis, providing new leads for the development of new diagnostic tools and potential treatments.

Evaluation of Multimodal Imaging Biomarkers of Prostate Cancer

Science.gov (United States)

2016-11-01

relationship prostate cancer growth, androgen receptor (AR) levels, hypoxia, and translocator protein (TSPO) levels. As described in the statement of work... bladder uptake) that enable robust detection of small prostate cancers . In contrast, high background and variable uptake of FDHT and FMISO confounded the...Award Number: W81XWH-12-1-0245 TITLE: Evaluation of Multimodal Imaging Biomarkers of Prostate Cancer PRINCIPAL INVESTIGATOR: Christopher Chad

TU-C-12A-02: Development of a Multiparametric Statistical Response Map for Quantitative Imaging

Energy Technology Data Exchange (ETDEWEB)

Bosca, R [The University of Texas Graduate School of Biomedical Sciences, Houston, TX (United States); The University of Texas MD Anderson Cancer Center, Houston, TX (United States); Mahajan, A; Brown, PD; Stafford, RJ [The University of Texas MD Anderson Cancer Center, Houston, TX (United States); Johnson, VE [Texas A' M University, College Station, TX (United States); Dong, L [Scripps Proton Therapy Center, San Diego, CA (United States); Jackson, EF [University of Wisconsin, Madison, WI (United States)

2014-06-15

Purpose: Quantitative imaging biomarkers (QIB) are becoming increasingly utilized in early phase clinical trials as a means of non-invasively assessing treatment response and associated response heterogeneity. The aim of this study was to develop a flexible multiparametric statistical framework to predict voxel-by-voxel response of several potential MRI QIBs. Methods: Patients with histologically proven glioblastomas (n=11) were treated with chemoradiation (with/without bevacizumab) and underwent one baseline and two mid-treatment (3–4wks) MRIs. Dynamic contrast-enhanced (3D FSPGR, 6.3sec/phase, 0.1 mmol/kg Gd-DTPA), dynamic susceptibility contrast (2D GRE-EPI, 1.5sec/phase, 0.2mmol/kg Gd-DTPA), and diffusion tensor (2D DW-EPI, b=0, 1200 s/mm{sup 2}, 27 directions) imaging acquisitions were obtained during each study. Mid-treatment and pre-treatment images were rigidly aligned, and regions of partial response (PR), stable disease (SD), and progressive disease (PD) were contoured in consensus by two experienced radiation oncologists. Voxels in these categories were used to train ordinal (PRimaging biomarkers, as well as treatment type. Leave-one-out cross-validation was performed at the patient level to assess model prediction accuracy. Results: Ordinal regression resulted in model prediction accuracies of 60% (PR), 0% (SD), 81% (PD), and 69% (overall), with coefficients of variation (COV) of 9.4%, 9.6%, and 23.6%, respectively. Logistic regression resulted in accuracies of 82.0% (PR/SD), 46.2% (PD), and 76.2% (overall) with COVs of 22.4%, 45.7%, and 23.8%, respectively. Conclusion: Despite limited patient numbers, this feasibility pilot study demonstrates that ordinal and logistic regression models potentially provide a flexible statistical framework for incorporating longitudinal multiparametric

TU-C-12A-02: Development of a Multiparametric Statistical Response Map for Quantitative Imaging

International Nuclear Information System (INIS)

Bosca, R; Mahajan, A; Brown, PD; Stafford, RJ; Johnson, VE; Dong, L; Jackson, EF

2014-01-01

Purpose: Quantitative imaging biomarkers (QIB) are becoming increasingly utilized in early phase clinical trials as a means of non-invasively assessing treatment response and associated response heterogeneity. The aim of this study was to develop a flexible multiparametric statistical framework to predict voxel-by-voxel response of several potential MRI QIBs. Methods: Patients with histologically proven glioblastomas (n=11) were treated with chemoradiation (with/without bevacizumab) and underwent one baseline and two mid-treatment (3–4wks) MRIs. Dynamic contrast-enhanced (3D FSPGR, 6.3sec/phase, 0.1 mmol/kg Gd-DTPA), dynamic susceptibility contrast (2D GRE-EPI, 1.5sec/phase, 0.2mmol/kg Gd-DTPA), and diffusion tensor (2D DW-EPI, b=0, 1200 s/mm 2 , 27 directions) imaging acquisitions were obtained during each study. Mid-treatment and pre-treatment images were rigidly aligned, and regions of partial response (PR), stable disease (SD), and progressive disease (PD) were contoured in consensus by two experienced radiation oncologists. Voxels in these categories were used to train ordinal (PRimaging biomarkers, as well as treatment type. Leave-one-out cross-validation was performed at the patient level to assess model prediction accuracy. Results: Ordinal regression resulted in model prediction accuracies of 60% (PR), 0% (SD), 81% (PD), and 69% (overall), with coefficients of variation (COV) of 9.4%, 9.6%, and 23.6%, respectively. Logistic regression resulted in accuracies of 82.0% (PR/SD), 46.2% (PD), and 76.2% (overall) with COVs of 22.4%, 45.7%, and 23.8%, respectively. Conclusion: Despite limited patient numbers, this feasibility pilot study demonstrates that ordinal and logistic regression models potentially provide a flexible statistical framework for incorporating longitudinal multiparametric

Quantitative Phase Imaging Using Hard X Rays

International Nuclear Information System (INIS)

Nugent, K.A.; Gureyev, T.E.; Cookson, D.J.; Paganin, D.; Barnea, Z.

1996-01-01

The quantitative imaging of a phase object using 16keV xrays is reported. The theoretical basis of the techniques is presented along with its implementation using a synchrotron x-ray source. We find that our phase image is in quantitative agreement with independent measurements of the object. copyright 1996 The American Physical Society

Imaging biomarkers in Parkinson's disease and Parkinsonian syndromes: current and emerging concepts.

Science.gov (United States)

Saeed, Usman; Compagnone, Jordana; Aviv, Richard I; Strafella, Antonio P; Black, Sandra E; Lang, Anthony E; Masellis, Mario

2017-01-01

Two centuries ago in 1817, James Parkinson provided the first medical description of Parkinson's disease, later refined by Jean-Martin Charcot in the mid-to-late 19th century to include the atypical parkinsonian variants (also termed, Parkinson-plus syndromes). Today, Parkinson's disease represents the second most common neurodegenerative disorder with an estimated global prevalence of over 10 million. Conversely, atypical parkinsonian syndromes encompass a group of relatively heterogeneous disorders that may share some clinical features with Parkinson's disease, but are uncommon distinct clinicopathological diseases. Decades of scientific advancements have vastly improved our understanding of these disorders, including improvements in in vivo imaging for biomarker identification. Multimodal imaging for the visualization of structural and functional brain changes is especially important, as it allows a 'window' into the underlying pathophysiological abnormalities. In this article, we first present an overview of the cardinal clinical and neuropathological features of, 1) synucleinopathies: Parkinson's disease and other Lewy body spectrum disorders, as well as multiple system atrophy, and 2) tauopathies: progressive supranuclear palsy, and corticobasal degeneration. A comprehensive presentation of well-established and emerging imaging biomarkers for each disorder are then discussed. Biomarkers for the following imaging modalities are reviewed: 1) structural magnetic resonance imaging (MRI) using T1, T2, and susceptibility-weighted sequences for volumetric and voxel-based morphometric analyses, as well as MRI derived visual signatures, 2) diffusion tensor MRI for the assessment of white matter tract injury and microstructural integrity, 3) proton magnetic resonance spectroscopy for quantifying proton-containing brain metabolites, 4) single photon emission computed tomography for the evaluation of nigrostriatal integrity (as assessed by presynaptic dopamine

Machine Learning for Quantification of Small Vessel Disease Imaging Biomarkers

NARCIS (Netherlands)

Ghafoorian, M.

2018-01-01

This thesis is devoted to developing fully automated methods for quantification of small vessel disease imaging bio-markers, namely WMHs and lacunes, using vari- ous machine learning/deep learning and computer vision techniques. The rest of the thesis is organized as follows: Chapter 2 describes

Molecular Imaging Biomarkers of Resistance to Radiation Therapy for Spontaneous Nasal Tumors in Canines

International Nuclear Information System (INIS)

Bradshaw, Tyler J.; Bowen, Stephen R.; Deveau, Michael A.; Kubicek, Lyndsay; White, Pamela; Bentzen, Søren M.; Chappell, Richard J.; Forrest, Lisa J.; Jeraj, Robert

2015-01-01

Purpose: Imaging biomarkers of resistance to radiation therapy can inform and guide treatment management. Most studies have so far focused on assessing a single imaging biomarker. The goal of this study was to explore a number of different molecular imaging biomarkers as surrogates of resistance to radiation therapy. Methods and Materials: Twenty-two canine patients with spontaneous sinonasal tumors were treated with accelerated hypofractionated radiation therapy, receiving either 10 fractions of 4.2 Gy each or 10 fractions of 5.0 Gy each to the gross tumor volume. Patients underwent fluorodeoxyglucose (FDG)-, fluorothymidine (FLT)-, and Cu(II)-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM)-labeled positron emission tomography/computed tomography (PET/CT) imaging before therapy and FLT and Cu-ATSM PET/CT imaging during therapy. In addition to conventional maximum and mean standardized uptake values (SUV max ; SUV mean ) measurements, imaging metrics providing response and spatiotemporal information were extracted for each patient. Progression-free survival was assessed according to response evaluation criteria in solid tumor. The prognostic value of each imaging biomarker was evaluated using univariable Cox proportional hazards regression. Multivariable analysis was also performed but was restricted to 2 predictor variables due to the limited number of patients. The best bivariable model was selected according to pseudo-R 2 . Results: The following variables were significantly associated with poor clinical outcome following radiation therapy according to univariable analysis: tumor volume (P=.011), midtreatment FLT SUV mean (P=.018), and midtreatment FLT SUV max (P=.006). Large decreases in FLT SUV mean from pretreatment to midtreatment were associated with worse clinical outcome (P=.013). In the bivariable model, the best 2-variable combination for predicting poor outcome was high midtreatment FLT SUV max (P=.022) in combination with large FLT response from

Molecular Imaging Biomarkers of Resistance to Radiation Therapy for Spontaneous Nasal Tumors in Canines

Energy Technology Data Exchange (ETDEWEB)

Bradshaw, Tyler J. [Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin (United States); Bowen, Stephen R. [Departments of Radiation Oncology and Radiology, University of Washington, Seattle, Washington (United States); Deveau, Michael A. [Department of Small Animal Clinical Sciences, Texas A& M University, College Station, Texas (United States); Kubicek, Lyndsay [Angell Animal Medical Center, Boston, Massachusetts (United States); White, Pamela [Department of Surgical Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin (United States); Bentzen, Søren M. [Division of Biostatistics and Bioinformatics, University of Maryland Greenebaum Cancer Center, and Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland (United States); Chappell, Richard J. [Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin (United States); Forrest, Lisa J. [Department of Surgical Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin (United States); Jeraj, Robert, E-mail: rjeraj@wisc.edu [Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin (United States); Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin (United States)

2015-03-15

Purpose: Imaging biomarkers of resistance to radiation therapy can inform and guide treatment management. Most studies have so far focused on assessing a single imaging biomarker. The goal of this study was to explore a number of different molecular imaging biomarkers as surrogates of resistance to radiation therapy. Methods and Materials: Twenty-two canine patients with spontaneous sinonasal tumors were treated with accelerated hypofractionated radiation therapy, receiving either 10 fractions of 4.2 Gy each or 10 fractions of 5.0 Gy each to the gross tumor volume. Patients underwent fluorodeoxyglucose (FDG)-, fluorothymidine (FLT)-, and Cu(II)-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM)-labeled positron emission tomography/computed tomography (PET/CT) imaging before therapy and FLT and Cu-ATSM PET/CT imaging during therapy. In addition to conventional maximum and mean standardized uptake values (SUV{sub max}; SUV{sub mean}) measurements, imaging metrics providing response and spatiotemporal information were extracted for each patient. Progression-free survival was assessed according to response evaluation criteria in solid tumor. The prognostic value of each imaging biomarker was evaluated using univariable Cox proportional hazards regression. Multivariable analysis was also performed but was restricted to 2 predictor variables due to the limited number of patients. The best bivariable model was selected according to pseudo-R{sup 2}. Results: The following variables were significantly associated with poor clinical outcome following radiation therapy according to univariable analysis: tumor volume (P=.011), midtreatment FLT SUV{sub mean} (P=.018), and midtreatment FLT SUV{sub max} (P=.006). Large decreases in FLT SUV{sub mean} from pretreatment to midtreatment were associated with worse clinical outcome (P=.013). In the bivariable model, the best 2-variable combination for predicting poor outcome was high midtreatment FLT SUV{sub max} (P=.022) in

New prognostic factor telomerase reverse transcriptase promotor mutation presents without MR imaging biomarkers in primary glioblastoma

Energy Technology Data Exchange (ETDEWEB)

Ersoy, Tunc F.; Simon, Matthias [University Hospital Bonn, Department of Neurosurgery and Stereotaxy, Bonn (Germany); Ev. Krankenhaus Bielefeld, Department of Neurosurgery, Bielefeld (Germany); Keil, Vera C.; Hadizadeh, Dariusch R.; Schild, Hans H. [University Hospital Bonn, Department of Radiology, Bonn (Germany); Gielen, Gerrit H.; Waha, Andreas [University Hospital Bonn, Institute of Neuropathology, Bonn (Germany); Fimmers, Rolf [IMBIE, University Hospital Bonn, Bonn (Germany); Heidenreich, Barbara; Kumar, Rajiv [DFKZ, Department of Molecular Genetic Epidemiology, Heidelberg (Germany)

2017-12-15

Magnetic resonance (MR) imaging biomarkers can assist in the non-invasive assessment of the genetic status in glioblastomas (GBMs). Telomerase reverse transcriptase (TERT) promoter mutations are associated with a negative prognosis. This study was performed to identify MR imaging biomarkers to forecast the TERT mutation status. Pre-operative MRIs of 64/67 genetically confirmed primary GBM patients (51/67 TERT-mutated with rs2853669 polymorphism) were analyzed according to Visually AcceSAble Rembrandt Images (VASARI) (https: //wiki.cancerimagingarchive.net/display/Public/VASARI+Research+Project) imaging criteria by three radiological raters. TERT mutation and O{sup 6}-methylguanine-DNA methyltransferase (MGMT) hypermethylation data were obtained through direct and pyrosequencing as described in a previous study. Clinical data were derived from a prospectively maintained electronic database. Associations of potential imaging biomarkers and genetic status were assessed by Fisher and Mann-Whitney U tests and stepwise linear regression. No imaging biomarkers could be identified to predict TERT mutational status (alone or in conjunction with TERT promoter polymorphism rs2853669 AA-allele). TERT promoter mutations were more common in patients with tumor-associated seizures as first symptom (26/30 vs. 25/37, p = 0.07); these showed significantly smaller tumors [13.1 (9.0-19.0) vs. 24.0 (16.6-37.5) all cm{sup 3}; p = 0.007] and prolonged median overall survival [17.0 (11.5-28.0) vs. 9.0 (4.0-12.0) all months; p = 0.02]. TERT-mutated GBMs were underrepresented in the extended angularis region (p = 0.03), whereas MGMT-methylated GBMs were overrepresented in the corpus callosum (p = 0.03) and underrepresented temporomesially (p = 0.01). Imaging biomarkers for prediction of TERT mutation status remain weak and cannot be derived from the VASARI protocol. Tumor-associated seizures are less common in TERT mutated glioblastomas. (orig.)

Multimodal quantitative phase and fluorescence imaging of cell apoptosis

Science.gov (United States)

Fu, Xinye; Zuo, Chao; Yan, Hao

2017-06-01

Fluorescence microscopy, utilizing fluorescence labeling, has the capability to observe intercellular changes which transmitted and reflected light microscopy techniques cannot resolve. However, the parts without fluorescence labeling are not imaged. Hence, the processes simultaneously happen in these parts cannot be revealed. Meanwhile, fluorescence imaging is 2D imaging where information in the depth is missing. Therefore the information in labeling parts is also not complete. On the other hand, quantitative phase imaging is capable to image cells in 3D in real time through phase calculation. However, its resolution is limited by the optical diffraction and cannot observe intercellular changes below 200 nanometers. In this work, fluorescence imaging and quantitative phase imaging are combined to build a multimodal imaging system. Such system has the capability to simultaneously observe the detailed intercellular phenomenon and 3D cell morphology. In this study the proposed multimodal imaging system is used to observe the cell behavior in the cell apoptosis. The aim is to highlight the limitations of fluorescence microscopy and to point out the advantages of multimodal quantitative phase and fluorescence imaging. The proposed multimodal quantitative phase imaging could be further applied in cell related biomedical research, such as tumor.

Quantitative SIMS Imaging of Agar-Based Microbial Communities.

Science.gov (United States)

Dunham, Sage J B; Ellis, Joseph F; Baig, Nameera F; Morales-Soto, Nydia; Cao, Tianyuan; Shrout, Joshua D; Bohn, Paul W; Sweedler, Jonathan V

2018-05-01

After several decades of widespread use for mapping elemental ions and small molecular fragments in surface science, secondary ion mass spectrometry (SIMS) has emerged as a powerful analytical tool for molecular imaging in biology. Biomolecular SIMS imaging has primarily been used as a qualitative technique; although the distribution of a single analyte can be accurately determined, it is difficult to map the absolute quantity of a compound or even to compare the relative abundance of one molecular species to that of another. We describe a method for quantitative SIMS imaging of small molecules in agar-based microbial communities. The microbes are cultivated on a thin film of agar, dried under nitrogen, and imaged directly with SIMS. By use of optical microscopy, we show that the area of the agar is reduced by 26 ± 2% (standard deviation) during dehydration, but the overall biofilm morphology and analyte distribution are largely retained. We detail a quantitative imaging methodology, in which the ion intensity of each analyte is (1) normalized to an external quadratic regression curve, (2) corrected for isomeric interference, and (3) filtered for sample-specific noise and lower and upper limits of quantitation. The end result is a two-dimensional surface density image for each analyte. The sample preparation and quantitation methods are validated by quantitatively imaging four alkyl-quinolone and alkyl-quinoline N-oxide signaling molecules (including Pseudomonas quinolone signal) in Pseudomonas aeruginosa colony biofilms. We show that the relative surface densities of the target biomolecules are substantially different from values inferred through direct intensity comparison and that the developed methodologies can be used to quantitatively compare as many ions as there are available standards.

PCA-based groupwise image registration for quantitative MRI

NARCIS (Netherlands)

Huizinga, W.; Poot, D. H. J.; Guyader, J.-M.; Klaassen, R.; Coolen, B. F.; van Kranenburg, M.; van Geuns, R. J. M.; Uitterdijk, A.; Polfliet, M.; Vandemeulebroucke, J.; Leemans, A.; Niessen, W. J.; Klein, S.

2016-01-01

Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T5 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different

TU-G-303-01: Radiomics: Quantitative Imaging in the Service of Improved Treatment Decision Making

International Nuclear Information System (INIS)

Deasy, J.

2015-01-01

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

TU-G-303-01: Radiomics: Quantitative Imaging in the Service of Improved Treatment Decision Making

Energy Technology Data Exchange (ETDEWEB)

Deasy, J. [Memorial Sloan Kettering Cancer Center, New York, NY (United States)

2015-06-15

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

Mass spectrometry imaging of biomarker lipids for phagocytosis and signalling during focal cerebral ischaemia

DEFF Research Database (Denmark)

Nielsen, Mette M B; Lambertsen, Kate L; Clausen, Bettina H

2016-01-01

biomarker CD11b, and probably with cholesteryl ester. Mass spectrometry imaging can visualize spatiotemporal changes in the lipidome during the progression and resolution of focal cerebral inflammation and suggests that BMP(22:6/22:6) and N-acyl-phosphatidylethanolamines can be used as biomarkers......Focal cerebral ischaemia has an initial phase of inflammation and tissue injury followed by a later phase of resolution and repair. Mass spectrometry imaging (desorption electrospray ionization and matrix assisted laser desorption ionization) was applied on brain sections from mice 2 h, 24 h, 5d, 7...

In Vivo Imaging Biomarkers in Mouse Models of Alzheimer's Disease: Are We Lost in Translation or Breaking Through?

Directory of Open Access Journals (Sweden)

Benoît Delatour

2010-01-01

Full Text Available Identification of biomarkers of Alzheimer's Disease (AD is a critical priority to efficiently diagnose the patients, to stage the progression of neurodegeneration in living subjects, and to assess the effects of disease-modifier treatments. This paper addresses the development and usefulness of preclinical neuroimaging biomarkers of AD. It is today possible to image in vivo the brain of small rodents at high resolution and to detect the occurrence of macroscopic/microscopic lesions in these species, as well as of functional alterations reminiscent of AD pathology. We will outline three different types of imaging biomarkers that can be used in AD mouse models: biomarkers with clear translational potential, biomarkers that can serve as in vivo readouts (in particular in the context of drug discovery exclusively for preclinical research, and finally biomarkers that constitute new tools for fundamental research on AD physiopathogeny.

[Quantitative data analysis for live imaging of bone.

Science.gov (United States)

Seno, Shigeto

Bone tissue is a hard tissue, it was difficult to observe the interior of the bone tissue alive. With the progress of microscopic technology and fluorescent probe technology in recent years, it becomes possible to observe various activities of various cells forming bone society. On the other hand, the quantitative increase in data and the diversification and complexity of the images makes it difficult to perform quantitative analysis by visual inspection. It has been expected to develop a methodology for processing microscopic images and data analysis. In this article, we introduce the research field of bioimage informatics which is the boundary area of biology and information science, and then outline the basic image processing technology for quantitative analysis of live imaging data of bone.

Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods

Directory of Open Access Journals (Sweden)

Ahmed R

2014-03-01

Full Text Available Rafay Ahmed,1 Matthew J Oborski,2 Misun Hwang,1 Frank S Lieberman,3 James M Mountz11Department of Radiology, 2Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; 3Department of Neurology and Department of Medicine, Division of Hematology/Oncology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USAAbstract: Malignant gliomas consist of glioblastomas, anaplastic astrocytomas, anaplastic oligodendrogliomas and anaplastic oligoastrocytomas, and some less common tumors such as anaplastic ependymomas and anaplastic gangliogliomas. Malignant gliomas have high morbidity and mortality. Even with optimal treatment, median survival is only 12–15 months for glioblastomas and 2–5 years for anaplastic gliomas. However, recent advances in imaging and quantitative analysis of image data have led to earlier diagnosis of tumors and tumor response to therapy, providing oncologists with a greater time window for therapy management. In addition, improved understanding of tumor biology, genetics, and resistance mechanisms has enhanced surgical techniques, chemotherapy methods, and radiotherapy administration. After proper diagnosis and institution of appropriate therapy, there is now a vital need for quantitative methods that can sensitively detect malignant glioma response to therapy at early follow-up times, when changes in management of nonresponders can have its greatest effect. Currently, response is largely evaluated by measuring magnetic resonance contrast and size change, but this approach does not take into account the key biologic steps that precede tumor size reduction. Molecular imaging is ideally suited to measuring early response by quantifying cellular metabolism, proliferation, and apoptosis, activities altered early in treatment. We expect that successful integration of quantitative imaging biomarker assessment into the early phase of clinical trials could provide a novel approach for testing new therapies

Systemic, local and imaging biomarkers of brain injury: more needed, and better use of those already established?

Directory of Open Access Journals (Sweden)

Keri Linda Carpenter

2015-02-01

Full Text Available Much progress has been made over the past two decades in the treatment of severe acute brain injury, including traumatic brain injury and subarachnoid haemorrhage, resulting in a higher proportion of patients surviving with better outcomes. This has arisen from a combination of factors. These include improvements in procedures at the scene (pre-hospital and in the hospital emergency department, advances in neuromonitoring in the intensive care unit, both continuously at the bedside and intermittently in scans, evolution and refinement of protocol-driven therapy for better management of patients, and advances in surgical procedures and rehabilitation. Nevertheless, many patients still experience varying degrees of long-term disabilities post-injury with consequent demands on carers and resources, and there is room for improvement. Biomarkers are a key aspect of neuromonitoring. A broad definition of a biomarker is any observable feature that can be used to inform on the state of the patient, e.g. a molecular species, a feature on a scan, or a monitoring characteristic e.g. cerebrovascular pressure reactivity index. Biomarkers are usually quantitative measures, which can be utilised in diagnosis and monitoring of response to treatment. They are thus crucial to the development of therapies and may be utilised as surrogate endpoints in Phase II clinical trials. To date, there is no specific drug treatment for acute brain injury, and many seemingly promising agents emerging from pre-clinical animal models have failed in clinical trials. Large Phase III studies of clinical outcomes are costly, consuming time and resources. It is therefore important that adequate Phase II clinical studies with informative surrogate endpoints are performed employing appropriate biomarkers. In this article we review some of the available systemic, local and imaging biomarkers and technologies relevant in acute brain injury patients, and highlight gaps in the current

Quantitative proteomic analysis for novel biomarkers of buccal squamous cell carcinoma arising in background of oral submucous fibrosis

International Nuclear Information System (INIS)

Liu, Wen; Zeng, Lijuan; Li, Ning; Wang, Fei; Jiang, Canhua; Guo, Feng; Chen, Xinqun; Su, Tong; Xu, Chunjiao; Zhang, Shanshan; Fang, Changyun

2016-01-01

In South and Southeast Asian, the majority of buccal squamous cell carcinoma (BSCC) can arise from oral submucous fibrosis (OSF). BSCCs develop in OSF that are often not completely resected, causing local relapse. The aim of our study was to find candidate protein biomarkers to detect OSF and predict prognosis in BSCCs by quantitative proteomics approaches. We compared normal oral mucosa (NBM) and paired biopsies of BSCC and OSF by quantitative proteomics using isobaric tags for relative and absolute quantification (iTRAQ) to discover proteins with differential expression. Gene Ontology and KEGG networks were analyzed. The prognostic value of biomarkers was evaluated in 94 BSCCs accompanied with OSF. Significant associations were assessed by Kaplan-Meier survival and Cox-proportional hazards analysis. In total 30 proteins were identified with significantly different expression (false discovery rate < 0.05) among three tissues. Two consistently upregulated proteins, ANXA4 and FLNA, were validated. The disease-free survival was negatively associated with the expression of ANXA4 (hazard ratio, 3.4; P = 0.000), FLNA (hazard ratio, 2.1; P = 0.000) and their combination (hazard ratio, 8.8; P = 0.002) in BSCCs. The present study indicates that iTRAQ quantitative proteomics analysis for tissues of BSCC and OSF is a reliable strategy. A significantly up-regulated ANXA4 and FLNA could be not only candidate biomarkers for BSCC prognosis but also potential targets for its therapy. The online version of this article (doi:10.1186/s12885-016-2650-1) contains supplementary material, which is available to authorized users

Quantitative image fusion in infrared radiometry

Science.gov (United States)

Romm, Iliya; Cukurel, Beni

2018-05-01

Towards high-accuracy infrared radiance estimates, measurement practices and processing techniques aimed to achieve quantitative image fusion using a set of multi-exposure images of a static scene are reviewed. The conventional non-uniformity correction technique is extended, as the original is incompatible with quantitative fusion. Recognizing the inherent limitations of even the extended non-uniformity correction, an alternative measurement methodology, which relies on estimates of the detector bias using self-calibration, is developed. Combining data from multi-exposure images, two novel image fusion techniques that ultimately provide high tonal fidelity of a photoquantity are considered: ‘subtract-then-fuse’, which conducts image subtraction in the camera output domain and partially negates the bias frame contribution common to both the dark and scene frames; and ‘fuse-then-subtract’, which reconstructs the bias frame explicitly and conducts image fusion independently for the dark and the scene frames, followed by subtraction in the photoquantity domain. The performances of the different techniques are evaluated for various synthetic and experimental data, identifying the factors contributing to potential degradation of the image quality. The findings reflect the superiority of the ‘fuse-then-subtract’ approach, conducting image fusion via per-pixel nonlinear weighted least squares optimization.

Quantitative ultrasound and photoacoustic imaging for the assessment of vascular parameters

CERN Document Server

Meiburger, Kristen M

2017-01-01

This book describes the development of quantitative techniques for ultrasound and photoacoustic imaging in the assessment of architectural and vascular parameters. It presents morphological vascular research based on the development of quantitative imaging techniques for the use of clinical B-mode ultrasound images, and preclinical architectural vascular investigations on quantitative imaging techniques for ultrasounds and photoacoustics. The book is divided into two main parts, the first of which focuses on the development and validation of quantitative techniques for the assessment of vascular morphological parameters that can be extracted from B-mode ultrasound longitudinal images of the common carotid artery. In turn, the second part highlights quantitative imaging techniques for assessing the architectural parameters of vasculature that can be extracted from 3D volumes, using both contrast-enhanced ultrasound (CEUS) imaging and photoacoustic imaging without the addition of any contrast agent. Sharing and...

Quantitative imaging of turbulent and reacting flows

Energy Technology Data Exchange (ETDEWEB)

Paul, P.H. [Sandia National Laboratories, Livermore, CA (United States)

1993-12-01

Quantitative digital imaging, using planar laser light scattering techniques is being developed for the analysis of turbulent and reacting flows. Quantitative image data, implying both a direct relation to flowfield variables as well as sufficient signal and spatial dynamic range, can be readily processed to yield two-dimensional distributions of flowfield scalars and in turn two-dimensional images of gradients and turbulence scales. Much of the development of imaging techniques to date has concentrated on understanding the requisite molecular spectroscopy and collision dynamics to be able to determine how flowfield variable information is encoded into the measured signal. From this standpoint the image is seen as a collection of single point measurements. The present effort aims at realizing necessary improvements in signal and spatial dynamic range, signal-to-noise ratio and spatial resolution in the imaging system as well as developing excitation/detection strategies which provide for a quantitative measure of particular flowfield scalars. The standard camera used for the study is an intensified CCD array operated in a conventional video format. The design of the system was based on detailed modeling of signal and image transfer properties of fast UV imaging lenses, image intensifiers and CCD detector arrays. While this system is suitable for direct scalar imaging, derived quantities (e.g. temperature or velocity images) require an exceptionally wide dynamic range imaging detector. To apply these diagnostics to reacting flows also requires a very fast shuttered camera. The authors have developed and successfully tested a new type of gated low-light level detector. This system relies on fast switching of proximity focused image-diode which is direct fiber-optic coupled to a cooled CCD array. Tests on this new detector show significant improvements in detection limit, dynamic range and spatial resolution as compared to microchannel plate intensified arrays.

TU-G-303-00: Radiomics: Advances in the Use of Quantitative Imaging Used for Predictive Modeling

International Nuclear Information System (INIS)

2015-01-01

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

TU-G-303-00: Radiomics: Advances in the Use of Quantitative Imaging Used for Predictive Modeling

Energy Technology Data Exchange (ETDEWEB)

NONE

2015-06-15

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

The Biomarker-Surrogacy Evaluation Schema: a review of the biomarker-surrogate literature and a proposal for a criterion-based, quantitative, multidimensional hierarchical levels of evidence schema for evaluating the status of biomarkers as surrogate endpoints.

Science.gov (United States)

Lassere, Marissa N

2008-06-01

There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Section 2 is a systematic, historical review of the biomarker-surrogate endpoint literature with special reference to the nomenclature, the systems of classification and statistical methods developed for their evaluation. In Section 3 an explicit, criterion-based, quantitative, multidimensional hierarchical levels of evidence schema - Biomarker-Surrogacy Evaluation Schema - is proposed to evaluate and co-ordinate the multiple dimensions (biological, epidemiological, statistical, clinical trial and risk-benefit evidence) of the biomarker clinical endpoint relationships. The schema systematically evaluates and ranks the surrogacy status of biomarkers and surrogate endpoints using defined levels of evidence. The schema incorporates the three independent domains: Study Design, Target Outcome and Statistical Evaluation. Each domain has items ranked from zero to five. An additional category called Penalties incorporates additional considerations of biological plausibility, risk-benefit and generalizability. The total score (0-15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. The term ;surrogate' is restricted to markers attaining Levels 1 or 2 only. Surrogacy status of markers can then be directly compared within and across different areas of medicine to guide individual, trial-based or drug-development decisions. This schema would facilitate communication between clinical, researcher, regulatory, industry and consumer participants necessary for evaluation of the biomarker-surrogate-clinical endpoint relationship in their different settings.

FLIM-FRET image analysis of tryptophan in prostate cancer cells

Science.gov (United States)

Periasamy, Ammasi; Alam, Shagufta R.; Svindrych, Zdenek; Wallrabe, Horst

2017-07-01

A region of interest (ROI) based quantitative FLIM-FRET image analysis is developed to quantitate the autofluorescence signals of the essential amino acid tryptophan as a biomarker to investigate the metabolism in prostate cancer cells.

Quantitative image cytometry measurements of lipids, DNA, CD45 and cytokeratin for circulating tumor cell identification in a model system

Science.gov (United States)

Futia, Gregory L.; Qamar, Lubna; Behbakht, Kian; Gibson, Emily A.

2016-04-01

Circulating tumor cell (CTC) identification has applications in both early detection and monitoring of solid cancers. The rarity of CTCs, expected at ~1-50 CTCs per million nucleated blood cells (WBCs), requires identifying methods based on biomarkers with high sensitivity and specificity for accurate identification. Discovery of biomarkers with ever higher sensitivity and specificity to CTCs is always desirable to potentially find more CTCs in cancer patients thus increasing their clinical utility. Here, we investigate quantitative image cytometry measurements of lipids with the biomarker panel of DNA, Cytokeratin (CK), and CD45 commonly used to identify CTCs. We engineered a device for labeling suspended cell samples with fluorescent antibodies and dyes. We used it to prepare samples for 4 channel confocal laser scanning microscopy. The total data acquired at high resolution from one sample is ~ 1.3 GB. We developed software to perform the automated segmentation of these images into regions of interest (ROIs) containing individual cells. We quantified image features of total signal, spatial second moment, spatial frequency second moment, and their product for each ROI. We performed measurements on pure WBCs, cancer cell line MCF7 and mixed samples. Multivariable regressions and feature selection were used to determine combination features that are more sensitive and specific than any individual feature separately. We also demonstrate that computation of spatial characteristics provides higher sensitivity and specificity than intensity alone. Statistical models allowed quantification of the required sensitivity and specificity for detecting small levels of CTCs in a human blood sample.

Progress towards in vitro quantitative imaging of human femur using compound quantitative ultrasonic tomography

International Nuclear Information System (INIS)

Lasaygues, Philippe; Ouedraogo, Edgard; Lefebvre, Jean-Pierre; Gindre, Marcel; Talmant, Marilyne; Laugier, Pascal

2005-01-01

The objective of this study is to make cross-sectional ultrasonic quantitative tomography of the diaphysis of long bones. Ultrasonic propagation in bones is affected by the severe mismatch between the acoustic properties of this biological solid and those of the surrounding soft medium, namely, the soft tissues in vivo or water in vitro. Bone imaging is then a nonlinear inverse-scattering problem. In this paper, we showed that in vitro quantitative images of sound velocities in a human femur cross section could be reconstructed by combining ultrasonic reflection tomography (URT), which provides images of the macroscopic structure of the bone, and ultrasonic transmission tomography (UTT), which provides quantitative images of the sound velocity. For the shape, we developed an image-processing tool to extract the external and internal boundaries and cortical thickness measurements. For velocity mapping, we used a wavelet analysis tool adapted to ultrasound, which allowed us to detect precisely the time of flight from the transmitted signals. A brief review of the ultrasonic tomography that we developed using correction algorithms of the wavepaths and compensation procedures are presented. Also shown are the first results of our analyses on models and specimens of long bone using our new iterative quantitative protocol

Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema

DEFF Research Database (Denmark)

Lassere, Marissa N; Johnson, Kent R; Boers, Maarten

2007-01-01

endpoints, and leading indicators, a quantitative surrogate validation schema was developed and subsequently evaluated at a stakeholder workshop. RESULTS: The search identified several classification schema and definitions. Components of these were incorporated into a new quantitative surrogate validation...... of the National Institutes of Health definitions of biomarker, surrogate endpoint, and clinical endpoint was useful. CONCLUSION: Further development and application of this schema provides incentives and guidance for effective biomarker and surrogate endpoint research, and more efficient drug discovery...... are then applied if there is serious counterevidence. A total score (0 to 15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. It was proposed that the term "surrogate" be restricted to markers attaining Levels 1 or 2 only. Most stakeholders agreed that this operationalization...

Elastography as a hybrid imaging technique : coupling with photoacoustics and quantitative imaging

International Nuclear Information System (INIS)

Widlak, T.G.

2015-01-01

While classical imaging methods, such as ultrasound, computed tomography or magnetic resonance imaging, are well-known and mathematically understood, a host of physiological parameters relevant for diagnostic purposes cannot be obtained by them. This gap is recently being closed by the introduction of hybrid, or coupled-physics imaging methods. They connect more then one physical modality, and aim to provide quantitative information on optical, electrical or mechanical parameters with high resolution. Central to this thesis is the mechanical contrast of elastic tissue, especially Young’s modulus or the shear modulus. Different methods of qualitative elastography provide interior information of the mechanical displacement field. From this interior data the nonlinear inverse problem of quantitative elastography aims to reconstruct the shear modulus. In this thesis, the elastography problem is seen from a hybrid imaging perspective; methods from coupled-physics inspired literature and regularization theory have been employed to recover displacement and shear modulus information. The overdetermined systems approach by G. Bal is applied to the quantitative problem, and ellipticity criteria are deduced, for one and several measurements, as well as injectivity results. Together with the geometric theory of G. Chavent, the results are used for analyzing convergence of Tikhonov regularization. Also, a convergence analysis for the Levenberg Marquardt method is provided. As a second mainstream project in this thesis, elastography imaging is developed for extracting displacements from photoacoustic images. A novel method is provided for texturizing the images, and the optical flow problem for motion estimation is shown to be regularized with this texture generation. The results are tested in cooperation with the Medical University Vienna, and the methods for quantitative determination of the shear modulus evaluated in first experiments. In summary, the overdetermined systems

Quantitative imaging with a mobile phone microscope.

Directory of Open Access Journals (Sweden)

Arunan Skandarajah

Full Text Available Use of optical imaging for medical and scientific applications requires accurate quantification of features such as object size, color, and brightness. High pixel density cameras available on modern mobile phones have made photography simple and convenient for consumer applications; however, the camera hardware and software that enables this simplicity can present a barrier to accurate quantification of image data. This issue is exacerbated by automated settings, proprietary image processing algorithms, rapid phone evolution, and the diversity of manufacturers. If mobile phone cameras are to live up to their potential to increase access to healthcare in low-resource settings, limitations of mobile phone-based imaging must be fully understood and addressed with procedures that minimize their effects on image quantification. Here we focus on microscopic optical imaging using a custom mobile phone microscope that is compatible with phones from multiple manufacturers. We demonstrate that quantitative microscopy with micron-scale spatial resolution can be carried out with multiple phones and that image linearity, distortion, and color can be corrected as needed. Using all versions of the iPhone and a selection of Android phones released between 2007 and 2012, we show that phones with greater than 5 MP are capable of nearly diffraction-limited resolution over a broad range of magnifications, including those relevant for single cell imaging. We find that automatic focus, exposure, and color gain standard on mobile phones can degrade image resolution and reduce accuracy of color capture if uncorrected, and we devise procedures to avoid these barriers to quantitative imaging. By accommodating the differences between mobile phone cameras and the scientific cameras, mobile phone microscopes can be reliably used to increase access to quantitative imaging for a variety of medical and scientific applications.

Quantitative Imaging with a Mobile Phone Microscope

Science.gov (United States)

Skandarajah, Arunan; Reber, Clay D.; Switz, Neil A.; Fletcher, Daniel A.

2014-01-01

Use of optical imaging for medical and scientific applications requires accurate quantification of features such as object size, color, and brightness. High pixel density cameras available on modern mobile phones have made photography simple and convenient for consumer applications; however, the camera hardware and software that enables this simplicity can present a barrier to accurate quantification of image data. This issue is exacerbated by automated settings, proprietary image processing algorithms, rapid phone evolution, and the diversity of manufacturers. If mobile phone cameras are to live up to their potential to increase access to healthcare in low-resource settings, limitations of mobile phone–based imaging must be fully understood and addressed with procedures that minimize their effects on image quantification. Here we focus on microscopic optical imaging using a custom mobile phone microscope that is compatible with phones from multiple manufacturers. We demonstrate that quantitative microscopy with micron-scale spatial resolution can be carried out with multiple phones and that image linearity, distortion, and color can be corrected as needed. Using all versions of the iPhone and a selection of Android phones released between 2007 and 2012, we show that phones with greater than 5 MP are capable of nearly diffraction-limited resolution over a broad range of magnifications, including those relevant for single cell imaging. We find that automatic focus, exposure, and color gain standard on mobile phones can degrade image resolution and reduce accuracy of color capture if uncorrected, and we devise procedures to avoid these barriers to quantitative imaging. By accommodating the differences between mobile phone cameras and the scientific cameras, mobile phone microscopes can be reliably used to increase access to quantitative imaging for a variety of medical and scientific applications. PMID:24824072

Enrichment of MCI and early Alzheimer's disease treatment trials using neurochemical and imaging candidate biomarkers.

LENUS (Irish Health Repository)

Hampel, H

2012-02-01

In the earliest clinical stages of Alzheimer\\'s Disease (AD), when symptoms are mild, clinical diagnosis will still be difficult. AD related molecular mechanisms precede symptoms. Biological markers can serve as early diagnostic indicators, as markers of preclinical pathological change, e.g. underlying mechanisms of action (MoA). Hypothesis based candidates are derived from structural and functional neuroimaging as well as from cerebrospinal fluid (CSF) and plasma. Unbiased exploratory approaches e.g. proteome analysis or rater independent fully automated imaging post-processing methods yield novel candidates. Recent progress in the validation of core feasible imaging and neurochemical biomarkers for functions such as early detection, classification, progression and prediction of AD is summarized. Single core feasible biomarkers can already be used to enrich populations at risk for AD and may be further enhanced using distinct combinations. Some biomarkers are currently in the process of implementation as primary or secondary outcome variables into regulatory guideline documents, e.g. regarding phase II in drug development programs as outcome measures in proof of concept or dose finding studies. There are specific biomarkers available depending on the hypothesized mechanism of action of a medicinal product, e.g. impact on the amyloidogenic cascade or on tauhyperphosphorylation. Ongoing large-scale international controlled multi-center trials will provide further validation of selected core feasible imaging and CSF biomarker candidates as outcome measures in early AD for use in phase III clinical efficacy trials. There is a need of rigorous co-development of biological trait- and statemarker candidates facilitated through planned synergistic collaboration between academic, industrial and regulatory partners.

Technological challenges in Magnetic Resonance Imaging: enhancing sensitivity, moving to quantitative imaging and searching for disease biomarkers

Science.gov (United States)

Retico, A.

2018-02-01

Diagnostic imaging based on the Nuclear Magnetic Resonance phenomenon has increasingly spread in the recent few decades, mainly owing to its exquisite capability in depicting a contrast between soft tissues, to its generally non-invasive nature, and to the priceless advantage of using non-ionizing radiation. Magnetic Resonance (MR)-based acquisition techniques allow gathering information on the structure (through Magnetic Resonance Imaging— MRI), the metabolic composition (through Magnetic Resonance Spectroscopy—MRS), and the functioning (through functional MRI —fMRI) of the human body. MR investigations are the methods of choice for studying the brain in vivo, including anatomy, structural wiring and functional connectivity, in healthy and pathological conditions. Alongside the efforts of the clinical research community in extending the acquisition protocols to allow the exploration of a large variety of pathologies affecting diverse body regions, some relevant technological improvements are on the way to maximize the impact of MR in medical diagnostic. The development of MR scanners operating at ultra-high magnetic field (UHF) strength (>= 7 tesla), is pushing forward the spatial resolution of MRI and the spectral resolution of MRS, and it is increasing the specificity of fMRI to grey matter signal. UHF MR systems are currently in use for research purposes only; nevertheless, UHF technological advances are positively affecting MR investigations at clinical field strengths. To overcome the current major limitation of MRI, which is mostly based on contrast between tissues rather than on absolute measurements of physical quantities, a new acquisition modality is under development, which is referred as Magnetic Resonance Fingerprinting technique. Finally, as neuroimaging data acquired worldwide are reaching the typical size of Big Data, dedicated technical solutions are required to mine large amount of information and to identify specific biomarkers of

Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

Science.gov (United States)

Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y

2018-04-01

Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping

Generalized PSF modeling for optimized quantitation in PET imaging.

Science.gov (United States)

Ashrafinia, Saeed; Mohy-Ud-Din, Hassan; Karakatsanis, Nicolas A; Jha, Abhinav K; Casey, Michael E; Kadrmas, Dan J; Rahmim, Arman

2017-06-21

Point-spread function (PSF) modeling offers the ability to account for resolution degrading phenomena within the PET image generation framework. PSF modeling improves resolution and enhances contrast, but at the same time significantly alters image noise properties and induces edge overshoot effect. Thus, studying the effect of PSF modeling on quantitation task performance can be very important. Frameworks explored in the past involved a dichotomy of PSF versus no-PSF modeling. By contrast, the present work focuses on quantitative performance evaluation of standard uptake value (SUV) PET images, while incorporating a wide spectrum of PSF models, including those that under- and over-estimate the true PSF, for the potential of enhanced quantitation of SUVs. The developed framework first analytically models the true PSF, considering a range of resolution degradation phenomena (including photon non-collinearity, inter-crystal penetration and scattering) as present in data acquisitions with modern commercial PET systems. In the context of oncologic liver FDG PET imaging, we generated 200 noisy datasets per image-set (with clinically realistic noise levels) using an XCAT anthropomorphic phantom with liver tumours of varying sizes. These were subsequently reconstructed using the OS-EM algorithm with varying PSF modelled kernels. We focused on quantitation of both SUV mean and SUV max , including assessment of contrast recovery coefficients, as well as noise-bias characteristics (including both image roughness and coefficient of-variability), for different tumours/iterations/PSF kernels. It was observed that overestimated PSF yielded more accurate contrast recovery for a range of tumours, and typically improved quantitative performance. For a clinically reasonable number of iterations, edge enhancement due to PSF modeling (especially due to over-estimated PSF) was in fact seen to lower SUV mean bias in small tumours. Overall, the results indicate that exactly matched PSF

Use of Diffusion Spectrum imaging in preliminary longitudinal evaluation of Amyotrophic Lateral Sclerosis: development of an imaging biomarker

Directory of Open Access Journals (Sweden)

Kumar eAbhinav

2014-04-01

Full Text Available Previous diffusion tensor imaging (DTI studies have shown white matter pathology in ALS, predominantly in the motor pathways. Further these studies have shown that DTI can be used longitudinally to track pathology over time, making white matter pathology a candidate as an outcome measure in future trials. DTI has demonstrated application in group studies, however its derived indices, for example fractional anisotropy, are susceptible to partial volume effects, making its role questionable in examining individual progression. We hypothesize that changes in the white matter are present in ALS beyond the motor tracts, and that the affected pathways and associated pattern of disease progression can be tracked longitudinally using automated diffusion connectometry analysis. Connectometry analysis is based on diffusion spectrum imaging (DSI and overcomes the limitations of a conventional tractography approach and DTI. The identified affected white matter tracts can then be assessed in a targeted fashion using High definition fiber tractography (a novel white matter MR imaging technique. Changes in quantitative and qualitative markers over time could then be correlated with clinical progression.We illustrate these principles towards developing an imaging biomarker for demonstrating individual progression, by presenting results for five ALS patients, including with longitudinal data in two. Preliminary analysis demonstrated a number of changes bilaterally and asymmetrically in motoric and extramotoric white matter pathways. Further the limbic system was also affected possibly explaining the cognitive symptoms in ALS. In the two longitudinal subjects, the white matter changes were less extensive at baseline, although there was evidence of disease progression in a frontal pattern with a relatively spared postcentral gyrus, consistent with the known pathology in ALS.

Alzheimer's disease imaging biomarkers using small-angle x-ray scattering

Science.gov (United States)

Choi, Mina; Alam, Nadia; Dahal, Eshan; Ghammraoui, Bahaa; Badano, Aldo

2016-03-01

There is a need for novel imaging techniques for the earlier detection of Alzheimer's disease (AD). Two hallmarks of AD are amyloid beta (Aβ) plaques and tau tangles that are formed in the brain. Well-characterized x-ray cross sections of Aβ and tau proteins in a variety of structural states could potentially be used as AD biomarkers for small-angle x-ray scattering (SAXS) imaging without the need for injectable probes or contrast agents. First, however, the protein structures must be controlled and measured to determine accurate biomarkers for SAXS imaging. Here we report SAXS measurements of Aβ42 and tau352 in a 50% dimethyl sulfoxide (DMSO) solution in which these proteins are believed to remain monomeric because of the stabilizing interaction of DMSO solution. Our SAXS analysis showed the aggregation of both proteins. In particular, we found that the aggregation of Aβ42 slowly progresses with time in comparison to tau352 that aggregates at a faster rate and reaches a steady-state. Furthermore, the measured signals were compared to the theoretical SAXS profiles of Aβ42 monomer, Aβ42 fibril, and tau352 that were computed from their respective protein data bank structures. We have begun the work to systematically control the structural states of these proteins in vitro using various solvent conditions. Our future work is to utilize the distinct SAXS profiles of various structural states of Aβ and tau to build a library of signals of interest for SAXS imaging in brain tissue.

Quantitative methods for the analysis of electron microscope images

DEFF Research Database (Denmark)

Skands, Peter Ulrik Vallø

1996-01-01

The topic of this thesis is an general introduction to quantitative methods for the analysis of digital microscope images. The images presented are primarily been acquired from Scanning Electron Microscopes (SEM) and interfermeter microscopes (IFM). The topic is approached though several examples...... foundation of the thesis fall in the areas of: 1) Mathematical Morphology; 2) Distance transforms and applications; and 3) Fractal geometry. Image analysis opens in general the possibility of a quantitative and statistical well founded measurement of digital microscope images. Herein lies also the conditions...

Quantitative label-free proteomics for discovery of biomarkers in cerebrospinal fluid: assessment of technical and inter-individual variation.

Directory of Open Access Journals (Sweden)

Richard J Perrin

Full Text Available Biomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS for CSF biomarker discovery by (1 identifying reparable sources of technical variability, (2 assessing subject variance and residual technical variability for numerous CSF proteins, and (3 testing its ability to segregate samples on the basis of desired biomarker characteristics.Fourteen aliquots of pooled CSF and two aliquots from six cognitively normal individuals were randomized, enriched for low-abundance proteins by MAF, digested endoproteolytically, randomized again, and analyzed by nano-LC-MS. Nano-LC-MS data were time and m/z aligned across samples for relative peptide quantification. Among 11,433 aligned charge groups, 1360 relatively abundant ones were annotated by MS2, yielding 823 unique peptides. Analyses, including Pearson correlations of annotated LC-MS ion chromatograms, performed for all pairwise sample comparisons, identified several sources of technical variability: i incomplete MAF and keratins; ii globally- or segmentally-decreased ion current in isolated LC-MS analyses; and iii oxidized methionine-containing peptides. Exclusion of these sources yielded 609 peptides representing 81 proteins. Most of these proteins showed very low coefficients of variation (CV<5% whether they were quantified from the mean of all or only the 2 most-abundant peptides. Unsupervised clustering, using only 24 proteins selected for high subject variance, yielded perfect segregation of pooled and

Quantitative proteomic analysis by iTRAQ® for the identification of candidate biomarkers in ovarian cancer serum

Directory of Open Access Journals (Sweden)

Higgins LeeAnn

2010-06-01

Full Text Available Abstract Background Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ®. Results Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ® to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified. Conclusions This study provides the first analysis of immunodepleted serum in combination with iTRAQ® to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

Quantitative Image Restoration in Bright Field Optical Microscopy.

Science.gov (United States)

Gutiérrez-Medina, Braulio; Sánchez Miranda, Manuel de Jesús

2017-11-07

Bright field (BF) optical microscopy is regarded as a poor method to observe unstained biological samples due to intrinsic low image contrast. We introduce quantitative image restoration in bright field (QRBF), a digital image processing method that restores out-of-focus BF images of unstained cells. Our procedure is based on deconvolution, using a point spread function modeled from theory. By comparing with reference images of bacteria observed in fluorescence, we show that QRBF faithfully recovers shape and enables quantify size of individual cells, even from a single input image. We applied QRBF in a high-throughput image cytometer to assess shape changes in Escherichia coli during hyperosmotic shock, finding size heterogeneity. We demonstrate that QRBF is also applicable to eukaryotic cells (yeast). Altogether, digital restoration emerges as a straightforward alternative to methods designed to generate contrast in BF imaging for quantitative analysis. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Rapid and High-Throughput Detection and Quantitation of Radiation Biomarkers in Human and Nonhuman Primates by Differential Mobility Spectrometry-Mass Spectrometry

Science.gov (United States)

Chen, Zhidan; Coy, Stephen L.; Pannkuk, Evan L.; Laiakis, Evagelia C.; Hall, Adam B.; Fornace, Albert J.; Vouros, Paul

2016-10-01

Radiation exposure is an important public health issue due to a range of accidental and intentional threats. Prompt and effective large-scale screening and appropriate use of medical countermeasures (MCM) to mitigate radiation injury requires rapid methods for determining the radiation dose. In a number of studies, metabolomics has identified small-molecule biomarkers responding to the radiation dose. Differential mobility spectrometry-mass spectrometry (DMS-MS) has been used for similar compounds for high-throughput small-molecule detection and quantitation. In this study, we show that DMS-MS can detect and quantify two radiation biomarkers, trimethyl-L-lysine (TML) and hypoxanthine. Hypoxanthine is a human and nonhuman primate (NHP) radiation biomarker and metabolic intermediate, whereas TML is a radiation biomarker in humans but not in NHP, which is involved in carnitine synthesis. They have been analyzed by DMS-MS from urine samples after a simple strong cation exchange-solid phase extraction (SCX-SPE). The dramatic suppression of background and chemical noise provided by DMS-MS results in an approximately 10-fold reduction in time, including sample pretreatment time, compared with liquid chromatography-mass spectrometry (LC-MS). DMS-MS quantitation accuracy has been verified by validation testing for each biomarker. Human samples are not yet available, but for hypoxanthine, selected NHP urine samples (pre- and 7-d-post 10 Gy exposure) were analyzed, resulting in a mean change in concentration essentially identical to that obtained by LC-MS (fold-change 2.76 versus 2.59). These results confirm the potential of DMS-MS for field or clinical first-level rapid screening for radiation exposure.

GPC and quantitative phase imaging

DEFF Research Database (Denmark)

Palima, Darwin; Banas, Andrew Rafael; Villangca, Mark Jayson

2016-01-01

shaper followed by the potential of GPC for biomedical and multispectral applications where we experimentally demonstrate the active light shaping of a supercontinuum laser over most of the visible wavelength range. Finally, we discuss how GPC can be advantageously applied for Quantitative Phase Imaging...

Gastrointestinal stromal tumours: Correlation of modified NIH risk stratification with diffusion-weighted MR imaging as an imaging biomarker

International Nuclear Information System (INIS)

Kang, Tae Wook; Kim, Seong Hyun; Jang, Kyung Mi; Choi, Dongil; Ha, Sang Yun; Kim, Kyoung-Mee; Kang, Won Ki; Kim, Min Ji

2015-01-01

Highlights: • Except size and necrosis, conventional MR findings of GISTs were not significantly different according to the modified NIH criteria. • The ADC values of GISTs were negatively correlated with the modified NIH criteria. • The ADC value can be helpful for the determination of intermediate or high-risk GISTs. - Abstract: Purpose: To evaluate the correlation of risk grade of gastrointestinal stromal tumours (GISTs) based on modified National Institutes of Health (NIH) criteria with conventional magnetic resonance (MR) imaging and diffusion-weighted (DW) imaging. Methods: We included 22 patients with histopathologically proven GISTs in the stomach or small bowel who underwent pre-operative gadoxetic acid-enhanced MR imaging and DW imaging. We retrospectively assessed correlations between morphologic findings, qualitative (signal intensity, consensus from two observers) and quantitative (degree of dynamic enhancement using signal intensity of tumour/muscle ratio and apparent diffusion coefficient [ADC]) values, and the modified NIH criteria for risk stratification. Spearman partial correlation analysis was used to control for tumour size as a confounding factor. The optimal cut-off level of ADC values for intermediate or high risk GISTs was analyzed using a receiver operating characteristic analysis. Results: Except tumour size and necrosis, conventional MR imaging findings, including the degree of dynamic enhancement, were not significantly different according to the modified NIH criteria (p > 0.05). Tumour ADC values were negatively correlated with the modified NIH criteria, before and after adjustment of tumour size (ρ = −0.754; p < 0.001 and ρ = −0.513; p = 0.017, respectively). The optimal cut-off value for the determination of intermediate or high-risk GISTs was 1.279 × 10 −3 mm 2 /s (100% sensitivity, 69.2% specificity, 81.8% accuracy). Conclusion: Except tumour size and necrosis, conventional MR imaging findings did not correlate with

Gastrointestinal stromal tumours: Correlation of modified NIH risk stratification with diffusion-weighted MR imaging as an imaging biomarker

Energy Technology Data Exchange (ETDEWEB)

Kang, Tae Wook [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Kim, Seong Hyun, E-mail: kshyun@skku.edu [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Jang, Kyung Mi; Choi, Dongil [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Ha, Sang Yun; Kim, Kyoung-Mee [Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Kang, Won Ki [Division of Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Kim, Min Ji [Biostatics Unit, Samsung Biomedical Research Institute, Samsung Medical Center, Seoul 135-710 (Korea, Republic of)

2015-01-15

Highlights: • Except size and necrosis, conventional MR findings of GISTs were not significantly different according to the modified NIH criteria. • The ADC values of GISTs were negatively correlated with the modified NIH criteria. • The ADC value can be helpful for the determination of intermediate or high-risk GISTs. - Abstract: Purpose: To evaluate the correlation of risk grade of gastrointestinal stromal tumours (GISTs) based on modified National Institutes of Health (NIH) criteria with conventional magnetic resonance (MR) imaging and diffusion-weighted (DW) imaging. Methods: We included 22 patients with histopathologically proven GISTs in the stomach or small bowel who underwent pre-operative gadoxetic acid-enhanced MR imaging and DW imaging. We retrospectively assessed correlations between morphologic findings, qualitative (signal intensity, consensus from two observers) and quantitative (degree of dynamic enhancement using signal intensity of tumour/muscle ratio and apparent diffusion coefficient [ADC]) values, and the modified NIH criteria for risk stratification. Spearman partial correlation analysis was used to control for tumour size as a confounding factor. The optimal cut-off level of ADC values for intermediate or high risk GISTs was analyzed using a receiver operating characteristic analysis. Results: Except tumour size and necrosis, conventional MR imaging findings, including the degree of dynamic enhancement, were not significantly different according to the modified NIH criteria (p > 0.05). Tumour ADC values were negatively correlated with the modified NIH criteria, before and after adjustment of tumour size (ρ = −0.754; p < 0.001 and ρ = −0.513; p = 0.017, respectively). The optimal cut-off value for the determination of intermediate or high-risk GISTs was 1.279 × 10{sup −3} mm{sup 2}/s (100% sensitivity, 69.2% specificity, 81.8% accuracy). Conclusion: Except tumour size and necrosis, conventional MR imaging findings did not

Quantitative Imaging in Cancer Evolution and Ecology

Science.gov (United States)

Grove, Olya; Gillies, Robert J.

2013-01-01

Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral

Advancing Precision Nuclear Medicine and Molecular Imaging for Lymphoma.

Science.gov (United States)

Wright, Chadwick L; Maly, Joseph J; Zhang, Jun; Knopp, Michael V

2017-01-01

PET with fluorodeoxyglucose F 18 ( 18 F FDG-PET) is a meaningful biomarker for the detection, targeted biopsy, and treatment of lymphoma. This article reviews the evolution of 18 F FDG-PET as a putative biomarker for lymphoma and addresses the current capabilities, challenges, and opportunities to enable precision medicine practices for lymphoma. Precision nuclear medicine is driven by new imaging technologies and methodologies to more accurately detect malignant disease. Although quantitative assessment of response is limited, such technologies will enable a more precise metabolic mapping with much higher definition image detail and thus may make it a robust and valid quantitative response assessment methodology. Copyright © 2016 Elsevier Inc. All rights reserved.

Prospects and challenges of quantitative phase imaging in tumor cell biology

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Kemper, Björn; Götte, Martin; Greve, Burkhard; Ketelhut, Steffi

2016-03-01

Quantitative phase imaging (QPI) techniques provide high resolution label-free quantitative live cell imaging. Here, prospects and challenges of QPI in tumor cell biology are presented, using the example of digital holographic microscopy (DHM). It is shown that the evaluation of quantitative DHM phase images allows the retrieval of different parameter sets for quantification of cellular motion changes in migration and motility assays that are caused by genetic modifications. Furthermore, we demonstrate simultaneously label-free imaging of cell growth and morphology properties.

Applying Data-driven Imaging Biomarker in Mammography for Breast Cancer Screening: Preliminary Study.

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Kim, Eun-Kyung; Kim, Hyo-Eun; Han, Kyunghwa; Kang, Bong Joo; Sohn, Yu-Mee; Woo, Ok Hee; Lee, Chan Wha

2018-02-09

We assessed the feasibility of a data-driven imaging biomarker based on weakly supervised learning (DIB; an imaging biomarker derived from large-scale medical image data with deep learning technology) in mammography (DIB-MG). A total of 29,107 digital mammograms from five institutions (4,339 cancer cases and 24,768 normal cases) were included. After matching patients' age, breast density, and equipment, 1,238 and 1,238 cases were chosen as validation and test sets, respectively, and the remainder were used for training. The core algorithm of DIB-MG is a deep convolutional neural network; a deep learning algorithm specialized for images. Each sample (case) is an exam composed of 4-view images (RCC, RMLO, LCC, and LMLO). For each case in a training set, the cancer probability inferred from DIB-MG is compared with the per-case ground-truth label. Then the model parameters in DIB-MG are updated based on the error between the prediction and the ground-truth. At the operating point (threshold) of 0.5, sensitivity was 75.6% and 76.1% when specificity was 90.2% and 88.5%, and AUC was 0.903 and 0.906 for the validation and test sets, respectively. This research showed the potential of DIB-MG as a screening tool for breast cancer.

Qualitative and quantitative characterization of plasma proteins when incorporating traveling wave ion mobility into a liquid chromatography-mass spectrometry workflow for biomarker discovery: use of product ion quantitation as an alternative data analysis tool for label free quantitation.

Science.gov (United States)

Daly, Charlotte E; Ng, Leong L; Hakimi, Amirmansoor; Willingale, Richard; Jones, Donald J L

2014-02-18

Discovery of protein biomarkers in clinical samples necessitates significant prefractionation prior to liquid chromatography-mass spectrometry (LC-MS) analysis. Integrating traveling wave ion mobility spectrometry (TWIMS) enables in-line gas phase separation which when coupled with nanoflow liquid chromatography and data independent acquisition tandem mass spectrometry, confers significant advantages to the discovery of protein biomarkers by improving separation and inherent sensitivity. Incorporation of TWIMS leads to a packet of concentrated ions which ultimately provides a significant improvement in sensitivity. As a consequence of ion packeting, when present at high concentrations, accurate quantitation of proteins can be affected due to detector saturation effects. Human plasma was analyzed in triplicate using liquid-chromatography data independent acquisition mass spectrometry (LC-DIA-MS) and using liquid-chromatography ion-mobility data independent acquisition mass spectrometry (LC-IM-DIA-MS). The inclusion of TWIMS was assessed for the effect on sample throughput, data integrity, confidence of protein and peptide identification, and dynamic range. The number of identified proteins is significantly increased by an average of 84% while both the precursor and product mass accuracies are maintained between the modalities. Sample dynamic range is also maintained while quantitation is achieved for all but the most abundant proteins by incorporating a novel data interpretation method that allows accurate quantitation to occur. This additional separation is all achieved within a workflow with no discernible deleterious effect on throughput. Consequently, TWIMS greatly enhances proteome coverage and can be reliably used for quantification when using an alternative product ion quantification strategy. Using TWIMS in biomarker discovery in human plasma is thus recommended.

Skeletal muscle magnetic resonance biomarkers correlate with function and sentinel events in Duchenne muscular dystrophy.

Science.gov (United States)

Barnard, Alison M; Willcocks, Rebecca J; Finanger, Erika L; Daniels, Michael J; Triplett, William T; Rooney, William D; Lott, Donovan J; Forbes, Sean C; Wang, Dah-Jyuu; Senesac, Claudia R; Harrington, Ann T; Finkel, Richard S; Russman, Barry S; Byrne, Barry J; Tennekoon, Gihan I; Walter, Glenn A; Sweeney, H Lee; Vandenborne, Krista

2018-01-01

To provide evidence for quantitative magnetic resonance (qMR) biomarkers in Duchenne muscular dystrophy by investigating the relationship between qMR measures of lower extremity muscle pathology and functional endpoints in a large ambulatory cohort using a multicenter study design. MR spectroscopy and quantitative imaging were implemented to measure intramuscular fat fraction and the transverse magnetization relaxation time constant (T2) in lower extremity muscles of 136 participants with Duchenne muscular dystrophy. Measures were collected at 554 visits over 48 months at one of three imaging sites. Fat fraction was measured in the soleus and vastus lateralis using MR spectroscopy, while T2 was assessed using MRI in eight lower extremity muscles. Ambulatory function was measured using the 10m walk/run, climb four stairs, supine to stand, and six minute walk tests. Significant correlations were found between all qMR and functional measures. Vastus lateralis qMR measures correlated most strongly to functional endpoints (|ρ| = 0.68-0.78), although measures in other rapidly progressing muscles including the biceps femoris (|ρ| = 0.63-0.73) and peroneals (|ρ| = 0.59-0.72) also showed strong correlations. Quantitative MR biomarkers were excellent indicators of loss of functional ability and correlated with qualitative measures of function. A VL FF of 0.40 was an approximate lower threshold of muscle pathology associated with loss of ambulation. Lower extremity qMR biomarkers have a robust relationship to clinically meaningful measures of ambulatory function in Duchenne muscular dystrophy. These results provide strong supporting evidence for qMR biomarkers and set the stage for their potential use as surrogate outcomes in clinical trials.

Quantitative Methods for Molecular Diagnostic and Therapeutic Imaging

OpenAIRE

Li, Quanzheng

2013-01-01

This theme issue provides an overview on the basic quantitative methods, an in-depth discussion on the cutting-edge quantitative analysis approaches as well as their applications for both static and dynamic molecular diagnostic and therapeutic imaging.

Quantitative multimodality imaging in cancer research and therapy.

Science.gov (United States)

Yankeelov, Thomas E; Abramson, Richard G; Quarles, C Chad

2014-11-01

Advances in hardware and software have enabled the realization of clinically feasible, quantitative multimodality imaging of tissue pathophysiology. Earlier efforts relating to multimodality imaging of cancer have focused on the integration of anatomical and functional characteristics, such as PET-CT and single-photon emission CT (SPECT-CT), whereas more-recent advances and applications have involved the integration of multiple quantitative, functional measurements (for example, multiple PET tracers, varied MRI contrast mechanisms, and PET-MRI), thereby providing a more-comprehensive characterization of the tumour phenotype. The enormous amount of complementary quantitative data generated by such studies is beginning to offer unique insights into opportunities to optimize care for individual patients. Although important technical optimization and improved biological interpretation of multimodality imaging findings are needed, this approach can already be applied informatively in clinical trials of cancer therapeutics using existing tools. These concepts are discussed herein.

Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.

Science.gov (United States)

Boissoneault, Jeff; Sevel, Landrew; Letzen, Janelle; Robinson, Michael; Staud, Roland

2017-01-01

Chronic musculoskeletal pain condition often shows poor correlations between tissue abnormalities and clinical pain. Therefore, classification of pain conditions like chronic low back pain, osteoarthritis, and fibromyalgia depends mostly on self report and less on objective findings like X-ray or magnetic resonance imaging (MRI) changes. However, recent advances in structural and functional brain imaging have identified brain abnormalities in chronic pain conditions that can be used for illness classification. Because the analysis of complex and multivariate brain imaging data is challenging, machine learning techniques have been increasingly utilized for this purpose. The goal of machine learning is to train specific classifiers to best identify variables of interest on brain MRIs (i.e., biomarkers). This report describes classification techniques capable of separating MRI-based brain biomarkers of chronic pain patients from healthy controls with high accuracy (70-92%) using machine learning, as well as critical scientific, practical, and ethical considerations related to their potential clinical application. Although self-report remains the gold standard for pain assessment, machine learning may aid in the classification of chronic pain disorders like chronic back pain and fibromyalgia as well as provide mechanistic information regarding their neural correlates.

Quantitative image processing in fluid mechanics

Science.gov (United States)

Hesselink, Lambertus; Helman, James; Ning, Paul

1992-01-01

The current status of digital image processing in fluid flow research is reviewed. In particular, attention is given to a comprehensive approach to the extraction of quantitative data from multivariate databases and examples of recent developments. The discussion covers numerical simulations and experiments, data processing, generation and dissemination of knowledge, traditional image processing, hybrid processing, fluid flow vector field topology, and isosurface analysis using Marching Cubes.

Meta-analysis of the technical performance of an imaging procedure: guidelines and statistical methodology.

Science.gov (United States)

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2015-02-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test-retest repeatability data for illustrative purposes. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

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Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

Infrared thermography quantitative image processing

Science.gov (United States)

Skouroliakou, A.; Kalatzis, I.; Kalyvas, N.; Grivas, TB

2017-11-01

Infrared thermography is an imaging technique that has the ability to provide a map of temperature distribution of an object’s surface. It is considered for a wide range of applications in medicine as well as in non-destructive testing procedures. One of its promising medical applications is in orthopaedics and diseases of the musculoskeletal system where temperature distribution of the body’s surface can contribute to the diagnosis and follow up of certain disorders. Although the thermographic image can give a fairly good visual estimation of distribution homogeneity and temperature pattern differences between two symmetric body parts, it is important to extract a quantitative measurement characterising temperature. Certain approaches use temperature of enantiomorphic anatomical points, or parameters extracted from a Region of Interest (ROI). A number of indices have been developed by researchers to that end. In this study a quantitative approach in thermographic image processing is attempted based on extracting different indices for symmetric ROIs on thermograms of the lower back area of scoliotic patients. The indices are based on first order statistical parameters describing temperature distribution. Analysis and comparison of these indices result in evaluating the temperature distribution pattern of the back trunk expected in healthy, regarding spinal problems, subjects.

Quantitative phase imaging and differential interference contrast imaging for biological TEM

International Nuclear Information System (INIS)

Allman, B.E.; McMahon, P.J.; Barone-Nugent, E.D.; Nugent, E.D.

2002-01-01

Full text: Phase microscopy is a central technique in science. An experienced microscopist uses this effect to visualise (edge) structure within transparent samples by slightly defocusing the microscope. Although widespread in optical microscopy, phase contrast transmission electron microscopy (TEM) has not been widely adopted. TEM for biological specimens has largely relied on staining techniques to yield sufficient contrast. We show here a simple method for quantitative TEM phase microscopy that quantifies this phase contrast effect. Starting with conventional, digital, bright field images of the sample, our algorithm provides quantitative phase information independent of the sample's bright field intensity image. We present TEM phase images of a range of stained and unstained, biological and material science specimens. This independent phase and intensity information is then used to emulate a range of phase visualisation images familiar to optical microscopy, e.g. differential interference contrast. The phase images contain features not visible with the other imaging modalities. Further, if the TEM samples have been prepared on a microtome to a uniform thickness, the phase information can be converted into refractive index structure of the specimen. Copyright (2002) Australian Society for Electron Microscopy Inc

Use of posttreatment imaging and biomarkers in survivors of early-stage breast cancer: Inappropriate surveillance or necessary care?

Science.gov (United States)

Hahn, Erin E; Tang, Tania; Lee, Janet S; Munoz-Plaza, Corrine E; Shen, Ernest; Rowley, Braden; Maeda, Jared L; Mosen, David M; Ruckdeschel, John C; Gould, Michael K

2016-03-15

Advanced imaging and serum biomarkers are commonly used for surveillance in patients with early-stage breast cancer, despite recommendations against this practice. Incentives to perform such low-value testing may be less prominent in integrated health care delivery systems. The purpose of the current study was to evaluate and compare the use of these services within 2 integrated systems: Kaiser Permanente (KP) and Intermountain Healthcare (IH). The authors also sought to distinguish the indication for testing: diagnostic purposes or routine surveillance. Patients with American Joint Committee on Cancer stage 0 to II breast cancer diagnosed between 2009 and 2010 were identified and the use of imaging and biomarker tests over an 18-month period were quantified, starting at 1 year after diagnosis. Chart abstraction was performed on a random sample of patients who received testing to identify the indication for testing. Multivariate regression was used to explore associations with the use of nonrecommended care. A total of 6585 patients were identified; 22% had stage 0 disease, 44% had stage I disease, and 34% had stage II disease. Overall, 24% of patients received at least 1 imaging test (25% at KP vs 22% at IH; P = .009) and 28% of patients received at least 1 biomarker (36% at KP vs 13% at IH; Ptests were performed to evaluate symptoms or signs. Virtually all biomarkers were ordered for routine surveillance. Stage of disease, medical center that provided the services, and provider experience were found to be significantly associated with the use of biomarkers. Advanced imaging was most often performed for appropriate indications, but biomarkers were used for nonrecommended surveillance. Distinguishing between inappropriate use for surveillance and appropriate diagnostic testing is essential when evaluating adherence to recommendations. © 2015 American Cancer Society.

Reliability of Using Retinal Vascular Fractal Dimension as a Biomarker in the Diabetic Retinopathy Detection.

Science.gov (United States)

Huang, Fan; Dashtbozorg, Behdad; Zhang, Jiong; Bekkers, Erik; Abbasi-Sureshjani, Samaneh; Berendschot, Tos T J M; Ter Haar Romeny, Bart M

2016-01-01

The retinal fractal dimension (FD) is a measure of vasculature branching pattern complexity. FD has been considered as a potential biomarker for the detection of several diseases like diabetes and hypertension. However, conflicting findings were found in the reported literature regarding the association between this biomarker and diseases. In this paper, we examine the stability of the FD measurement with respect to (1) different vessel annotations obtained from human observers, (2) automatic segmentation methods, (3) various regions of interest, (4) accuracy of vessel segmentation methods, and (5) different imaging modalities. Our results demonstrate that the relative errors for the measurement of FD are significant and FD varies considerably according to the image quality, modality, and the technique used for measuring it. Automated and semiautomated methods for the measurement of FD are not stable enough, which makes FD a deceptive biomarker in quantitative clinical applications.

Molecular imaging reveals elevated VEGFR-2 expression in retinal capillaries in diabetes: a novel biomarker for early diagnosis

Science.gov (United States)

Sun, Dawei; Nakao, Shintaro; Xie, Fang; Zandi, Souska; Bagheri, Abouzar; Kanavi, Mozhgan Rezaei; Samiei, Shahram; Soheili, Zahra-Soheila; Frimmel, Sonja; Zhang, Zhongyu; Ablonczy, Zsolt; Ahmadieh, Hamid; Hafezi-Moghadam, Ali

2014-01-01

Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of vision loss. Biomarkers and methods for early diagnosis of DR are urgently needed. Using a new molecular imaging approach, we show up to 94% higher accumulation of custom designed imaging probes against vascular endothelial growth factor receptor 2 (VEGFR-2) in retinal and choroidal vessels of diabetic animals (PM. R., Samiei, S., Soheili, Z.-S., Frimmel, S., Zhang, Z., Ablonczy, Z., Ahmadieh, H., Hafezi-Moghadam, A. Molecular imaging reveals elevated VEGFR-2 expression in retinal capillaries in diabetes: a novel biomarker for early diagnosis. PMID:24903276

An Ibm PC/AT-Based Image Acquisition And Processing System For Quantitative Image Analysis

Science.gov (United States)

Kim, Yongmin; Alexander, Thomas

1986-06-01

In recent years, a large number of applications have been developed for image processing systems in the area of biological imaging. We have already finished the development of a dedicated microcomputer-based image processing and analysis system for quantitative microscopy. The system's primary function has been to facilitate and ultimately automate quantitative image analysis tasks such as the measurement of cellular DNA contents. We have recognized from this development experience, and interaction with system users, biologists and technicians, that the increasingly widespread use of image processing systems, and the development and application of new techniques for utilizing the capabilities of such systems, would generate a need for some kind of inexpensive general purpose image acquisition and processing system specially tailored for the needs of the medical community. We are currently engaged in the development and testing of hardware and software for a fairly high-performance image processing computer system based on a popular personal computer. In this paper, we describe the design and development of this system. Biological image processing computer systems have now reached a level of hardware and software refinement where they could become convenient image analysis tools for biologists. The development of a general purpose image processing system for quantitative image analysis that is inexpensive, flexible, and easy-to-use represents a significant step towards making the microscopic digital image processing techniques more widely applicable not only in a research environment as a biologist's workstation, but also in clinical environments as a diagnostic tool.

Parametric biomedical imaging - what defines the quality of quantitative radiological approaches?

International Nuclear Information System (INIS)

Glueer, C.C.; Barkmann, R.; Bolte, H.; Heller, M.; Hahn, H.K.; Dicken, V.; Majumdar, S.; Eckstein, F.; Nickelsen, T.N.

2006-01-01

Quantitative parametric imaging approaches provide new perspectives for radiological imaging. These include quantitative 2D, 3D, and 4D visualization options along with the parametric depiction of biological tissue properties and tissue function. This allows the interpretation of radiological data from a biochemical, biomechanical, or physiological perspective. Quantification permits the detection of small changes that are not yet visually apparent, thus allowing application in early disease diagnosis and monitoring therapy with enhanced sensitivity. This review outlines the potential of quantitative parametric imaging methods and demonstrates this on the basis of a few exemplary applications. One field of particular interest, the use of these methods for investigational new drug application studies, is presented. Assessment criteria for judging the quality of quantitative imaging approaches are discussed in the context of the potential and the limitations of these methods. While quantitative parametric imaging methods do not replace but rather supplement established visual interpretation methods in radiology, they do open up new perspectives for diagnosis and prognosis and in particular for monitoring disease progression and therapy. (orig.)

Nuclear medicine and imaging research (instrumentation and quantitative methods of evaluation)

International Nuclear Information System (INIS)

Beck, R.N.; Cooper, M.; Chen, C.T.

1992-07-01

This document is the annual progress report for project entitled ''Instrumentation and Quantitative Methods of Evaluation.'' Progress is reported in separate sections individually abstracted and indexed for the database. Subject areas reported include theoretical studies of imaging systems and methods, hardware developments, quantitative methods of evaluation, and knowledge transfer: education in quantitative nuclear medicine imaging

Quantitative study of undersampled recoverability for sparse images in computed tomography

DEFF Research Database (Denmark)

Jørgensen, Jakob Heide; Sidky, Emil Y.; Hansen, Per Christian

2012-01-01

on artificial random sampling patterns. We establish quantitatively an average-case relation between image sparsity and sufficient number of measurements for recovery, and we show that the transition from non-recovery to recovery is sharp within well-defined classes of simple and semi-realistic test images....... The specific behavior depends on the type of image, but the same quantitative relation holds independently of image size....

Image Based Biomarker of Breast Cancer Risk: Analysis of Risk Disparity Among Minority Populations

Science.gov (United States)

2014-03-01

cluster locations. In the undirected strategy, the PDF is uniform within the entire volume of the breast , while in...stereoscopic breast biopsy images (13, 14). Each cluster in the database is stored as a 3D binary volume, with a voxel value of ‘1’ representing...AD_________________ Award Number: W81XWH-09-1-0062 TITLE: Image Based Biomarker of Breast Cancer

Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery.

Science.gov (United States)

Quanico, Jusal; Franck, Julien; Wisztorski, Maxence; Salzet, Michel; Fournier, Isabelle

2017-01-01

Mapping provides a direct means to assess the impact of protein biomarkers and puts into context their relevance in the type of cancer being examined. To this end, mass spectrometry imaging (MSI) was developed to provide the needed spatial information which is missing in traditional liquid-based mass spectrometric proteomics approaches. Aptly described as a "molecular histology" technique, MSI gives an additional dimension in characterizing tumor biopsies, allowing for mapping of hundreds of molecules in a single analysis. A decade of developments focused on improving and standardizing MSI so that the technique can be translated into the clinical setting. This review describes the progress made in addressing the technological development that allows to bridge local protein detection by MSI to its identification and to illustrate its potential in studying various aspects of cancer biomarker discovery.

18F-Fluorothymidine-Pet Imaging of Glioblastoma Multiforme: Effects of Radiation Therapy on Radiotracer Uptake and Molecular Biomarker Patterns

Directory of Open Access Journals (Sweden)

Sanjay Chandrasekaran

2013-01-01

Full Text Available Introduction. PET imaging is a useful clinical tool for studying tumor progression and treatment effects. Conventional 18F-FDG-PET imaging is of limited usefulness for imaging Glioblastoma Multiforme (GBM due to high levels of glucose uptake by normal brain and the resultant signal-to-noise intensity. 18F-Fluorothymidine (FLT in contrast has shown promise for imaging GBM, as thymidine is taken up preferentially by proliferating cells. These studies were undertaken to investigate the effectiveness of 18F-FLT-PET in a GBM mouse model, especially after radiation therapy (RT, and its correlation with useful biomarkers, including proliferation and DNA damage. Methods. Nude/athymic mice with human GBM orthografts were assessed by microPET imaging with 18F-FDG and 18F-FLT. Patterns of tumor PET imaging were then compared to immunohistochemistry and immunofluorescence for markers of proliferation (Ki-67, DNA damage and repair (γH2AX, hypoxia (HIF-1α, and angiogenesis (VEGF. Results. We confirmed that 18F-FLT-PET uptake is limited in healthy mice but enhanced in the intracranial tumors. Our data further demonstrate that 18F-FLT-PET imaging usefully reflects the inhibition of tumor by RT and correlates with changes in biomarker expression. Conclusions. 18F-FLT-PET imaging is a promising tumor imaging modality for GBM, including assessing RT effects and biologically relevant biomarkers.

Biomarkers: in medicine, drug discovery, and environmental health

National Research Council Canada - National Science Library

Vaidya, Vishal S; Bonventre, Joseph V

2010-01-01

... Identification Using Mass Spectrometry Sample Preparation Protein Quantitation Examples of Biomarker Discovery and Evaluation Challenges in Proteomic Biomarker Discovery The Road Forward: Targeted ...

Quantitative magnetic resonance micro-imaging methods for pharmaceutical research.

Science.gov (United States)

Mantle, M D

2011-09-30

The use of magnetic resonance imaging (MRI) as a tool in pharmaceutical research is now well established and the current literature covers a multitude of different pharmaceutically relevant research areas. This review focuses on the use of quantitative magnetic resonance micro-imaging techniques and how they have been exploited to extract information that is of direct relevance to the pharmaceutical industry. The article is divided into two main areas. The first half outlines the theoretical aspects of magnetic resonance and deals with basic magnetic resonance theory, the effects of nuclear spin-lattice (T(1)), spin-spin (T(2)) relaxation and molecular diffusion upon image quantitation, and discusses the applications of rapid magnetic resonance imaging techniques. In addition to the theory, the review aims to provide some practical guidelines for the pharmaceutical researcher with an interest in MRI as to which MRI pulse sequences/protocols should be used and when. The second half of the article reviews the recent advances and developments that have appeared in the literature concerning the use of quantitative micro-imaging methods to pharmaceutically relevant research. Copyright © 2010 Elsevier B.V. All rights reserved.

Novel applications of quantitative MRI for the fetal brain

Energy Technology Data Exchange (ETDEWEB)

Clouchoux, Cedric [Children' s National Medical Center, Division of Diagnostic Imaging and Radiology, Washington, DC (United States); Limperopoulos, Catherine [Children' s National Medical Center, Division of Diagnostic Imaging and Radiology, Washington, DC (United States); McGill University, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal (Canada); McGill University, Department of Neurology and Neurosurgery, Montreal (Canada); Children' s National Medical Center, Division of Fetal and Transitional Medicine, Washington, DC (United States)

2012-01-15

The advent of ultrafast MRI acquisitions is offering vital insights into the critical maturational events that occur throughout pregnancy. Concurrent with the ongoing enhancement of ultrafast imaging has been the development of innovative image-processing techniques that are enabling us to capture and quantify the exuberant growth, and organizational and remodeling processes that occur during fetal brain development. This paper provides an overview of the role of advanced neuroimaging techniques to study in vivo brain maturation and explores the application of a range of new quantitative imaging biomarkers that can be used clinically to monitor high-risk pregnancies. (orig.)

Electroencephalography Is a Good Complement to Currently Established Dementia Biomarkers

DEFF Research Database (Denmark)

Ferreira, Daniel; Jelic, Vesna; Cavallin, Lena

2016-01-01

, 135 Alzheimer's disease (AD), 15 dementia with Lewy bodies/Parkinson's disease with dementia (DLB/PDD), 32 other dementias]. The EEG data were recorded in a standardized way. Structural imaging data were visually rated using scales of atrophy in the medial temporal, frontal, and posterior cortex......BACKGROUND/AIMS: Dementia biomarkers that are accessible and easily applicable in nonspecialized clinical settings are urgently needed. Quantitative electroencephalography (qEEG) is a good candidate, and the statistical pattern recognition (SPR) method has recently provided promising results. We......EEG to the diagnostic workup substantially increases the detection of AD pathology even in pre-dementia stages and improves differential diagnosis. EEG could serve as a good complement to currently established dementia biomarkers since it is cheap, noninvasive, and extensively applied outside academic centers....

Differences in Normal Tissue Response in the Esophagus Between Proton and Photon Radiation Therapy for Non-Small Cell Lung Cancer Using In Vivo Imaging Biomarkers.

Science.gov (United States)

Niedzielski, Joshua S; Yang, Jinzhong; Mohan, Radhe; Titt, Uwe; Mirkovic, Dragan; Stingo, Francesco; Liao, Zhongxing; Gomez, Daniel R; Martel, Mary K; Briere, Tina M; Court, Laurence E

2017-11-15

To determine whether there exists any significant difference in normal tissue toxicity between intensity modulated radiation therapy (IMRT) or proton therapy for the treatment of non-small cell lung cancer. A total of 134 study patients (n=49 treated with proton therapy, n=85 with IMRT) treated in a randomized trial had a previously validated esophageal toxicity imaging biomarker, esophageal expansion, quantified during radiation therapy, as well as esophagitis grade (Common Terminology Criteria for Adverse Events version 3.0), on a weekly basis during treatment. Differences between the 2 modalities were statically analyzed using the imaging biomarker metric value (Kruskal-Wallis analysis of variance), as well as the incidence and severity of esophagitis grade (χ 2 and Fisher exact tests, respectively). The dose-response of the imaging biomarker was also compared between modalities using esophageal equivalent uniform dose, as well as delivered dose to an isotropic esophageal subvolume. No statistically significant difference in the distribution of esophagitis grade, the incidence of grade ≥3 esophagitis (15 and 11 patients treated with IMRT and proton therapy, respectively), or the esophageal expansion imaging biomarker between cohorts (P>.05) was found. The distribution of imaging biomarker metric values had similar distributions between treatment arms, despite a slightly higher dose volume in the proton arm (P>.05). Imaging biomarker dose-response was similar between modalities for dose quantified as esophageal equivalent uniform dose and delivered esophageal subvolume dose. Regardless of treatment modality, there was high variability in imaging biomarker response, as well as esophagitis grade, for similar esophageal doses between patients. There was no significant difference in esophageal toxicity from either proton- or photon-based radiation therapy as quantified by esophagitis grade or the esophageal expansion imaging biomarker. Copyright © 2017 Elsevier

Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

Science.gov (United States)

Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

2017-12-01

Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

Toward objective and quantitative evaluation of imaging systems using images of phantoms

International Nuclear Information System (INIS)

Gagne, Robert M.; Gallas, Brandon D.; Myers, Kyle J.

2006-01-01

The use of imaging phantoms is a common method of evaluating image quality in the clinical setting. These evaluations rely on a subjective decision by a human observer with respect to the faintest detectable signal(s) in the image. Because of the variable and subjective nature of the human-observer scores, the evaluations manifest a lack of precision and a potential for bias. The advent of digital imaging systems with their inherent digital data provides the opportunity to use techniques that do not rely on human-observer decisions and thresholds. Using the digital data, signal-detection theory (SDT) provides the basis for more objective and quantitative evaluations which are independent of a human-observer decision threshold. In a SDT framework, the evaluation of imaging phantoms represents a 'signal-known-exactly/background-known-exactly' ('SKE/BKE') detection task. In this study, we compute the performance of prewhitening and nonprewhitening model observers in terms of the observer signal-to-noise ratio (SNR) for these 'SKE/BKE' tasks. We apply the evaluation methods to a number of imaging systems. For example, we use data from a laboratory implementation of digital radiography and from a full-field digital mammography system in a clinical setting. In addition, we make a comparison of our methods to human-observer scoring of a set of digital images of the CDMAM phantom available from the internet (EUREF--European Reference Organization). In the latter case, we show a significant increase in the precision of the quantitative methods versus the variability in the scores from human observers on the same set of images. As regards bias, the performance of a model observer estimated from a finite data set is known to be biased. In this study, we minimize the bias and estimate the variance of the observer SNR using statistical resampling techniques, namely, 'bootstrapping' and 'shuffling' of the data sets. Our methods provide objective and quantitative evaluation of

Regional Ventilation Changes in the Lung: Treatment Response Mapping by Using Hyperpolarized Gas MR Imaging as a Quantitative Biomarker.

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Horn, Felix C; Marshall, Helen; Collier, Guilhem J; Kay, Richard; Siddiqui, Salman; Brightling, Christopher E; Parra-Robles, Juan; Wild, Jim M

2017-09-01

Purpose To assess the magnitude of regional response to respiratory therapeutic agents in the lungs by using treatment response mapping (TRM) with hyperpolarized gas magnetic resonance (MR) imaging. TRM was used to quantify regional physiologic response in adults with asthma who underwent a bronchodilator challenge. Materials and Methods This study was approved by the national research ethics committee and was performed with informed consent. Imaging was performed in 20 adult patients with asthma by using hyperpolarized helium 3 ( 3 He) ventilation MR imaging. Two sets of baseline images were acquired before inhalation of a bronchodilating agent (salbutamol 400 μg), and one set was acquired after. All images were registered for voxelwise comparison. Regional treatment response, ΔR(r), was calculated as the difference in regional gas distribution (R[r] = ratio of inhaled gas to total volume of a voxel when normalized for lung inflation volume) before and after intervention. A voxelwise activation threshold from the variability of the baseline images was applied to ΔR(r) maps. The summed global treatment response map (ΔR net ) was then used as a global lung index for comparison with metrics of bronchodilator response measured by using spirometry and the global imaging metric percentage ventilated volume (%VV). Results ΔR net showed significant correlation (P treatment effect was detected with all metrics; however, ΔR net showed a lower intersubject coefficient of variation (64%) than all of the other tests (coefficient of variation, ≥99%). Conclusion TRM provides regional quantitative information on changes in inhaled gas ventilation in response to therapy. This method could be used as a sensitive regional outcome metric for novel respiratory interventions. © RSNA, 2017 Online supplemental material is available for this article.

Brain tissues atrophy is not always the best structural biomarker of physiological aging: A multimodal cross-sectional study.

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Cherubini, Andrea; Caligiuri, Maria Eugenia; Péran, Patrice; Sabatini, Umberto; Cosentino, Carlo; Amato, Francesco

2015-01-01

This study presents a voxel-based multiple regression analysis of different magnetic resonance image modalities, including anatomical T1-weighted, T2* relaxometry, and diffusion tensor imaging. Quantitative parameters sensitive to complementary brain tissue alterations, including morphometric atrophy, mineralization, microstructural damage, and anisotropy loss, were compared in a linear physiological aging model in 140 healthy subjects (range 20-74 years). The performance of different predictors and the identification of the best biomarker of age-induced structural variation were compared without a priori anatomical knowledge. The best quantitative predictors in several brain regions were iron deposition and microstructural damage, rather than macroscopic tissue atrophy. Age variations were best resolved with a combination of markers, suggesting that multiple predictors better capture age-induced tissue alterations. These findings highlight the importance of a combined evaluation of multimodal biomarkers for the study of aging and point to a number of novel applications for the method described.

Magnetic Resonance-based Motion Correction for Quantitative PET in Simultaneous PET-MR Imaging.

Science.gov (United States)

Rakvongthai, Yothin; El Fakhri, Georges

2017-07-01

Motion degrades image quality and quantitation of PET images, and is an obstacle to quantitative PET imaging. Simultaneous PET-MR offers a tool that can be used for correcting the motion in PET images by using anatomic information from MR imaging acquired concurrently. Motion correction can be performed by transforming a set of reconstructed PET images into the same frame or by incorporating the transformation into the system model and reconstructing the motion-corrected image. Several phantom and patient studies have validated that MR-based motion correction strategies have great promise for quantitative PET imaging in simultaneous PET-MR. Copyright © 2017 Elsevier Inc. All rights reserved.

Diffusion-Weighted Magnetic Resonance Imaging as a Cancer Biomarker: Consensus and Recommendations

Directory of Open Access Journals (Sweden)

Anwar R. Padhani

2009-02-01

Full Text Available On May 3, 2008, a National Cancer Institute (NCI-sponsored open consensus conference was held in Toronto, Ontario, Canada, during the 2008 International Society for Magnetic Resonance in Medicine Meeting. Approximately 100 experts and stakeholders summarized the current understanding of diffusion-weighted magnetic resonance imaging (DW-MRI and reached consensus on the use of DW-MRI as a cancer imaging biomarker. DW-MRI should be tested as an imaging biomarker in the context of well-defined clinical trials, by adding DW-MRI to existing NCI-sponsored trials, particularly those with tissue sampling or survival indicators. Where possible, DW-MRI measurements should be compared with histologic indices including cellularity and tissue response. There is a need for tissue equivalent diffusivity phantoms; meanwhile, simple fluid-filled phantoms should be used. Monoexponential assessments of apparent diffusion coefficient values should use two b values (> 100 and between 500 and 1000 mm2/sec depending on the application. Free breathing with multiple acquisitions is superior to complex gating techniques. Baseline patient reproducibility studies should be part of study designs. Both region of interest and histogram analysis of apparent diffusion coefficient measurements should be obtained. Standards for measurement, analysis, and display are needed. Annotated data from validation studies (along with outcome measures should be made publicly available. Magnetic resonance imaging vendors should be engaged in this process. The NCI should establish a task force of experts (physicists, radiologists, and oncologists to plan, organize technical aspects, and conduct pilot trials. The American College of Radiology Imaging Network infrastructure may be suitable for these purposes. There is an extraordinary opportunity for DW-MRI to evolve into a clinically valuable imaging tool, potentially important for drug development.

Evaluating biomarkers for prognostic enrichment of clinical trials.

Science.gov (United States)

Kerr, Kathleen F; Roth, Jeremy; Zhu, Kehao; Thiessen-Philbrook, Heather; Meisner, Allison; Wilson, Francis Perry; Coca, Steven; Parikh, Chirag R

2017-12-01

A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment. We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency. We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform. In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

Automatic segmentation of lumbar vertebrae in CT images

Science.gov (United States)

Kulkarni, Amruta; Raina, Akshita; Sharifi Sarabi, Mona; Ahn, Christine S.; Babayan, Diana; Gaonkar, Bilwaj; Macyszyn, Luke; Raghavendra, Cauligi

2017-03-01

Lower back pain is one of the most prevalent disorders in the developed/developing world. However, its etiology is poorly understood and treatment is often determined subjectively. In order to quantitatively study the emergence and evolution of back pain, it is necessary to develop consistently measurable markers for pathology. Imaging based measures offer one solution to this problem. The development of imaging based on quantitative biomarkers for the lower back necessitates automated techniques to acquire this data. While the problem of segmenting lumbar vertebrae has been addressed repeatedly in literature, the associated problem of computing relevant biomarkers on the basis of the segmentation has not been addressed thoroughly. In this paper, we propose a Random-Forest based approach that learns to segment vertebral bodies in CT images followed by a biomarker evaluation framework that extracts vertebral heights and widths from the segmentations obtained. Our dataset consists of 15 CT sagittal scans obtained from General Electric Healthcare. Our main approach is divided into three parts: the first stage is image pre-processing which is used to correct for variations in illumination across all the images followed by preparing the foreground and background objects from images; the next stage is Machine Learning using Random-Forests, which distinguishes the interest-point vectors between foreground or background; and the last step is image post-processing, which is crucial to refine the results of classifier. The Dice coefficient was used as a statistical validation metric to evaluate the performance of our segmentations with an average value of 0.725 for our dataset.

MO-AB-BRA-05: [18F]NaF PET/CT Imaging Biomarkers in Metastatic Prostate Cancer

Energy Technology Data Exchange (ETDEWEB)

Harmon, S; Perk, T; Lin, C; Eickhoff, J; Perlman, S; Liu, G; Jeraj, R [University of Wisconsin Madison, Madison, WI (United States); Choyke, P; Dahut, W; Apolo, A [National Cancer Institute at the National Institutes of Health, Bethesda, MD (United States); Humm, J; Larson, S; Morris, MJ [Memorial Sloan-Kettering Cancer Center, New York, NY (United States)

2016-06-15

Purpose: Clinical use of {sup 18}F-Sodium Fluoride (NaF) PET/CT in metastatic settings often lacks technology to quantitatively measure full disease dynamics due to high tumor burden. This study assesses radiomics-based extraction of NaF PET/CT measures, including global metrics of overall burden and local metrics of disease heterogeneity, in metastatic prostate cancer for correlation to clinical outcomes. Methods: Fifty-six metastatic Castrate-Resistant Prostate Cancer (mCRPC) patients had NaF PET/CT scans performed at baseline and three cycles into chemotherapy (N=16) or androgen-receptor (AR) inhibitors (N=39). A novel technology, Quantitative Total Bone Imaging (QTBI), was used for analysis. Employing hybrid PET/CT segmentation and articulated skeletal-registration, QTBI allows for response assessment of individual lesions. Various SUV metrics were extracted from each lesion (iSUV). Global metrics were extracted from composite lesion-level statistics for each patient (pSUV). Proportion of detected lesions and those with significant response (%-increase or %-decrease) was calculated for each patient based on test-retest limits for iSUV metrics. Cox proportional hazard regression analyses were conducted between imaging metrics and progression-free survival (PFS). Results: Functional burden (pSUV{sub total}) assessed mid-treatment was the strongest univariate predictor of PFS (HR=2.03; p<0.0001). Various global metrics outperformed baseline clinical markers, including fraction of skeletal burden, mean uptake (pSUV{sub mean}), and heterogeneity of average lesion uptake (pSUV{sub hetero}). Of 43 patients with paired baseline/mid-treatment imaging, 40 showed heterogeneity in lesion-level response, containing populations of lesions with both increasing/decreasing metrics. Proportion of lesions with significantly increasing iSUV{sub mean} was highly predictive of clinical PFS (HR=2.0; p=0.0002). Patients exhibiting higher proportion of lesions with decreasing i

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

Science.gov (United States)

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

Prognostic biomarkers in osteoarthritis

Science.gov (United States)

Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

2013-01-01

Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

Quantitative assessment of dynamic PET imaging data in cancer imaging.

Science.gov (United States)

Muzi, Mark; O'Sullivan, Finbarr; Mankoff, David A; Doot, Robert K; Pierce, Larry A; Kurland, Brenda F; Linden, Hannah M; Kinahan, Paul E

2012-11-01

Clinical imaging in positron emission tomography (PET) is often performed using single-time-point estimates of tracer uptake or static imaging that provides a spatial map of regional tracer concentration. However, dynamic tracer imaging can provide considerably more information about in vivo biology by delineating both the temporal and spatial pattern of tracer uptake. In addition, several potential sources of error that occur in static imaging can be mitigated. This review focuses on the application of dynamic PET imaging to measuring regional cancer biologic features and especially in using dynamic PET imaging for quantitative therapeutic response monitoring for cancer clinical trials. Dynamic PET imaging output parameters, particularly transport (flow) and overall metabolic rate, have provided imaging end points for clinical trials at single-center institutions for years. However, dynamic imaging poses many challenges for multicenter clinical trial implementations from cross-center calibration to the inadequacy of a common informatics infrastructure. Underlying principles and methodology of PET dynamic imaging are first reviewed, followed by an examination of current approaches to dynamic PET image analysis with a specific case example of dynamic fluorothymidine imaging to illustrate the approach. Copyright © 2012 Elsevier Inc. All rights reserved.

Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

Science.gov (United States)

Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.

1999-01-01

The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

Quantitative imaging of bilirubin by photoacoustic microscopy

Science.gov (United States)

Zhou, Yong; Zhang, Chi; Yao, Da-Kang; Wang, Lihong V.

2013-03-01

Noninvasive detection of both bilirubin concentration and its distribution is important for disease diagnosis. Here we implemented photoacoustic microscopy (PAM) to detect bilirubin distribution. We first demonstrate that our PAM system can measure the absorption spectra of bilirubin and blood. We also image bilirubin distributions in tissuemimicking samples, both without and with blood mixed. Our results show that PAM has the potential to quantitatively image bilirubin in vivo for clinical applications.

Quantitative magnetic resonance imaging in limb-girdle muscular dystrophy 2I

DEFF Research Database (Denmark)

Willis, Tracey A; Hollingsworth, Kieren G; Coombs, Anna

2014-01-01

-related protein (FKRP) gene were recruited. In each patient, T1-weighted (T1w) imaging was assessed by qualitative grading for 15 individual lower limb muscles and quantitative Dixon imaging was analysed on 14 individual lower limb muscles by region of interest analysis. We described the pattern and appearance......) that the quantitative Dixon technique is an objective quantitative marker of disease and (ii) new observations of gender specific patterns of muscle involvement in LGMD2I....

Alzheimer's Disease and Glaucoma: Imaging the Biomarkers of Neurodegenerative Disease

Directory of Open Access Journals (Sweden)

Denise A. Valenti

2010-01-01

Full Text Available Imaging through the visual system in Alzheimer's disease, with the technology currently in widespread use for the diagnosis and management of eye disease such as glaucoma and macular degeneration, is proving to be promising. In vivo cross-section imaging during an annual comprehensive eye exam has been available for a decade for glaucoma and macular degeneration, and this same imaging, using Optical Coherence Tomography, has been demonstrated to show deficits specific to AD and mild cognitive impairment. These deficits are in the form of nerve fiber layer tissue drop out in the retina and optic nerve. The retrograde loss of nerve fiber layer tissue in the retina and optic nerve may be an early biomarker of AD, and these deficits in the nerve fiber layer of the retina and optic nerve may be the earliest sign of AD, even prior to damage to the hippocampal region that impacts memory.

The Digital Image Processing And Quantitative Analysis In Microscopic Image Characterization

International Nuclear Information System (INIS)

Ardisasmita, M. Syamsa

2000-01-01

Many electron microscopes although have produced digital images, but not all of them are equipped with a supporting unit to process and analyse image data quantitatively. Generally the analysis of image has to be made visually and the measurement is realized manually. The development of mathematical method for geometric analysis and pattern recognition, allows automatic microscopic image analysis with computer. Image processing program can be used for image texture and structure periodic analysis by the application of Fourier transform. Because the development of composite materials. Fourier analysis in frequency domain become important for measure the crystallography orientation. The periodic structure analysis and crystal orientation are the key to understand many material properties like mechanical strength. stress, heat conductivity, resistance, capacitance and other material electric and magnetic properties. In this paper will be shown the application of digital image processing in microscopic image characterization and analysis in microscopic image

SPECT and PET Serve as Molecular Imaging Techniques and in Vivo Biomarkers for Brain Metastases

Science.gov (United States)

Palumbo, Barbara; Buresta, Tommaso; Nuvoli, Susanna; Spanu, Angela; Schillaci, Orazio; Fravolini, Mario Luca; Palumbo, Isabella

2014-01-01

Nuclear medicine techniques (single photon emission computerized tomography, SPECT, and positron emission tomography, PET) represent molecular imaging tools, able to provide in vivo biomarkers of different diseases. To investigate brain tumours and metastases many different radiopharmaceuticals imaged by SPECT and PET can be used. In this review the main and most promising radiopharmaceuticals available to detect brain metastases are reported. Furthermore the diagnostic contribution of the combination of SPECT and PET data with radiological findings (magnetic resonance imaging, MRI) is discussed. PMID:24897023

Quantitative imaging of subcellular metabolism with stable isotopes and multi-isotope imaging mass spectrometry

Science.gov (United States)

Steinhauser, Matthew L.; Lechene, Claude P.

2014-01-01

Multi-isotope imaging mass spectrometry (MIMS) is the quantitative imaging of stable isotope labels in cells with a new type of secondary ion mass spectrometer (NanoSIMS). The power of the methodology is attributable to (i) the immense advantage of using non-toxic stable isotope labels, (ii) high resolution imaging that approaches the resolution of usual transmission electron microscopy and (iii) the precise quantification of label down to 1 part-per-million and spanning several orders of magnitude. Here we review the basic elements of MIMS and describe new applications of MIMS to the quantitative study of metabolic processes including protein and nucleic acid synthesis in model organisms ranging from microbes to humans. PMID:23660233

Magnetic Resonance Imaging Biomarkers to Assess Substantia Nigra Damage in Idiopathic Rapid Eye Movement Sleep Behavior Disorder.

Science.gov (United States)

Pyatigorskaya, Nadya; Gaurav, Rahul; Arnaldi, Dario; Leu-Semenescu, Smaranda; Yahia-Cherif, Lydia; Valabregue, Romain; Vidailhet, Marie; Arnulf, Isabelle; Lehéricy, Stephane

2017-11-01

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is considered to be a prodromal stage of Parkinson's disease (PD). At PD onset, 40 to 70% of the dopaminergic neurons in the substantia nigra (SN) are already lost. Thus, milder SN damage is expected in participants with iRBD. We aimed to quantify SN damage in participants with iRBD using multimodal magnetic resonance imaging (MRI) and to determine biomarker efficacy in preclinical Parkinsonism. Nineteen participants with iRBD and 18 controls underwent 3-Tesla MRI, including diffusion tensor imaging, neuromelanin (NM)-sensitive imaging, and T2* mapping. Regions of interest in the SN area were drawn in NM-sensitive and T2-weighted images. The volume and normalized signal intensity in NM-sensitive images, R2*, and diffusion tensor measures were quantified in the SN. Additionally, two raters performed visual analysis of the SN using the NM-sensitive images. Participants with iRBD showed a reduction in the NM-sensitive volume and signal intensity and a decrease in fractional anisotropy (FA) versus controls, but showed no differences in axial, radial, or mean diffusivity or in R2*. For NM-sensitive volume and signal intensity, the receiver operating characteristic analysis discriminated between participants with iRBD and controls with a diagnostic accuracy of 0.86 and 0.79, respectively, whereas the accuracy was 0.77 for FA. The three biomarkers had a combined accuracy of 0.92. The fraction of participants correctly characterized by visual assessment was 0.81. NM-sensitive imaging and FA allowed for the detection of SN damage in participants with iRBD with good diagnostic accuracy. These measures may represent valuable biomarkers for prodromal Parkinsonism. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Micro-computer system for quantitative image analysis of damage microstructure

International Nuclear Information System (INIS)

Kohyama, A.; Kohno, Y.; Satoh, K.; Igata, N.

1984-01-01

Quantitative image analysis of radiation induced damage microstructure is very important in evaluating material behaviors in radiation environment. But, quite a few improvement have been seen in quantitative analysis of damage microstructure in these decades. The objective of this work is to develop new system for quantitative image analysis of damage microstructure which could improve accuracy and efficiency of data sampling and processing and could enable to get new information about mutual relations among dislocations, precipitates, cavities, grain boundaries, etc. In this system, data sampling is done with X-Y digitizer. The cavity microstructure in dual-ion irradiated 316 SS is analyzed and the effectiveness of this system is discussed. (orig.)

Quantitative imaging of protein targets in the human brain with PET

International Nuclear Information System (INIS)

Gunn, Roger N; Slifstein, Mark; Searle, Graham E; Price, Julie C

2015-01-01

PET imaging of proteins in the human brain with high affinity radiolabelled molecules has a history stretching back over 30 years. During this period the portfolio of protein targets that can be imaged has increased significantly through successes in radioligand discovery and development. This portfolio now spans six major categories of proteins; G-protein coupled receptors, membrane transporters, ligand gated ion channels, enzymes, misfolded proteins and tryptophan-rich sensory proteins. In parallel to these achievements in radiochemical sciences there have also been significant advances in the quantitative analysis and interpretation of the imaging data including the development of methods for image registration, image segmentation, tracer compartmental modeling, reference tissue kinetic analysis and partial volume correction. In this review, we analyze the activity of the field around each of the protein targets in order to give a perspective on the historical focus and the possible future trajectory of the field. The important neurobiology and pharmacology is introduced for each of the six protein classes and we present established radioligands for each that have successfully transitioned to quantitative imaging in humans. We present a standard quantitative analysis workflow for these radioligands which takes the dynamic PET data, associated blood and anatomical MRI data as the inputs to a series of image processing and bio-mathematical modeling steps before outputting the outcome measure of interest on either a regional or parametric image basis. The quantitative outcome measures are then used in a range of different imaging studies including tracer discovery and development studies, cross sectional studies, classification studies, intervention studies and longitudinal studies. Finally we consider some of the confounds, challenges and subtleties that arise in practice when trying to quantify and interpret PET neuroimaging data including motion artifacts

Quantitative imaging of protein targets in the human brain with PET

Science.gov (United States)

Gunn, Roger N.; Slifstein, Mark; Searle, Graham E.; Price, Julie C.

2015-11-01

PET imaging of proteins in the human brain with high affinity radiolabelled molecules has a history stretching back over 30 years. During this period the portfolio of protein targets that can be imaged has increased significantly through successes in radioligand discovery and development. This portfolio now spans six major categories of proteins; G-protein coupled receptors, membrane transporters, ligand gated ion channels, enzymes, misfolded proteins and tryptophan-rich sensory proteins. In parallel to these achievements in radiochemical sciences there have also been significant advances in the quantitative analysis and interpretation of the imaging data including the development of methods for image registration, image segmentation, tracer compartmental modeling, reference tissue kinetic analysis and partial volume correction. In this review, we analyze the activity of the field around each of the protein targets in order to give a perspective on the historical focus and the possible future trajectory of the field. The important neurobiology and pharmacology is introduced for each of the six protein classes and we present established radioligands for each that have successfully transitioned to quantitative imaging in humans. We present a standard quantitative analysis workflow for these radioligands which takes the dynamic PET data, associated blood and anatomical MRI data as the inputs to a series of image processing and bio-mathematical modeling steps before outputting the outcome measure of interest on either a regional or parametric image basis. The quantitative outcome measures are then used in a range of different imaging studies including tracer discovery and development studies, cross sectional studies, classification studies, intervention studies and longitudinal studies. Finally we consider some of the confounds, challenges and subtleties that arise in practice when trying to quantify and interpret PET neuroimaging data including motion artifacts

Quantitative subsurface analysis using frequency modulated thermal wave imaging

Science.gov (United States)

Subhani, S. K.; Suresh, B.; Ghali, V. S.

2018-01-01

Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

Radiogenomics of hepatocellular carcinoma: multiregion analysis-based identification of prognostic imaging biomarkers by integrating gene data—a preliminary study

Science.gov (United States)

Xia, Wei; Chen, Ying; Zhang, Rui; Yan, Zhuangzhi; Zhou, Xiaobo; Zhang, Bo; Gao, Xin

2018-02-01

Our objective was to identify prognostic imaging biomarkers for hepatocellular carcinoma in contrast-enhanced computed tomography (CECT) with biological interpretations by associating imaging features and gene modules. We retrospectively analyzed 371 patients who had gene expression profiles. For the 38 patients with CECT imaging data, automatic intra-tumor partitioning was performed, resulting in three spatially distinct subregions. We extracted a total of 37 quantitative imaging features describing intensity, geometry, and texture from each subregion. Imaging features were selected after robustness and redundancy analysis. Gene modules acquired from clustering were chosen for their prognostic significance. By constructing an association map between imaging features and gene modules with Spearman rank correlations, the imaging features that significantly correlated with gene modules were obtained. These features were evaluated with Cox’s proportional hazard models and Kaplan-Meier estimates to determine their prognostic capabilities for overall survival (OS). Eight imaging features were significantly correlated with prognostic gene modules, and two of them were associated with OS. Among these, the geometry feature volume fraction of the subregion, which was significantly correlated with all prognostic gene modules representing cancer-related interpretation, was predictive of OS (Cox p  =  0.022, hazard ratio  =  0.24). The texture feature cluster prominence in the subregion, which was correlated with the prognostic gene module representing lipid metabolism and complement activation, also had the ability to predict OS (Cox p  =  0.021, hazard ratio  =  0.17). Imaging features depicting the volume fraction and textural heterogeneity in subregions have the potential to be predictors of OS with interpretable biological meaning.

SPECT and PET Serve as Molecular Imaging Techniques and in Vivo Biomarkers for Brain Metastases

Directory of Open Access Journals (Sweden)

Barbara Palumbo

2014-06-01

Full Text Available Nuclear medicine techniques (single photon emission computerized tomography, SPECT, and positron emission tomography, PET represent molecular imaging tools, able to provide in vivo biomarkers of different diseases. To investigate brain tumours and metastases many different radiopharmaceuticals imaged by SPECT and PET can be used. In this review the main and most promising radiopharmaceuticals available to detect brain metastases are reported. Furthermore the diagnostic contribution of the combination of SPECT and PET data with radiological findings (magnetic resonance imaging, MRI is discussed.

Quantitative Radiomics System Decoding the Tumor Phenotype | Informatics Technology for Cancer Research (ITCR)

Science.gov (United States)

Our goal is to construct a publicly available computational radiomics system for the objective and automated extraction of quantitative imaging features that we believe will yield biomarkers of greater prognostic value compared with routinely extracted descriptors of tumor size. We will create a generalized, open, portable, and extensible radiomics platform that is widely applicable across cancer types and imaging modalities and describe how we will use lung and head and neck cancers as models to validate our developments.

FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0

International Nuclear Information System (INIS)

Boellaard, Ronald; Hoekstra, Otto S.; Delgado-Bolton, Roberto; Oyen, Wim J.G.; Visser, Eric; Giammarile, Francesco; Tatsch, Klaus; Eschner, Wolfgang; Verzijlbergen, Fred J.; Barrington, Sally F.; Pike, Lucy C.; Weber, Wolfgang A.; Stroobants, Sigrid; Delbeke, Dominique; Donohoe, Kevin J.; Holbrook, Scott; Graham, Michael M.; Testanera, Giorgio; Chiti, Arturo; Zijlstra, Josee; Hoekstra, Corneline J.; Pruim, Jan; Willemsen, Antoon; Arends, Bertjan; Kotzerke, Joerg; Bockisch, Andreas; Beyer, Thomas; Krause, Bernd J.

2015-01-01

The purpose of these guidelines is to assist physicians in recommending, performing, interpreting and reporting the results of FDG PET/CT for oncological imaging of adult patients. PET is a quantitative imaging technique and therefore requires a common quality control (QC)/quality assurance (QA) procedure to maintain the accuracy and precision of quantitation. Repeatability and reproducibility are two essential requirements for any quantitative measurement and/or imaging biomarker. Repeatability relates to the uncertainty in obtaining the same result in the same patient when he or she is examined more than once on the same system. However, imaging biomarkers should also have adequate reproducibility, i.e. the ability to yield the same result in the same patient when that patient is examined on different systems and at different imaging sites. Adequate repeatability and reproducibility are essential for the clinical management of patients and the use of FDG PET/CT within multicentre trials. A common standardised imaging procedure will help promote the appropriate use of FDG PET/CT imaging and increase the value of publications and, therefore, their contribution to evidence-based medicine. Moreover, consistency in numerical values between platforms and institutes that acquire the data will potentially enhance the role of semiquantitative and quantitative image interpretation. Precision and accuracy are additionally important as FDG PET/CT is used to evaluate tumour response as well as for diagnosis, prognosis and staging. Therefore both the previous and these new guidelines specifically aim to achieve standardised uptake value harmonisation in multicentre settings. (orig.)

FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0

Energy Technology Data Exchange (ETDEWEB)

Boellaard, Ronald; Hoekstra, Otto S. [VU University Medical Centre, Department of Radiology and Nuclear Medicine, Amsterdam (Netherlands); Delgado-Bolton, Roberto [University of La Rioja, Department of Diagnostic Imaging (Radiology) and Nuclear Medicine, San Pedro Hospital and Centre for Biomedical Research of La Rioja (CIBIR), Logrono, La Rioja (Spain); Oyen, Wim J.G.; Visser, Eric [Radboud University Nijmegen Medical Centre, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Giammarile, Francesco [Centre Hospitalier Universitaire de Lyon, Department of Nuclear Medicine, Lyon (France); Tatsch, Klaus [Municipal Hospital Karlsruhe Inc., Department of Nuclear Medicine, Karlsruhe (Germany); Eschner, Wolfgang [University of Cologne, Department of Nuclear Medicine, Cologne (Germany); Verzijlbergen, Fred J. [Erasmus Medical Center, Department of Nuclear Medicine, Rotterdam (Netherlands); Barrington, Sally F.; Pike, Lucy C. [King' s College London, King' s Health Partners, PET Imaging Centre, St Thomas' Hospital, Division of Imaging Sciences and Biomedical Engineering, London (United Kingdom); Weber, Wolfgang A. [Memorial Sloan Kettering Center, Department of Radiology, New York, NY (United States); Stroobants, Sigrid [Antwerp University Hospital, Department of Nuclear Medicine, Antwerp (Belgium); Delbeke, Dominique [Vanderbilt University Medical Center, Department of Radiology and Radiological Sciences, Nashville, TN (United States); Donohoe, Kevin J. [Beth Israel Deaconess Medical Center, Boston, MA (United States); Holbrook, Scott [Invivo Molecular Imaging LLC, Gray, TN (United States); Graham, Michael M. [University of Iowa, Department of Radiology, Iowa City, IA (United States); Testanera, Giorgio; Chiti, Arturo [Humanitas Clinical and Research Center, Department of Nuclear Medicine, Rozzano, MI (Italy); Zijlstra, Josee [VU University Medical Centre, Department of Hematology, Amsterdam (Netherlands); Hoekstra, Corneline J. [Jeroen Bosch Hospital, Department of Nuclear Medicine, Den Bosch (Netherlands); Pruim, Jan; Willemsen, Antoon [University Medical Centre Groningen, Department of Nuclear Medicine and Molecular Imaging, Groningen (Netherlands); Arends, Bertjan [Catharina Hospital, Department of Clinical Physics, Eindhoven (Netherlands); Kotzerke, Joerg [University Hospital Dresden, Clinic and Outpatient Clinic for Nuclear Medicine, Dresden (Germany); Bockisch, Andreas [University Hospital Essen, Clinic for Nuclear Medicine, Essen (Germany); Beyer, Thomas [Medical University of Vienna, Centre for Medical Physics and Biomedical Engineering, Vienna (Austria); Krause, Bernd J. [University Hospital Rostock, Department of Nuclear Medicine, Rostock (Germany)

2014-12-02

The purpose of these guidelines is to assist physicians in recommending, performing, interpreting and reporting the results of FDG PET/CT for oncological imaging of adult patients. PET is a quantitative imaging technique and therefore requires a common quality control (QC)/quality assurance (QA) procedure to maintain the accuracy and precision of quantitation. Repeatability and reproducibility are two essential requirements for any quantitative measurement and/or imaging biomarker. Repeatability relates to the uncertainty in obtaining the same result in the same patient when he or she is examined more than once on the same system. However, imaging biomarkers should also have adequate reproducibility, i.e. the ability to yield the same result in the same patient when that patient is examined on different systems and at different imaging sites. Adequate repeatability and reproducibility are essential for the clinical management of patients and the use of FDG PET/CT within multicentre trials. A common standardised imaging procedure will help promote the appropriate use of FDG PET/CT imaging and increase the value of publications and, therefore, their contribution to evidence-based medicine. Moreover, consistency in numerical values between platforms and institutes that acquire the data will potentially enhance the role of semiquantitative and quantitative image interpretation. Precision and accuracy are additionally important as FDG PET/CT is used to evaluate tumour response as well as for diagnosis, prognosis and staging. Therefore both the previous and these new guidelines specifically aim to achieve standardised uptake value harmonisation in multicentre settings. (orig.)

Realizing the quantitative potential of the radioisotope image

International Nuclear Information System (INIS)

Brown, N.J.G.; Britton, K.E.; Cruz, F.R.

1977-01-01

The sophistication and accuracy of a clinical strategy depends on the accuracy of the results of the tests used. When numerical values are given in the test report powerful clinical strategies can be developed. The eye is well able to perceive structures in a high-quality grey-scale image. However, the degree of difference in density between two points cannot be estimated quantitatively by eye. This creates a problem particularly when there is only a small difference between the count-rate at a suspicious point or region and the count-rate to be expected there if the image were normal. To resolve this problem methods of quantitation of the amplitude of a feature, defined as the difference between the observed and expected values at the region of the feature, have been developed. The eye can estimate the frequency of light entering it very accurately (perceived as colour). Thus, if count-rate data are transformed into colour in a systematic way then information about realtive count-rate can be perceived. A computer-driven, interactive colour display system is used in which the count-rate range of each colour is computed as a percentage of a reference count-rate value. This can be used to obtain quantitative estimates of the amplitude of an image feature. The application of two methods to normal and pathological data are described and the results discussed. (author)

Quantitative sub-surface and non-contact imaging using scanning microwave microscopy

International Nuclear Information System (INIS)

Gramse, Georg; Kasper, Manuel; Hinterdorfer, Peter; Brinciotti, Enrico; Rankl, Christian; Kienberger, Ferry; Lucibello, Andrea; Marcelli, Romolo; Patil, Samadhan B.; Giridharagopal, Rajiv

2015-01-01

The capability of scanning microwave microscopy for calibrated sub-surface and non-contact capacitance imaging of silicon (Si) samples is quantitatively studied at broadband frequencies ranging from 1 to 20 GHz. Calibrated capacitance images of flat Si test samples with varying dopant density (10 15 –10 19 atoms cm −3 ) and covered with dielectric thin films of SiO 2 (100–400 nm thickness) are measured to demonstrate the sensitivity of scanning microwave microscopy (SMM) for sub-surface imaging. Using standard SMM imaging conditions the dopant areas could still be sensed under a 400 nm thick oxide layer. Non-contact SMM imaging in lift-mode and constant height mode is quantitatively demonstrated on a 50 nm thick SiO 2 test pad. The differences between non-contact and contact mode capacitances are studied with respect to the main parameters influencing the imaging contrast, namely the probe tip diameter and the tip–sample distance. Finite element modelling was used to further analyse the influence of the tip radius and the tip–sample distance on the SMM sensitivity. The understanding of how the two key parameters determine the SMM sensitivity and quantitative capacitances represents an important step towards its routine application for non-contact and sub-surface imaging. (paper)

Role of image analysis in quantitative characterisation of nuclear fuel materials

International Nuclear Information System (INIS)

Dubey, J.N.; Rao, T.S.; Pandey, V.D.; Majumdar, S.

2005-01-01

Image analysis is one of the important techniques, widely used for materials characterization. It provides the quantitative estimation of the microstructural features present in the material. This information is very much valuable for finding out the criteria for taking up the fuel for high burn up. Radiometallurgy Division has been carrying out development and fabrication of plutonium related fuels for different type of reactors viz. Purnima, Fast Breeder Test Reactor (FBTR), Prototype Fast Breeder Reactor (PFBR), Boiling Water Reactor (BWR), Advanced Heavy Water Reactor (AHWR), Pressurised Heavy Water Reactor (PHWR) and KAMINI Reactor. Image analysis has been carried out on microstructures of PHWR, AHWR, FBTR and KAMINI fuels. Samples were prepared as per standard ASTM metallographic procedure. Digital images of the microstructure of these specimens were obtained using CCD camera, attached to the optical microscope. These images are stores on computer and used for detection and analysis of features of interest with image analysis software. Quantitative image analysis technique has been standardised and used for finding put type of the porosity, its size, shape and distribution in the above sintered oxide and carbide fuels. This technique has also been used for quantitative estimation of different phases present in KAMINI fuel. Image analysis results have been summarised and presented in this paper. (author)

Developments in Dynamic Analysis for quantitative PIXE true elemental imaging

International Nuclear Information System (INIS)

Ryan, C.G.

2001-01-01

Dynamic Analysis (DA) is a method for projecting quantitative major and trace element images from PIXE event data-streams (off-line or on-line) obtained using the Nuclear Microprobe. The method separates full elemental spectral signatures to produce images that strongly reject artifacts due to overlapping elements, detector effects (such as escape peaks and tailing) and background. The images are also quantitative, stored in ppm-charge units, enabling images to be directly interrogated for the concentrations of all elements in areas of the images. Recent advances in the method include the correction for changing X-ray yields due to varying sample compositions across the image area and the construction of statistical variance images. The resulting accuracy of major element concentrations extracted directly from these images is better than 3% relative as determined from comparisons with electron microprobe point analysis. These results are complemented by error estimates derived from the variance images together with detection limits. This paper provides an update of research on these issues, introduces new software designed to make DA more accessible, and illustrates the application of the method to selected geological problems.

Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology.

Science.gov (United States)

Limkin, E J; Sun, R; Dercle, L; Zacharaki, E I; Robert, C; Reuzé, S; Schernberg, A; Paragios, N; Deutsch, E; Ferté, C

2017-06-01

Medical image processing and analysis (also known as Radiomics) is a rapidly growing discipline that maps digital medical images into quantitative data, with the end goal of generating imaging biomarkers as decision support tools for clinical practice. The use of imaging data from routine clinical work-up has tremendous potential in improving cancer care by heightening understanding of tumor biology and aiding in the implementation of precision medicine. As a noninvasive method of assessing the tumor and its microenvironment in their entirety, radiomics allows the evaluation and monitoring of tumor characteristics such as temporal and spatial heterogeneity. One can observe a rapid increase in the number of computational medical imaging publications-milestones that have highlighted the utility of imaging biomarkers in oncology. Nevertheless, the use of radiomics as clinical biomarkers still necessitates amelioration and standardization in order to achieve routine clinical adoption. This Review addresses the critical issues to ensure the proper development of radiomics as a biomarker and facilitate its implementation in clinical practice. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Ultrasound introscopic image quantitative characteristics for medical diagnosis

Science.gov (United States)

Novoselets, Mikhail K.; Sarkisov, Sergey S.; Gridko, Alexander N.; Tcheban, Anatoliy K.

1993-09-01

The results on computer aided extraction of quantitative characteristics (QC) of ultrasound introscopic images for medical diagnosis are presented. Thyroid gland (TG) images of Chernobil Accident sufferers are considered. It is shown that TG diseases can be associated with some values of selected QCs of random echo distribution in the image. The possibility of these QCs usage for TG diseases recognition in accordance with calculated values is analyzed. The role of speckle noise elimination in the solution of the problem on TG diagnosis is considered too.

On the benefit of the negative-spherical-aberration imaging technique for quantitative HRTEM

International Nuclear Information System (INIS)

Jia, C.L.; Houben, L.; Thust, A.; Barthel, J.

2010-01-01

Employing an aberration corrector in a high-resolution transmission electron microscope, the spherical aberration C S can be tuned to negative values, resulting in a novel imaging technique, which is called the negative C S imaging (NCSI) technique. The image contrast obtained with the NCSI technique is compared quantitatively with the image contrast formed with the traditional positive C S imaging (PCSI) technique. For the case of thin objects negative C S images are superior to positive C S images concerning the magnitude of the obtained contrast, which is due to constructive rather than destructive superposition of fundamental contrast contributions. As a consequence, the image signal obtained with a negative spherical aberration is significantly more robust against noise caused by amorphous surface layers, resulting in a measurement precision of atomic positions which is by a factor of 2-3 better at an identical noise level. The quantitative comparison of the two alternative C S -corrected imaging modes shows that the NCSI mode yields significantly more precise results in quantitative high-resolution transmission electron microscopy of thin objects than the traditional PCSI mode.

Quantitative label-free sperm imaging by means of transport of intensity

Science.gov (United States)

Poola, Praveen Kumar; Pandiyan, Vimal Prabhu; Jayaraman, Varshini; John, Renu

2016-03-01

Most living cells are optically transparent which makes it difficult to visualize them under bright field microscopy. Use of contrast agents or markers and staining procedures are often followed to observe these cells. However, most of these staining agents are toxic and not applicable for live cell imaging. In the last decade, quantitative phase imaging has become an indispensable tool for morphological characterization of the phase objects without any markers. In this paper, we report noninterferometric quantitative phase imaging of live sperm cells by solving transport of intensity equations with recorded intensity measurements along optical axis on a commercial bright field microscope.

Quantitative OCT and MRI biomarkers for the differentiation of cartilage degeneration

International Nuclear Information System (INIS)

Nebelung, Sven; Brill, Nicolai; Tingart, Markus; Jahr, Holger; Pufe, Thomas; Kuhl, Christiane; Truhn, Daniel

2016-01-01

To evaluate the usefulness of quantitative parameters obtained by optical coherence tomography (OCT) and magnetic resonance imaging (MRI) in the comprehensive assessment of human articular cartilage degeneration. Human osteochondral samples of variable degeneration (n = 45) were obtained from total knee replacements and assessed by MRI sequences measuring T1, T1ρ, T2 and T2* relaxivity and by OCT-based quantification of irregularity (OII, optical irregularity index), homogeneity (OHI, optical homogeneity index) and attenuation (OAI, optical attenuation index). Samples were also assessed macroscopically (Outerbridge classification) and histologically (Mankin classification) as grade-0 (Mankin scores 0-4)/grade-I (scores 5-8)/grade-II (scores 9-10)/grade-III (score 11-14). After data normalisation, differences between Mankin grades and correlations between imaging parameters were assessed using ANOVA and Tukey's post-hoc test and Spearman's correlation coefficients, respectively. Sensitivities and specificities in the detection of Mankin grade-0 were calculated. Significant degeneration-related increases were found for T2 and OII and decreases for OAI, while T1, T1ρ, T2* or OHI did not reveal significant changes in relation to degeneration. A number of significant correlations between imaging parameters and histological (sub)scores were found, in particular for T2 and OII. Sensitivities and specificities in the detection of Mankin grade-0 were highest for OHI/T1 and OII/T1ρ, respectively. Quantitative OCT and MRI techniques seem to complement each other in the comprehensive assessment of cartilage degeneration. Sufficiently large structural and compositional changes in the extracellular matrix may thus be parameterized and quantified, while the detection of early degeneration remains challenging. (orig.)

Quantitative OCT and MRI biomarkers for the differentiation of cartilage degeneration

Energy Technology Data Exchange (ETDEWEB)

Nebelung, Sven [Aachen University Hospital, Department of Orthopaedics, Aachen (Germany); Institute of Anatomy and Cell Biology, RWTH, Aachen (Germany); Brill, Nicolai [Fraunhofer Institute for Production Technology, Aachen (Germany); Tingart, Markus; Jahr, Holger [Aachen University Hospital, Department of Orthopaedics, Aachen (Germany); Pufe, Thomas [Institute of Anatomy and Cell Biology, RWTH, Aachen (Germany); Kuhl, Christiane; Truhn, Daniel [Aachen University Hospital, Department of Diagnostic and Interventional Radiology, Aachen (Germany)

2016-04-15

To evaluate the usefulness of quantitative parameters obtained by optical coherence tomography (OCT) and magnetic resonance imaging (MRI) in the comprehensive assessment of human articular cartilage degeneration. Human osteochondral samples of variable degeneration (n = 45) were obtained from total knee replacements and assessed by MRI sequences measuring T1, T1ρ, T2 and T2* relaxivity and by OCT-based quantification of irregularity (OII, optical irregularity index), homogeneity (OHI, optical homogeneity index) and attenuation (OAI, optical attenuation index). Samples were also assessed macroscopically (Outerbridge classification) and histologically (Mankin classification) as grade-0 (Mankin scores 0-4)/grade-I (scores 5-8)/grade-II (scores 9-10)/grade-III (score 11-14). After data normalisation, differences between Mankin grades and correlations between imaging parameters were assessed using ANOVA and Tukey's post-hoc test and Spearman's correlation coefficients, respectively. Sensitivities and specificities in the detection of Mankin grade-0 were calculated. Significant degeneration-related increases were found for T2 and OII and decreases for OAI, while T1, T1ρ, T2* or OHI did not reveal significant changes in relation to degeneration. A number of significant correlations between imaging parameters and histological (sub)scores were found, in particular for T2 and OII. Sensitivities and specificities in the detection of Mankin grade-0 were highest for OHI/T1 and OII/T1ρ, respectively. Quantitative OCT and MRI techniques seem to complement each other in the comprehensive assessment of cartilage degeneration. Sufficiently large structural and compositional changes in the extracellular matrix may thus be parameterized and quantified, while the detection of early degeneration remains challenging. (orig.)

Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization

Science.gov (United States)

Mahgoub, Hend; Gilchrist, John R.; Fearn, Thomas; Strlič, Matija

2017-07-01

Recently, spectral imaging techniques such as Multispectral (MSI) and Hyperspectral Imaging (HSI) have gained importance in the field of heritage conservation. This paper explores the analytical robustness of quantitative chemical imaging for Islamic paper characterization by focusing on the effect of different measurement and processing parameters, i.e. acquisition conditions and calibration on the accuracy of the collected spectral data. This will provide a better understanding of the technique that can provide a measure of change in collections through imaging. For the quantitative model, special calibration target was devised using 105 samples from a well-characterized reference Islamic paper collection. Two material properties were of interest: starch sizing and cellulose degree of polymerization (DP). Multivariate data analysis methods were used to develop discrimination and regression models which were used as an evaluation methodology for the metrology of quantitative NIR chemical imaging. Spectral data were collected using a pushbroom HSI scanner (Gilden Photonics Ltd) in the 1000-2500 nm range with a spectral resolution of 6.3 nm using a mirror scanning setup and halogen illumination. Data were acquired at different measurement conditions and acquisition parameters. Preliminary results showed the potential of the evaluation methodology to show that measurement parameters such as the use of different lenses and different scanning backgrounds may not have a great influence on the quantitative results. Moreover, the evaluation methodology allowed for the selection of the best pre-treatment method to be applied to the data.

Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders

Directory of Open Access Journals (Sweden)

Venugopal Abhilash

2009-01-01

Full Text Available Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS. Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.

TH-AB-209-09: Quantitative Imaging of Electrical Conductivity by VHF-Induced Thermoacoustics

Energy Technology Data Exchange (ETDEWEB)

Patch, S; Hull, D [Avero Diagnostics, Irving, TX (United States); See, W [Medical College of Wisconsin, Milwaukee, WI (United States); Hanson, G [UW-Milwaukee, Milwaukee, WI (United States)

2016-06-15

Purpose: To demonstrate that very high frequency (VHF) induced thermoacoustics has the potential to provide quantitative images of electrical conductivity in Siemens/meter, much as shear wave elastography provides tissue stiffness in kPa. Quantitatively imaging a large organ requires exciting thermoacoustic pulses throughout the volume and broadband detection of those pulses because tomographic image reconstruction preserves frequency content. Applying the half-wavelength limit to a 200-micron inclusion inside a 7.5 cm diameter organ requires measurement sensitivity to frequencies ranging from 4 MHz down to 10 kHz, respectively. VHF irradiation provides superior depth penetration over near infrared used in photoacoustics. Additionally, VHF signal production is proportional to electrical conductivity, and prostate cancer is known to suppress electrical conductivity of prostatic fluid. Methods: A dual-transducer system utilizing a P4-1 array connected to a Verasonics V1 system augmented by a lower frequency focused single element transducer was developed. Simultaneous acquisition of VHF-induced thermoacoustic pulses by both transducers enabled comparison of transducer performance. Data from the clinical array generated a stack of 96-images with separation of 0.3 mm, whereas the single element transducer imaged only in a single plane. In-plane resolution and quantitative accuracy were measured at isocenter. Results: The array provided volumetric imaging capability with superior resolution whereas the single element transducer provided superior quantitative accuracy. Combining axial images from both transducers preserved resolution of the P4-1 array and improved image contrast. Neither transducer was sensitive to frequencies below 50 kHz, resulting in a DC offset and low-frequency shading over fields of view exceeding 15 mm. Fresh human prostates were imaged ex vivo and volumetric reconstructions reveal structures rarely seen in diagnostic images. Conclusion

Volumetry based biomarker speed of growth: Quantifying the change of total tumor volume in whole-body magnetic resonance imaging over time improves risk stratification of smoldering multiple myeloma patients.

Science.gov (United States)

Wennmann, Markus; Kintzelé, Laurent; Piraud, Marie; Menze, Bjoern H; Hielscher, Thomas; Hofmanninger, Johannes; Wagner, Barbara; Kauczor, Hans-Ulrich; Merz, Maximilian; Hillengass, Jens; Langs, Georg; Weber, Marc-André

2018-05-18

The purpose of this study was to improve risk stratification of smoldering multiple myeloma patients, introducing new 3D-volumetry based imaging biomarkers derived from whole-body MRI. Two-hundred twenty whole-body MRIs from 63 patients with smoldering multiple myeloma were retrospectively analyzed and all focal lesions >5mm were manually segmented for volume quantification. The imaging biomarkers total tumor volume, speed of growth (development of the total tumor volume over time), number of focal lesions, development of the number of focal lesions over time and the recent imaging biomarker '>1 focal lesion' of the International Myeloma Working Group were compared, taking 2-year progression rate, sensitivity and false positive rate into account. Speed of growth, using a cutoff of 114mm 3 /month, was able to isolate a high-risk group with a 2-year progression rate of 82.5%. Additionally, it showed by far the highest sensitivity in this study and in comparison to other biomarkers in the literature, detecting 63.2% of patients who progress within 2 years. Furthermore, its false positive rate (8.7%) was much lower compared to the recent imaging biomarker '>1 focal lesion' of the International Myeloma Working Group. Therefore, speed of growth is the preferable imaging biomarker for risk stratification of smoldering multiple myeloma patients.

SNIPE: A New Method to Identify Imaging Biomarker for Early Detection of Alzheimer’s Disease

DEFF Research Database (Denmark)

Coupé, Pierrick; Eskildsen, Simon Fristed; Manjón, José V.

, from a clinical point of view the prediction of AD is the key question since it is in that moment when treatment is possible. The potential use of structural MRI as imaging biomarker for Alzheimer’s disease (AD) for early detection has become generally accepted, especially the use of atrophy...

Quantitative magnetization transfer imaging of rodent glioma using selective inversion recovery.

Science.gov (United States)

Xu, Junzhong; Li, Ke; Zu, Zhongliang; Li, Xia; Gochberg, Daniel F; Gore, John C

2014-03-01

Magnetization transfer (MT) provides an indirect means to detect noninvasively variations in macromolecular contents in biological tissues, but, so far, there have been only a few quantitative MT (qMT) studies reported in cancer, all of which used off-resonance pulsed saturation methods. This article describes the first implementation of a different qMT approach, selective inversion recovery (SIR), for the characterization of tumor in vivo using a rodent glioma model. The SIR method is an on-resonance method capable of fitting qMT parameters and T1 relaxation time simultaneously without mapping B0 and B1 , which is very suitable for high-field qMT measurements because of the lower saturation absorption rate. The results show that the average pool size ratio (PSR, the macromolecular pool versus the free water pool) in rat 9 L glioma (5.7%) is significantly lower than that in normal rat gray matter (9.2%) and white matter (17.4%), which suggests that PSR is potentially a sensitive imaging biomarker for the assessment of brain tumor. Despite being less robust, the estimated MT exchange rates also show clear differences from normal tissues (19.7 Hz for tumors versus 14.8 and 10.2 Hz for gray and white mater, respectively). In addition, the influence of confounding effects, e.g. B1 inhomogeneity, on qMT parameter estimates is investigated with numerical simulations. These findings not only help to better understand the changes in the macromolecular contents of tumors, but are also important for the interpretation of other imaging contrasts, such as chemical exchange saturation transfer of tumors. Copyright © 2013 John Wiley & Sons, Ltd.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

Science.gov (United States)

Parker, Carol E; Borchers, Christoph H

2014-06-01

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Classification of quantitative light-induced fluorescence images using convolutional neural network

NARCIS (Netherlands)

Imangaliyev, S.; van der Veen, M.H.; Volgenant, C.M.C.; Loos, B.G.; Keijser, B.J.F.; Crielaard, W.; Levin, E.; Lintas, A.; Rovetta, S.; Verschure, P.F.M.J.; Villa, A.E.P.

2017-01-01

Images are an important data source for diagnosis of oral diseases. The manual classification of images may lead to suboptimal treatment procedures due to subjective errors. In this paper an image classification algorithm based on Deep Learning framework is applied to Quantitative Light-induced

Water volume quantitation using nuclear magnetic resonance imaging: application to cerebrospinal fluid

International Nuclear Information System (INIS)

Lecouffe, P.; Huglo, D.; Dubois, P.; Rousseau, J.; Marchandise, X.

1990-01-01

Quantitation in proton NMR imaging is applied to cerebrospinal fluid (CSF). Total intracranial CSF volume was measured from Condon's method: CSF signal was compared with distilled water standard signal in a single sagittal thick slice. Brain signal was reduced to minimum using a 5000/360/400 sequence. Software constraints did not permit easy implementing on imager and uniformity correction was performed on a microcomputer. Accuracy was better than 4%. Total intracranial CSF was found between 91 and 164 ml in 5 healthy volunteers. Extraventricular CSF quantitation appears very improved by this method, but planimetric methods seem better in order to quantify ventricular CSF. This technique is compared to total lung water measurement from proton density according to Mac Lennan's method. Water volume quantitation confirms ability of NMR imaging to quantify biologic parameters but image defects have to be known by strict quality control [fr

Planar gamma camera imaging and quantitation of Yttrium-90 bremsstrahlung

International Nuclear Information System (INIS)

Shen, S.; DeNardo, G.L.; Yuan, A.

1994-01-01

Yttrium-90 is a promising radionuclide for radioimmunotherapy of cancer because of its energetic beta emissions. Therapeutic management requires quantitative imaging to assess the pharmacokinetics and radiation dosimetry of the 90 Y-labeled antibody. Conventional gamma photon imaging methods cannot be easily applied to imaging of 90 Y-bremsstrahlung because of its continuous energy spectrum. The sensitivity, resolution and source-to-background signal ratio (S/B) of the detector system for 90 Y-bremsstrahlung were investigated for various collimators and energy windows in order to determine optimum conditions for quantitative imaging. After these conditions were determined, the accuracy of quantitation of 90 Y activity in an Alderson abdominal phantom was examined. When the energy-window width was increased, the benefit of increased sensitivity outweighed degradation in resolution and S/B ratio until the manufacturer's energy specifications for the collimator were exceeded. Using the same energy window, the authors improved resolution and S/B for the medium-energy (ME) collimator when compared to the low-energy, all-purpose (LEAP) collimator, and there was little additional improvement using the high-energy (HE) collimator. Camera sensitivity under tissue equivalent conditions was 4.2 times greater for the LEAP and 1.7 times greater for the ME collimators when compared to the HE collimator. Thus, the best, most practical selections were found to be the ME collimator and an energy window of 55-285 keV. When they used these optimal conditions for image acquisition, the estimation of 90 Y activity in organs and tumors was within 15% of the true activities. The results for this study suggest that reasonable accuracy can be achieved in clinical radioimmunotherapy using 90 Y-bremsstrahlung quantitation. 28 refs., 5 figs., 7 tabs

Quantitative Nuclear Medicine Imaging: Concepts, Requirements and Methods

Energy Technology Data Exchange (ETDEWEB)

NONE

2014-01-15

The absolute quantification of radionuclide distribution has been a goal since the early days of nuclear medicine. Nevertheless, the apparent complexity and sometimes limited accuracy of these methods have prevented them from being widely used in important applications such as targeted radionuclide therapy or kinetic analysis. The intricacy of the effects degrading nuclear medicine images and the lack of availability of adequate methods to compensate for these effects have frequently been seen as insurmountable obstacles in the use of quantitative nuclear medicine in clinical institutions. In the last few decades, several research groups have consistently devoted their efforts to the filling of these gaps. As a result, many efficient methods are now available that make quantification a clinical reality, provided appropriate compensation tools are used. Despite these efforts, many clinical institutions still lack the knowledge and tools to adequately measure and estimate the accumulated activities in the human body, thereby using potentially outdated protocols and procedures. The purpose of the present publication is to review the current state of the art of image quantification and to provide medical physicists and other related professionals facing quantification tasks with a solid background of tools and methods. It describes and analyses the physical effects that degrade image quality and affect the accuracy of quantification, and describes methods to compensate for them in planar, single photon emission computed tomography (SPECT) and positron emission tomography (PET) images. The fast paced development of the computational infrastructure, both hardware and software, has made drastic changes in the ways image quantification is now performed. The measuring equipment has evolved from the simple blind probes to planar and three dimensional imaging, supported by SPECT, PET and hybrid equipment. Methods of iterative reconstruction have been developed to allow for

Morphological image processing for quantitative shape analysis of biomedical structures: effective contrast enhancement

International Nuclear Information System (INIS)

Kimori, Yoshitaka

2013-01-01

A contrast enhancement approach utilizing a new type of mathematical morphology called rotational morphological processing is introduced. The method is quantitatively evaluated and then applied to some medical images. Image processing methods significantly contribute to visualization of images captured by biomedical modalities (such as mammography, X-ray computed tomography, magnetic resonance imaging, and light and electron microscopy). Quantitative interpretation of the deluge of complicated biomedical images, however, poses many research challenges, one of which is to enhance structural features that are scarcely perceptible to the human eye. This study introduces a contrast enhancement approach based on a new type of mathematical morphology called rotational morphological processing. The proposed method is applied to medical images for the enhancement of structural features. The effectiveness of the method is evaluated quantitatively by the contrast improvement ratio (CIR). The CIR of the proposed method is 12.1, versus 4.7 and 0.1 for two conventional contrast enhancement methods, clearly indicating the high contrasting capability of the method

Quantitative PET imaging with the 3T MR-BrainPET

International Nuclear Information System (INIS)

Weirich, C.; Scheins, J.; Lohmann, P.; Tellmann, L.; Byars, L.; Michel, C.; Rota Kops, E.; Brenner, D.; Herzog, H.; Shah, N.J.

2013-01-01

The new hybrid imaging technology of MR-PET allows for simultaneous acquisition of versatile MRI contrasts and the quantitative metabolic imaging with PET. In order to achieve the quantification of PET images with minimal residual error the application of several corrections is crucial. In this work we present our results on quantification with the 3T MR BrainPET scanner

MR Fingerprinting for Rapid Quantitative Abdominal Imaging.

Science.gov (United States)

Chen, Yong; Jiang, Yun; Pahwa, Shivani; Ma, Dan; Lu, Lan; Twieg, Michael D; Wright, Katherine L; Seiberlich, Nicole; Griswold, Mark A; Gulani, Vikas

2016-04-01

To develop a magnetic resonance (MR) "fingerprinting" technique for quantitative abdominal imaging. This HIPAA-compliant study had institutional review board approval, and informed consent was obtained from all subjects. To achieve accurate quantification in the presence of marked B0 and B1 field inhomogeneities, the MR fingerprinting framework was extended by using a two-dimensional fast imaging with steady-state free precession, or FISP, acquisition and a Bloch-Siegert B1 mapping method. The accuracy of the proposed technique was validated by using agarose phantoms. Quantitative measurements were performed in eight asymptomatic subjects and in six patients with 20 focal liver lesions. A two-tailed Student t test was used to compare the T1 and T2 results in metastatic adenocarcinoma with those in surrounding liver parenchyma and healthy subjects. Phantom experiments showed good agreement with standard methods in T1 and T2 after B1 correction. In vivo studies demonstrated that quantitative T1, T2, and B1 maps can be acquired within a breath hold of approximately 19 seconds. T1 and T2 measurements were compatible with those in the literature. Representative values included the following: liver, 745 msec ± 65 (standard deviation) and 31 msec ± 6; renal medulla, 1702 msec ± 205 and 60 msec ± 21; renal cortex, 1314 msec ± 77 and 47 msec ± 10; spleen, 1232 msec ± 92 and 60 msec ± 19; skeletal muscle, 1100 msec ± 59 and 44 msec ± 9; and fat, 253 msec ± 42 and 77 msec ± 16, respectively. T1 and T2 in metastatic adenocarcinoma were 1673 msec ± 331 and 43 msec ± 13, respectively, significantly different from surrounding liver parenchyma relaxation times of 840 msec ± 113 and 28 msec ± 3 (P < .0001 and P < .01) and those in hepatic parenchyma in healthy volunteers (745 msec ± 65 and 31 msec ± 6, P < .0001 and P = .021, respectively). A rapid technique for quantitative abdominal imaging was developed that allows simultaneous quantification of multiple tissue

Biomarkers for Detecting Mitochondrial Disorders

Directory of Open Access Journals (Sweden)

Josef Finsterer

2018-01-01

Full Text Available (1 Objectives: Mitochondrial disorders (MIDs are a genetically and phenotypically heterogeneous group of slowly or rapidly progressive disorders with onset from birth to senescence. Because of their variegated clinical presentation, MIDs are difficult to diagnose and are frequently missed in their early and late stages. This is why there is a need to provide biomarkers, which can be easily obtained in the case of suspecting a MID to initiate the further diagnostic work-up. (2 Methods: Literature review. (3 Results: Biomarkers for diagnostic purposes are used to confirm a suspected diagnosis and to facilitate and speed up the diagnostic work-up. For diagnosing MIDs, a number of dry and wet biomarkers have been proposed. Dry biomarkers for MIDs include the history and clinical neurological exam and structural and functional imaging studies of the brain, muscle, or myocardium by ultrasound, computed tomography (CT, magnetic resonance imaging (MRI, MR-spectroscopy (MRS, positron emission tomography (PET, or functional MRI. Wet biomarkers from blood, urine, saliva, or cerebrospinal fluid (CSF for diagnosing MIDs include lactate, creatine-kinase, pyruvate, organic acids, amino acids, carnitines, oxidative stress markers, and circulating cytokines. The role of microRNAs, cutaneous respirometry, biopsy, exercise tests, and small molecule reporters as possible biomarkers is unsolved. (4 Conclusions: The disadvantages of most putative biomarkers for MIDs are that they hardly meet the criteria for being acceptable as a biomarker (missing longitudinal studies, not validated, not easily feasible, not cheap, not ubiquitously available and that not all MIDs manifest in the brain, muscle, or myocardium. There is currently a lack of validated biomarkers for diagnosing MIDs.

Morphological, functional and metabolic imaging biomarkers: assessment of vascular-disrupting effect on rodent liver tumours

International Nuclear Information System (INIS)

Wang, Huaijun; Li, Junjie; Keyzer, Frederik De; Yu, Jie; Feng, Yuanbo; Marchal, Guy; Ni, Yicheng; Chen, Feng; Nuyts, Johan

2010-01-01

To evaluate effects of a vascular-disrupting agent on rodent tumour models. Twenty rats with liver rhabdomyosarcomas received ZD6126 intravenously at 20 mg/kg, and 10 vehicle-treated rats were used as controls. Multiple sequences, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) with the microvascular permeability constant (K), were acquired at baseline, 1 h, 24 h and 48 h post-treatment by using 1.5-T MRI. [ 18 F]fluorodeoxyglucose micro-positron emission tomography ( 18 F-FDG μPET) was acquired pre- and post-treatment. The imaging biomarkers including tumour volume, enhancement ratio, necrosis ratio, apparent diffusion coefficient (ADC) and K from MRI, and maximal standardised uptake value (SUV max ) from FDG μPET were quantified and correlated with postmortem microangiography and histopathology. In the ZD6126-treated group, tumours grew slower with higher necrosis ratio at 48 h (P max dropped at 24 h (P < 0.01). Relative K of tumour versus liver at 48 h correlated with relative vascular density on microangiography (r = 0.93, P < 0.05). The imaging biomarkers allowed morphological, functional and metabolic quantifications of vascular shutdown, necrosis formation and tumour relapse shortly after treatment. A single dose of ZD6126 significantly diminished tumour blood supply and growth until 48 h post-treatment. (orig.)

Cadmium phytotoxicity: Quantitative sensitivity relationships between classical endpoints and antioxidative enzyme biomarkers

International Nuclear Information System (INIS)

Rosa Correa, Albertina Xavier da; Roerig, Leonardo Rubi; Verdinelli, Miguel A.; Cotelle, Sylvie; Ferard, Jean-Francois; Radetski, Claudemir Marcos

2006-01-01

In this work, cadmium phytotoxicity and quantitative sensitivity relationships between different hierarchical endpoints in plants cultivated in a contaminated soil were studied. Thus, germination rate, biomass growth and antioxidative enzyme activity (i.e. superoxide dismutase, peroxidase, catalase and glutathione reductase) in three terrestrial plants (Avena sativa L., Brassica campestris L. cv. Chinensis, Lactuca sativa L. cv. hanson) were analyzed. Plant growth tests were carried out according to an International Standard Organization method and the results were analyzed by ANOVA followed by Williams' test. The concentration of Cd 2+ that had the smallest observed significant negative effect (LOEC) on plant biomass was 6.25, 12.5 and 50 mg Cd/kg dry soil for lettuce, oat and Chinese cabbage, respectively. Activity of all enzymes studied increased significantly compared to enzyme activity in plant controls. For lettuce, LOEC values (mg Cd/kg dry soil) for enzymic activity ranged from 0.05 (glutathione reductase) to 0.39 (catalase). For oat, LOEC values (mg Cd/kg dry soil) ranged from 0.19 (for superoxide dismutase and glutathione reductase) to 0.39 (for catalase and peroxidase). For Chinese cabbage, LOEC values (mg Cd/kg dry soil) ranged from 0.19 (peroxidase, catalase and glutathione reductase) to 0.39 (superoxide dismutase). Classical (i.e. germination and biomass) and biochemical (i.e. enzyme activity) endpoints were compared to establish a sensitivity ranking, which was: enzyme activity > biomass > germination rate. For cadmium-soil contamination, the determination of quantitative sensitivity relationships (QSR) between classical and antioxidative enzyme biomarkers showed that the most sensitive plant species have, generally, the lowest QSR values

Quantitative analysis of elastography images in the detection of breast cancer

International Nuclear Information System (INIS)

Landoni, V.; Francione, V.; Marzi, S.; Pasciuti, K.; Ferrante, F.; Saracca, E.; Pedrini, M.; Strigari, L.; Crecco, M.; Di Nallo, A.

2012-01-01

Purpose: The aim of this study was to develop a quantitative method for breast cancer diagnosis based on elastosonography images in order to reduce whenever possible unnecessary biopsies. The proposed method was validated by correlating the results of quantitative analysis with the diagnosis assessed by histopathologic exam. Material and methods: 109 images of breast lesions (50 benign and 59 malignant) were acquired with the traditional B-mode technique and with elastographic modality. Images in Digital Imaging and COmmunications in Medicine format (DICOM) were exported into a software, written in Visual Basic, especially developed to perform this study. The lesion was contoured and the mean grey value and softness inside the region of interest (ROI) were calculated. The correlations between variables were investigated and receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of the proposed method. Pathologic results were used as standard reference. Results: Both the mean grey value and the softness inside the ROI resulted statistically different at the t test for the two populations of lesions (i.e., benign versus malignant): p < 0.0001. The area under the curve (AUC) was 0.924 (0.834–0.973) and 0.917 (0.826–0.970) for the mean grey value and for the softness respectively. Conclusions: Quantitative elastosonography is a promising ultrasound technique in the detection of breast cancer but large prospective trials are necessary to determine whether quantitative analysis of images can help to overcome some pitfalls of the methodic.

Dynamic and accurate assessment of acetaminophen-induced hepatotoxicity by integrated photoacoustic imaging and mechanistic biomarkers in vivo.

Science.gov (United States)

Brillant, Nathalie; Elmasry, Mohamed; Burton, Neal C; Rodriguez, Josep Monne; Sharkey, Jack W; Fenwick, Stephen; Poptani, Harish; Kitteringham, Neil R; Goldring, Christopher E; Kipar, Anja; Park, B Kevin; Antoine, Daniel J

2017-10-01

The prediction and understanding of acetaminophen (APAP)-induced liver injury (APAP-ILI) and the response to therapeutic interventions is complex. This is due in part to sensitivity and specificity limitations of currently used assessment techniques. Here we sought to determine the utility of integrating translational non-invasive photoacoustic imaging of liver function with mechanistic circulating biomarkers of hepatotoxicity with histological assessment to facilitate the more accurate and precise characterization of APAP-ILI and the efficacy of therapeutic intervention. Perturbation of liver function and cellular viability was assessed in C57BL/6J male mice by Indocyanine green (ICG) clearance (Multispectral Optoacoustic Tomography (MSOT)) and by measurement of mechanistic (miR-122, HMGB1) and established (ALT, bilirubin) circulating biomarkers in response to the acetaminophen and its treatment with acetylcysteine (NAC) in vivo. We utilised a 60% partial hepatectomy model as a situation of defined hepatic functional mass loss to compared acetaminophen-induced changes to. Integration of these mechanistic markers correlated with histological features of APAP hepatotoxicity in a time-dependent manner. They accurately reflected the onset and recovery from hepatotoxicity compared to traditional biomarkers and also reported the efficacy of NAC with high sensitivity. ICG clearance kinetics correlated with histological scores for acute liver damage for APAP (i.e. 3h timepoint; r=0.90, P<0.0001) and elevations in both of the mechanistic biomarkers, miR-122 (e.g. 6h timepoint; r=0.70, P=0.005) and HMGB1 (e.g. 6h timepoint; r=0.56, P=0.04). For the first time we report the utility of this non-invasive longitudinal imaging approach to provide direct visualisation of the liver function coupled with mechanistic biomarkers, in the same animal, allowing the investigation of the toxicological and pharmacological aspects of APAP-ILI and hepatic regeneration. Copyright © 2017

Quantitative Analysis in Nuclear Medicine Imaging

CERN Document Server

2006-01-01

This book provides a review of image analysis techniques as they are applied in the field of diagnostic and therapeutic nuclear medicine. Driven in part by the remarkable increase in computing power and its ready and inexpensive availability, this is a relatively new yet rapidly expanding field. Likewise, although the use of radionuclides for diagnosis and therapy has origins dating back almost to the discovery of natural radioactivity itself, radionuclide therapy and, in particular, targeted radionuclide therapy has only recently emerged as a promising approach for therapy of cancer and, to a lesser extent, other diseases. As effort has, therefore, been made to place the reviews provided in this book in a broader context. The effort to do this is reflected by the inclusion of introductory chapters that address basic principles of nuclear medicine imaging, followed by overview of issues that are closely related to quantitative nuclear imaging and its potential role in diagnostic and therapeutic applications. ...

Ultra-fast quantitative imaging using ptychographic iterative engine based digital micro-mirror device

Science.gov (United States)

Sun, Aihui; Tian, Xiaolin; Kong, Yan; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-01-01

As a lensfree imaging technique, ptychographic iterative engine (PIE) method can provide both quantitative sample amplitude and phase distributions avoiding aberration. However, it requires field of view (FoV) scanning often relying on mechanical translation, which not only slows down measuring speed, but also introduces mechanical errors decreasing both resolution and accuracy in retrieved information. In order to achieve high-accurate quantitative imaging with fast speed, digital micromirror device (DMD) is adopted in PIE for large FoV scanning controlled by on/off state coding by DMD. Measurements were implemented using biological samples as well as USAF resolution target, proving high resolution in quantitative imaging using the proposed system. Considering its fast and accurate imaging capability, it is believed the DMD based PIE technique provides a potential solution for medical observation and measurements.

Image segmentation evaluation for very-large datasets

Science.gov (United States)

Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

Magnetic resonance imaging biomarkers of gastrointestinal motor function and fluid distribution

Institute of Scientific and Technical Information of China (English)

Asseel; Khalaf; Caroline; L; Hoad; Robin; C; Spiller; Penny; A; Gowland; Gordon; W; Moran; Luca; Marciani

2015-01-01

Magnetic resonance imaging(MRI) is a well established technique that has revolutionized diagnostic radiology. Until recently, the impact that MRI has had in the assessment of gastrointestinal motor function and bowel fluid distribution in health and in disease has been more limited, despite the novel insights that MRI can provide along the entire gastrointestinal tract. MRI biomarkers include intestinal motility indices, small bowel water content and whole gut transit time. The present review discusses new developments and applications of MRI in the upper gastrointestinal tract, the small bowel and the colon reported in the literature in the last 5 years.

Susceptibility-Weighted Imaging and Quantitative Susceptibility Mapping in the Brain

Science.gov (United States)

Liu, Chunlei; Li, Wei; Tong, Karen A.; Yeom, Kristen W.; Kuzminski, Samuel

2015-01-01

Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique that enhances image contrast by using the susceptibility differences between tissues. It is created by combining both magnitude and phase in the gradient echo data. SWI is sensitive to both paramagnetic and diamagnetic substances which generate different phase shift in MRI data. SWI images can be displayed as a minimum intensity projection that provides high resolution delineation of the cerebral venous architecture, a feature that is not available in other MRI techniques. As such, SWI has been widely applied to diagnose various venous abnormalities. SWI is especially sensitive to deoxygenated blood and intracranial mineral deposition and, for that reason, has been applied to image various pathologies including intracranial hemorrhage, traumatic brain injury, stroke, neoplasm, and multiple sclerosis. SWI, however, does not provide quantitative measures of magnetic susceptibility. This limitation is currently being addressed with the development of quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI). While QSM treats susceptibility as isotropic, STI treats susceptibility as generally anisotropic characterized by a tensor quantity. This article reviews the basic principles of SWI, its clinical and research applications, the mechanisms governing brain susceptibility properties, and its practical implementation, with a focus on brain imaging. PMID:25270052

Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain.

Science.gov (United States)

Liu, Chunlei; Li, Wei; Tong, Karen A; Yeom, Kristen W; Kuzminski, Samuel

2015-07-01

Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique that enhances image contrast by using the susceptibility differences between tissues. It is created by combining both magnitude and phase in the gradient echo data. SWI is sensitive to both paramagnetic and diamagnetic substances which generate different phase shift in MRI data. SWI images can be displayed as a minimum intensity projection that provides high resolution delineation of the cerebral venous architecture, a feature that is not available in other MRI techniques. As such, SWI has been widely applied to diagnose various venous abnormalities. SWI is especially sensitive to deoxygenated blood and intracranial mineral deposition and, for that reason, has been applied to image various pathologies including intracranial hemorrhage, traumatic brain injury, stroke, neoplasm, and multiple sclerosis. SWI, however, does not provide quantitative measures of magnetic susceptibility. This limitation is currently being addressed with the development of quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI). While QSM treats susceptibility as isotropic, STI treats susceptibility as generally anisotropic characterized by a tensor quantity. This article reviews the basic principles of SWI, its clinical and research applications, the mechanisms governing brain susceptibility properties, and its practical implementation, with a focus on brain imaging. © 2014 Wiley Periodicals, Inc.

Quantitative myocardial perfusion PET parametric imaging at the voxel-level

International Nuclear Information System (INIS)

Mohy-ud-Din, Hassan; Rahmim, Arman; Lodge, Martin A

2015-01-01

Quantitative myocardial perfusion (MP) PET has the potential to enhance detection of early stages of atherosclerosis or microvascular dysfunction, characterization of flow-limiting effects of coronary artery disease (CAD), and identification of balanced reduction of flow due to multivessel stenosis. We aim to enable quantitative MP-PET at the individual voxel level, which has the potential to allow enhanced visualization and quantification of myocardial blood flow (MBF) and flow reserve (MFR) as computed from uptake parametric images. This framework is especially challenging for the 82 Rb radiotracer. The short half-life enables fast serial imaging and high patient throughput; yet, the acquired dynamic PET images suffer from high noise-levels introducing large variability in uptake parametric images and, therefore, in the estimates of MBF and MFR. Robust estimation requires substantial post-smoothing of noisy data, degrading valuable functional information of physiological and pathological importance. We present a feasible and robust approach to generate parametric images at the voxel-level that substantially reduces noise without significant loss of spatial resolution. The proposed methodology, denoted physiological clustering, makes use of the functional similarity of voxels to penalize deviation of voxel kinetics from physiological partners. The results were validated using extensive simulations (with transmural and non-transmural perfusion defects) and clinical studies. Compared to post-smoothing, physiological clustering depicted enhanced quantitative noise versus bias performance as well as superior recovery of perfusion defects (as quantified by CNR) with minimal increase in bias. Overall, parametric images obtained from the proposed methodology were robust in the presence of high-noise levels as manifested in the voxel time-activity-curves. (paper)

Qualitative and quantitative analysis of reconstructed images using projections with noises

International Nuclear Information System (INIS)

Lopes, R.T.; Assis, J.T. de

1988-01-01

The reconstruction of a two-dimencional image from one-dimensional projections in an analytic algorithm ''convolution method'' is simulated on a microcomputer. In this work it was analysed the effects caused in the reconstructed image in function of the number of projections and noise level added to the projection data. Qualitative and quantitative (distortion and image noise) comparison were done with the original image and the reconstructed images. (author) [pt

Molecular imaging reveals elevated VEGFR-2 expression in retinal capillaries in diabetes: a novel biomarker for early diagnosis

OpenAIRE

Sun, Dawei; Nakao, Shintaro; Xie, Fang; Zandi, Souska; Bagheri, Abouzar; Kanavi, Mozhgan Rezaei; Samiei, Shahram; Soheili, Zahra-Soheila; Frimmel, Sonja; Zhang, Zhongyu; Ablonczy, Zsolt; Ahmadieh, Hamid; Hafezi-Moghadam, Ali

2014-01-01

Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of vision loss. Biomarkers and methods for early diagnosis of DR are urgently needed. Using a new molecular imaging approach, we show up to 94% higher accumulation of custom designed imaging probes against vascular endothelial growth factor receptor 2 (VEGFR-2) in retinal and choroidal vessels of diabetic animals (P

Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.

Science.gov (United States)

Cerrolaza, Juan J; Peters, Craig A; Martin, Aaron D; Myers, Emmarie; Safdar, Nabile; Linguraru, Marius George

2016-04-01

We define sonographic biomarkers for hydronephrotic renal units that can predict the necessity of diuretic nuclear renography. We selected a cohort of 50 consecutive patients with hydronephrosis of varying severity in whom 2-dimensional sonography and diuretic mercaptoacetyltriglycine renography had been performed. A total of 131 morphological parameters were computed using quantitative image analysis algorithms. Machine learning techniques were then applied to identify ultrasound based safety thresholds that agreed with the t½ for washout. A best fit model was then derived for each threshold level of t½ that would be clinically relevant at 20, 30 and 40 minutes. Receiver operating characteristic curve analysis was performed. Sensitivity, specificity and area under the receiver operating characteristic curve were determined. Improvement obtained by the quantitative imaging method compared to the Society for Fetal Urology grading system and the hydronephrosis index was statistically verified. For the 3 thresholds considered and at 100% sensitivity the specificities of the quantitative imaging method were 94%, 70% and 74%, respectively. Corresponding area under the receiver operating characteristic curve values were 0.98, 0.94 and 0.94, respectively. Improvement obtained by the quantitative imaging method over the Society for Fetal Urology grade and hydronephrosis index was statistically significant (p hydronephrosis can identify thresholds of clinically significant washout times with 100% sensitivity to decrease the number of diuretic renograms in up to 62% of children. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Functional MRI and CT biomarkers in oncology

Energy Technology Data Exchange (ETDEWEB)

Winfield, J.M. [Institute of Cancer Research and Royal Marsden NHS Foundation Trust, CRUK Imaging Centre at the Institute of Cancer Research, Sutton (United Kingdom); Institute of Cancer Research and Royal Marsden Hospital, MRI Unit, Sutton (United Kingdom); Payne, G.S.; DeSouza, N.M. [Institute of Cancer Research and Royal Marsden NHS Foundation Trust, CRUK Imaging Centre at the Institute of Cancer Research, Sutton (United Kingdom)

2015-04-01

Imaging biomarkers derived from MRI or CT describe functional properties of tumours and normal tissues. They are finding increasing numbers of applications in diagnosis, monitoring of response to treatment and assessment of progression or recurrence. Imaging biomarkers also provide scope for assessment of heterogeneity within and between lesions. A wide variety of functional parameters have been investigated for use as biomarkers in oncology. Some imaging techniques are used routinely in clinical applications while others are currently restricted to clinical trials or preclinical studies. Apparent diffusion coefficient, magnetization transfer ratio and native T{sub 1} relaxation time provide information about structure and organization of tissues. Vascular properties may be described using parameters derived from dynamic contrast-enhanced MRI, dynamic contrast-enhanced CT, transverse relaxation rate (R{sub 2}*), vessel size index and relative blood volume, while magnetic resonance spectroscopy may be used to probe the metabolic profile of tumours. This review describes the mechanisms of contrast underpinning each technique and the technical requirements for robust and reproducible imaging. The current status of each biomarker is described in terms of its validation, qualification and clinical applications, followed by a discussion of the current limitations and future perspectives. (orig.)

A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers.

Science.gov (United States)

Lawrence, Emma; Vegvari, Carolin; Ower, Alison; Hadjichrysanthou, Christoforos; De Wolf, Frank; Anderson, Roy M

2017-01-01

Alzheimer's disease (AD) is a progressive and fatal neurodegenerative disease, with no effective treatment or cure. A gold standard therapy would be treatment to slow or halt disease progression; however, knowledge of causation in the early stages of AD is very limited. In order to determine effective endpoints for possible therapies, a number of quantitative surrogate markers of disease progression have been suggested, including biochemical and imaging biomarkers. The dynamics of these various surrogate markers over time, particularly in relation to disease development, are, however, not well characterized. We reviewed the literature for studies that measured cerebrospinal fluid or plasma amyloid-β and tau, or took magnetic resonance image or fluorodeoxyglucose/Pittsburgh compound B-positron electron tomography scans, in longitudinal cohort studies. We summarized the properties of the major cohort studies in various countries, commonly used diagnosis methods and study designs. We have concluded that additional studies with repeat measures over time in a representative population cohort are needed to address the gap in knowledge of AD progression. Based on our analysis, we suggest directions in which research could move in order to advance our understanding of this complex disease, including repeat biomarker measurements, standardization and increased sample sizes.

A custom-built PET phantom design for quantitative imaging of printed distributions

International Nuclear Information System (INIS)

Markiewicz, P J; Angelis, G I; Kotasidis, F; Green, M; Matthews, J C; Lionheart, W R; Reader, A J

2011-01-01

This note presents a practical approach to a custom-made design of PET phantoms enabling the use of digital radioactive distributions with high quantitative accuracy and spatial resolution. The phantom design allows planar sources of any radioactivity distribution to be imaged in transaxial and axial (sagittal or coronal) planes. Although the design presented here is specially adapted to the high-resolution research tomograph (HRRT), the presented methods can be adapted to almost any PET scanner. Although the presented phantom design has many advantages, a number of practical issues had to be overcome such as positioning of the printed source, calibration, uniformity and reproducibility of printing. A well counter (WC) was used in the calibration procedure to find the nonlinear relationship between digital voxel intensities and the actual measured radioactive concentrations. Repeated printing together with WC measurements and computed radiography (CR) using phosphor imaging plates (IP) were used to evaluate the reproducibility and uniformity of such printing. Results show satisfactory printing uniformity and reproducibility; however, calibration is dependent on the printing mode and the physical state of the cartridge. As a demonstration of the utility of using printed phantoms, the image resolution and quantitative accuracy of reconstructed HRRT images are assessed. There is very good quantitative agreement in the calibration procedure between HRRT, CR and WC measurements. However, the high resolution of CR and its quantitative accuracy supported by WC measurements made it possible to show the degraded resolution of HRRT brain images caused by the partial-volume effect and the limits of iterative image reconstruction. (note)

Mechanistic and quantitative insight into cell surface targeted molecular imaging agent design.

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Zhang, Liang; Bhatnagar, Sumit; Deschenes, Emily; Thurber, Greg M

2016-05-05

Molecular imaging agent design involves simultaneously optimizing multiple probe properties. While several desired characteristics are straightforward, including high affinity and low non-specific background signal, in practice there are quantitative trade-offs between these properties. These include plasma clearance, where fast clearance lowers background signal but can reduce target uptake, and binding, where high affinity compounds sometimes suffer from lower stability or increased non-specific interactions. Further complicating probe development, many of the optimal parameters vary depending on both target tissue and imaging agent properties, making empirical approaches or previous experience difficult to translate. Here, we focus on low molecular weight compounds targeting extracellular receptors, which have some of the highest contrast values for imaging agents. We use a mechanistic approach to provide a quantitative framework for weighing trade-offs between molecules. Our results show that specific target uptake is well-described by quantitative simulations for a variety of targeting agents, whereas non-specific background signal is more difficult to predict. Two in vitro experimental methods for estimating background signal in vivo are compared - non-specific cellular uptake and plasma protein binding. Together, these data provide a quantitative method to guide probe design and focus animal work for more cost-effective and time-efficient development of molecular imaging agents.

Clinical application of quantitative 99Tcm-pertechnetate thyroid imaging

International Nuclear Information System (INIS)

Gao Yongju; Xie Jian; Yan Xinhui; Wand Jiebin; Zhu Xuanmin; Liu Lin; Sun Haizhou

2002-01-01

Objective: To investigate the clinical value of quantitative 99 Tc m -pertechnetate thyroid imaging for the diagnosis and therapeutic evaluation in patients with thyroid disease. Methods: With the Siemens Orbit SPECT, 99 Tc m sodium pertechnetate thyroid imaging was performed on a control group and 108 patients with Graves' disease, 58 patients with Hashimoto's disease, 41 patients with subacute thyroiditis. Three functional parameters were calculated as follows: AR=5 min thyroid count/1 min thyroid count; UI=20 min thyroid count/thigh count; T d =imaging interval between carotid and thyroid. Results: 1) Three functional parameters were basically concordant with serological parameters in patients with Graves' disease. While uptake was high in patients who had contracted Graves' disease for ≤0.5 year, for those whose disease relapsed within 2 years the 99 Tc m thyroid uptake increased when the antithyroid medication was stopped. 2) Thyroid images of hyperthyroid patients with Hashimoto's disease showed increased perfusion and 99 Tc m uptake, a pattern similar to that found in Graves' disease. Differences in T d , AR , UI were not significant among euthyroid, subclinical hypothyroid patients with Hashimoto's disease, so uptake ratios could indicate the thyroid activity. 3) Delayed thyroid image and diffuse uptake decrease were found in hyperthyroid patients with SAT, however, focal damages were observed in euthyroid patients. Conclusion: Quantitative 99 Tc m -pertechnetate thyroid imaging is a significantly helpful technique in the diagnosis and treatment for common thyroid disorders

Quantitative magnetic resonance imaging phantoms: A review and the need for a system phantom.

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Keenan, Kathryn E; Ainslie, Maureen; Barker, Alex J; Boss, Michael A; Cecil, Kim M; Charles, Cecil; Chenevert, Thomas L; Clarke, Larry; Evelhoch, Jeffrey L; Finn, Paul; Gembris, Daniel; Gunter, Jeffrey L; Hill, Derek L G; Jack, Clifford R; Jackson, Edward F; Liu, Guoying; Russek, Stephen E; Sharma, Samir D; Steckner, Michael; Stupic, Karl F; Trzasko, Joshua D; Yuan, Chun; Zheng, Jie

2018-01-01

The MRI community is using quantitative mapping techniques to complement qualitative imaging. For quantitative imaging to reach its full potential, it is necessary to analyze measurements across systems and longitudinally. Clinical use of quantitative imaging can be facilitated through adoption and use of a standard system phantom, a calibration/standard reference object, to assess the performance of an MRI machine. The International Society of Magnetic Resonance in Medicine AdHoc Committee on Standards for Quantitative Magnetic Resonance was established in February 2007 to facilitate the expansion of MRI as a mainstream modality for multi-institutional measurements, including, among other things, multicenter trials. The goal of the Standards for Quantitative Magnetic Resonance committee was to provide a framework to ensure that quantitative measures derived from MR data are comparable over time, between subjects, between sites, and between vendors. This paper, written by members of the Standards for Quantitative Magnetic Resonance committee, reviews standardization attempts and then details the need, requirements, and implementation plan for a standard system phantom for quantitative MRI. In addition, application-specific phantoms and implementation of quantitative MRI are reviewed. Magn Reson Med 79:48-61, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Development of a calibration protocol for quantitative imaging for molecular radiotherapy dosimetry

International Nuclear Information System (INIS)

Wevrett, J.; Fenwick, A.; Scuffham, J.; Nisbet, A.

2017-01-01

Within the field of molecular radiotherapy, there is a significant need for standardisation in dosimetry, in both quantitative imaging and dosimetry calculations. Currently, there are a wide range of techniques used by different clinical centres and as a result there is no means to compare patient doses between centres. To help address this need, a 3 year project was funded by the European Metrology Research Programme, and a number of clinical centres were involved in the project. One of the required outcomes of the project was to develop a calibration protocol for three dimensional quantitative imaging of volumes of interest. Two radionuclides were selected as being of particular interest: iodine-131 ( 131 I, used to treat thyroid disorders) and lutetium-177 ( 177 Lu, used to treat neuroendocrine tumours). A small volume of activity within a scatter medium (water), representing a lesion within a patient body, was chosen as the calibration method. To ensure ease of use in clinical centres, an “off-the-shelf” solution was proposed – to avoid the need for in-house manufacturing. The BIODEX elliptical Jaszczak phantom and 16 ml fillable sphere were selected. The protocol was developed for use on SPECT/CT gamma cameras only, where the CT dataset would be used to correct the imaging data for attenuation of the emitted photons within the phantom. The protocol corrects for scatter of emitted photons using the triple energy window correction technique utilised by most clinical systems. A number of clinical systems were tested in the development of this protocol, covering the major manufacturers of gamma camera generally used in Europe. Initial imaging was performed with 131 I and 177 Lu at a number of clinical centres, but due to time constraints in the project, some acquisitions were performed with 177 Lu only. The protocol is relatively simplistic, and does not account for the effects of dead-time in high activity patients, the presence of background activity

Spectro-refractometry of individual microscopic objects using swept-source quantitative phase imaging.

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Jung, Jae-Hwang; Jang, Jaeduck; Park, Yongkeun

2013-11-05

We present a novel spectroscopic quantitative phase imaging technique with a wavelength swept-source, referred to as swept-source diffraction phase microscopy (ssDPM), for quantifying the optical dispersion of microscopic individual samples. Employing the swept-source and the principle of common-path interferometry, ssDPM measures the multispectral full-field quantitative phase imaging and spectroscopic microrefractometry of transparent microscopic samples in the visible spectrum with a wavelength range of 450-750 nm and a spectral resolution of less than 8 nm. With unprecedented precision and sensitivity, we demonstrate the quantitative spectroscopic microrefractometry of individual polystyrene beads, 30% bovine serum albumin solution, and healthy human red blood cells.

MR imaging of Minamata disease. Qualitative and quantitative analysis

International Nuclear Information System (INIS)

Korogi, Yukunori; Takahashi, Mutsumasa; Sumi, Minako; Hirai, Toshinori; Okuda, Tomoko; Shinzato, Jintetsu; Okajima, Toru.

1994-01-01

Minamata disease (MD), a result of methylmercury poisoning, is a neurological illness caused by ingestion of contaminated seafood. We evaluated MR findings of patients with MD qualitatively and quantitatively. Magnetic resonance imaging at 1.5 Tesla was performed in seven patients with MD and in eight control subjects. All of our patients showed typical neurological findings like sensory disturbance, constriction of the visual fields, and ataxia. In the quantitative image analysis, inferior and middle parts of the cerebellar vermis and cerebellar hemispheres were significantly atrophic in comparison with the normal controls. There were no significant differences in measurements of the basis pontis, middle cerebellar peduncles, corpus callosum, or cerebral hemispheres between MD and the normal controls. The calcarine sulci and central sulci were significantly dilated, reflecting atrophy of the visual cortex and postcentral cortex, respectively. The lesions located in the calcarine area, cerebellum, and postcentral gyri were related to three characteristic manifestations of this disease, constriction of the visual fields, ataxia, and sensory disturbance, respectively. MR imaging has proved to be useful in evaluating the CNS abnormalities of methylmercury poisoning. (author)

Analysis of PET hypoxia imaging in the quantitative imaging for personalized cancer medicine program

International Nuclear Information System (INIS)

Yeung, Ivan; Driscoll, Brandon; Keller, Harald; Shek, Tina; Jaffray, David; Hedley, David

2014-01-01

Quantitative imaging is an important tool in clinical trials of testing novel agents and strategies for cancer treatment. The Quantitative Imaging Personalized Cancer Medicine Program (QIPCM) provides clinicians and researchers participating in multi-center clinical trials with a central repository for their imaging data. In addition, a set of tools provide standards of practice (SOP) in end-to-end quality assurance of scanners and image analysis. The four components for data archiving and analysis are the Clinical Trials Patient Database, the Clinical Trials PACS, the data analysis engine(s) and the high-speed networks that connect them. The program provides a suite of software which is able to perform RECIST, dynamic MRI, CT and PET analysis. The imaging data can be assessed securely from remote and analyzed by researchers with these software tools, or with tools provided by the users and installed at the server. Alternatively, QIPCM provides a service for data analysis on the imaging data according developed SOP. An example of a clinical study in which patients with unresectable pancreatic adenocarcinoma were studied with dynamic PET-FAZA for hypoxia measurement will be discussed. We successfully quantified the degree of hypoxia as well as tumor perfusion in a group of 20 patients in terms of SUV and hypoxic fraction. It was found that there is no correlation between bulk tumor perfusion and hypoxia status in this cohort. QIPCM also provides end-to-end QA testing of scanners used in multi-center clinical trials. Based on quality assurance data from multiple CT-PET scanners, we concluded that quality control of imaging was vital in the success in multi-center trials as different imaging and reconstruction parameters in PET imaging could lead to very different results in hypoxia imaging. (author)

Quantitative image analysis reveals distinct structural transitions during aging in Caenorhabditis elegans tissues.

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Josiah Johnston

2008-07-01

Full Text Available Aging is associated with functional and structural declines in many body systems, even in the absence of underlying disease. In particular, skeletal muscles experience severe declines during aging, a phenomenon termed sarcopenia. Despite the high incidence and severity of sarcopenia, little is known about contributing factors and development. Many studies focus on functional aspects of aging-related tissue decline, while structural details remain understudied. Traditional approaches for quantifying structural changes have assessed individual markers at discrete intervals. Such approaches are inadequate for the complex changes associated with aging. An alternative is to consider changes in overall morphology rather than in specific markers. We have used this approach to quantitatively track tissue architecture during adulthood and aging in the C. elegans pharynx, the neuromuscular feeding organ. Using pattern recognition to analyze aged-grouped pharynx images, we identified discrete step-wise transitions between distinct morphologies. The morphology state transitions were maintained in mutants with pharynx neurotransmission defects, although the pace of the transitions was altered. Longitudinal measurements of pharynx function identified a predictive relationship between mid-life pharynx morphology and function at later ages. These studies demonstrate for the first time that adult tissues undergo distinct structural transitions reflecting postdevelopmental events. The processes that underlie these architectural changes may contribute to increased disease risk during aging, and may be targets for factors that alter the aging rate. This work further demonstrates that pattern analysis of an image series offers a novel and generally accessible approach for quantifying morphological changes and identifying structural biomarkers.

Quantitative image analysis reveals distinct structural transitions during aging in Caenorhabditis elegans tissues.

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Johnston, Josiah; Iser, Wendy B; Chow, David K; Goldberg, Ilya G; Wolkow, Catherine A

2008-07-30

Aging is associated with functional and structural declines in many body systems, even in the absence of underlying disease. In particular, skeletal muscles experience severe declines during aging, a phenomenon termed sarcopenia. Despite the high incidence and severity of sarcopenia, little is known about contributing factors and development. Many studies focus on functional aspects of aging-related tissue decline, while structural details remain understudied. Traditional approaches for quantifying structural changes have assessed individual markers at discrete intervals. Such approaches are inadequate for the complex changes associated with aging. An alternative is to consider changes in overall morphology rather than in specific markers. We have used this approach to quantitatively track tissue architecture during adulthood and aging in the C. elegans pharynx, the neuromuscular feeding organ. Using pattern recognition to analyze aged-grouped pharynx images, we identified discrete step-wise transitions between distinct morphologies. The morphology state transitions were maintained in mutants with pharynx neurotransmission defects, although the pace of the transitions was altered. Longitudinal measurements of pharynx function identified a predictive relationship between mid-life pharynx morphology and function at later ages. These studies demonstrate for the first time that adult tissues undergo distinct structural transitions reflecting postdevelopmental events. The processes that underlie these architectural changes may contribute to increased disease risk during aging, and may be targets for factors that alter the aging rate. This work further demonstrates that pattern analysis of an image series offers a novel and generally accessible approach for quantifying morphological changes and identifying structural biomarkers.

Cadmium phytotoxicity: Quantitative sensitivity relationships between classical endpoints and antioxidative enzyme biomarkers

Energy Technology Data Exchange (ETDEWEB)

Rosa Correa, Albertina Xavier da [Centro de Ciencias Tecnologicas da Terra e do Mar, Universidade do Vale do Itajai, Rua Uruguai, 458, 88302-202 Itajai SC (Brazil); Roerig, Leonardo Rubi [Centro de Ciencias Tecnologicas da Terra e do Mar, Universidade do Vale do Itajai, Rua Uruguai, 458, 88302-202 Itajai SC (Brazil); Verdinelli, Miguel A. [Centro de Ciencias Tecnologicas da Terra e do Mar, Universidade do Vale do Itajai, Rua Uruguai, 458, 88302-202 Itajai SC (Brazil); Cotelle, Sylvie [Centre des Sciences de l' Environnement, Universite de Metz, 57000 Metz (France); Ferard, Jean-Francois [Centre des Sciences de l' Environnement, Universite de Metz, 57000 Metz (France); Radetski, Claudemir Marcos [Centro de Ciencias Tecnologicas da Terra e do Mar, Universidade do Vale do Itajai, Rua Uruguai, 458, 88302-202 Itajai SC (Brazil)]. E-mail: radetski@univali.br

2006-03-15

In this work, cadmium phytotoxicity and quantitative sensitivity relationships between different hierarchical endpoints in plants cultivated in a contaminated soil were studied. Thus, germination rate, biomass growth and antioxidative enzyme activity (i.e. superoxide dismutase, peroxidase, catalase and glutathione reductase) in three terrestrial plants (Avena sativa L., Brassica campestris L. cv. Chinensis, Lactuca sativa L. cv. hanson) were analyzed. Plant growth tests were carried out according to an International Standard Organization method and the results were analyzed by ANOVA followed by Williams' test. The concentration of Cd{sup 2+} that had the smallest observed significant negative effect (LOEC) on plant biomass was 6.25, 12.5 and 50 mg Cd/kg dry soil for lettuce, oat and Chinese cabbage, respectively. Activity of all enzymes studied increased significantly compared to enzyme activity in plant controls. For lettuce, LOEC values (mg Cd/kg dry soil) for enzymic activity ranged from 0.05 (glutathione reductase) to 0.39 (catalase). For oat, LOEC values (mg Cd/kg dry soil) ranged from 0.19 (for superoxide dismutase and glutathione reductase) to 0.39 (for catalase and peroxidase). For Chinese cabbage, LOEC values (mg Cd/kg dry soil) ranged from 0.19 (peroxidase, catalase and glutathione reductase) to 0.39 (superoxide dismutase). Classical (i.e. germination and biomass) and biochemical (i.e. enzyme activity) endpoints were compared to establish a sensitivity ranking, which was: enzyme activity > biomass > germination rate. For cadmium-soil contamination, the determination of quantitative sensitivity relationships (QSR) between classical and antioxidative enzyme biomarkers showed that the most sensitive plant species have, generally, the lowest QSR values.

Analysis of vaginal microbicide film hydration kinetics by quantitative imaging refractometry.

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Rinehart, Matthew; Grab, Sheila; Rohan, Lisa; Katz, David; Wax, Adam

2014-01-01

We have developed a quantitative imaging refractometry technique, based on holographic phase microscopy, as a tool for investigating microscopic structural changes in water-soluble polymeric materials. Here we apply the approach to analyze the structural degradation of vaginal topical microbicide films due to water uptake. We implemented transmission imaging of 1-mm diameter film samples loaded into a flow chamber with a 1.5×2 mm field of view. After water was flooded into the chamber, interference images were captured and analyzed to obtain high resolution maps of the local refractive index and subsequently the volume fraction and mass density of film material at each spatial location. Here, we compare the hydration dynamics of a panel of films with varying thicknesses and polymer compositions, demonstrating that quantitative imaging refractometry can be an effective tool for evaluating and characterizing the performance of candidate microbicide film designs for anti-HIV drug delivery.

Quantitative damage imaging using Lamb wave diffraction tomography

International Nuclear Information System (INIS)

Zhang Hai-Yan; Ruan Min; Zhu Wen-Fa; Chai Xiao-Dong

2016-01-01

In this paper, we investigate the diffraction tomography for quantitative imaging damages of partly through-thickness holes with various shapes in isotropic plates by using converted and non-converted scattered Lamb waves generated numerically. Finite element simulations are carried out to provide the scattered wave data. The validity of the finite element model is confirmed by the comparison of scattering directivity pattern (SDP) of circle blind hole damage between the finite element simulations and the analytical results. The imaging method is based on a theoretical relation between the one-dimensional (1D) Fourier transform of the scattered projection and two-dimensional (2D) spatial Fourier transform of the scattering object. A quantitative image of the damage is obtained by carrying out the 2D inverse Fourier transform of the scattering object. The proposed approach employs a circle transducer network containing forward and backward projections, which lead to so-called transmission mode (TMDT) and reflection mode diffraction tomography (RMDT), respectively. The reconstructed results of the two projections for a non-converted S0 scattered mode are investigated to illuminate the influence of the scattering field data. The results show that Lamb wave diffraction tomography using the combination of TMDT and RMDT improves the imaging effect compared with by using only the TMDT or RMDT. The scattered data of the converted A0 mode are also used to assess the performance of the diffraction tomography method. It is found that the circle and elliptical shaped damages can still be reasonably identified from the reconstructed images while the reconstructed results of other complex shaped damages like crisscross rectangles and racecourse are relatively poor. (special topics)

Quantitative SPECT brain imaging: Effects of attenuation and detector response

International Nuclear Information System (INIS)

Gilland, D.R.; Jaszczak, R.J.; Bowsher, J.E.; Turkington, T.G.; Liang, Z.; Greer, K.L.; Coleman, R.E.

1993-01-01

Two physical factors that substantially degrade quantitative accuracy in SPECT imaging of the brain are attenuation and detector response. In addition to the physical factors, random noise in the reconstructed image can greatly affect the quantitative measurement. The purpose of this work was to implement two reconstruction methods that compensate for attenuation and detector response, a 3D maximum likelihood-EM method (ML) and a filtered backprojection method (FB) with Metz filter and Chang attenuation compensation, and compare the methods in terms of quantitative accuracy and image noise. The methods were tested on simulated data of the 3D Hoffman brain phantom. The simulation incorporated attenuation and distance-dependent detector response. Bias and standard deviation of reconstructed voxel intensities were measured in the gray and white matter regions. The results with ML showed that in both the gray and white matter regions as the number of iterations increased, bias decreased and standard deviation increased. Similar results were observed with FB as the Metz filter power increased. In both regions, ML had smaller standard deviation than FB for a given bias. Reconstruction times for the ML method have been greatly reduced through efficient coding, limited source support, and by computing attenuation factors only along rays perpendicular to the detector

Identification and localization of trauma-related biomarkers using matrix assisted laser desorption/ionization imaging mass spectrometry

Science.gov (United States)

Jones, Kirstin; Reilly, Matthew A.; Glickman, Randolph D.

2017-02-01

Current treatments for ocular and optic nerve trauma are largely ineffective and may have adverse side effects; therefore, new approaches are needed to understand trauma mechanisms. Identification of trauma-related biomarkers may yield insights into the molecular aspects of tissue trauma that can contribute to the development of better diagnostics and treatments. The conventional approach for protein biomarker measurement largely relies on immunoaffinity methods that typically can only be applied to analytes for which antibodies or other targeting means are available. Matrix assisted laser-assisted desorption/ionization imaging mass spectrometry (MALDI-IMS) is a specialized application of mass spectrometry that not only is well suited to the discovery of novel or unanticipated biomarkers, but also provides information about the spatial localization of biomarkers in tissue. We have been using MALDI-IMS to find traumarelated protein biomarkers in retina and optic nerve tissue from animal models subjected to ocular injury produced by either blast overpressure or mechanical torsion. Work to date by our group, using MALDI-IMS, found that the pattern of protein expression is modified in the injured ocular tissue as soon as 24 hr post-injury, compared to controls. Specific proteins may be up- or down-regulated by trauma, suggesting different tissue responses to a given injury. Ongoing work is directed at identifying the proteins affected and mapping their expression in the ocular tissue, anticipating that systematic analysis can be used to identify targets for prospective therapies for ocular trauma.

WONOEP appraisal: Biomarkers of epilepsy-associated comorbidities.

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Ravizza, Teresa; Onat, Filiz Y; Brooks-Kayal, Amy R; Depaulis, Antoine; Galanopoulou, Aristea S; Mazarati, Andrey; Numis, Adam L; Sankar, Raman; Friedman, Alon

2017-03-01

Neurologic and psychiatric comorbidities are common in patients with epilepsy. Diagnostic, predictive, and pharmacodynamic biomarkers of such comorbidities do not exist. They may share pathogenetic mechanisms with epileptogenesis/ictogenesis, and as such are an unmet clinical need. The objectives of the subgroup on biomarkers of comorbidities at the XIII Workshop on the Neurobiology of Epilepsy (WONOEP) were to present the state-of-the-art recent research findings in the field that highlighting potential biomarkers for comorbidities in epilepsy. We review recent progress in the field, including molecular, imaging, and genetic biomarkers of comorbidities as discussed during the WONOEP meeting on August 31-September 4, 2015, in Heybeliada Island (Istanbul, Turkey). We further highlight new directions and concepts from studies on comorbidities and potential new biomarkers for the prediction, diagnosis, and treatment of epilepsy-associated comorbidities. The activation of various molecular signaling pathways such as the "Janus Kinase/Signal Transducer and Activator of Transcription," "mammalian Target of Rapamycin," and oxidative stress have been shown to correlate with the presence and severity of subsequent cognitive abnormalities. Furthermore, dysfunction in serotonergic transmission, hyperactivity of the hypothalamic-pituitary-adrenocortical axis, the role of the inflammatory cytokines, and the contributions of genetic factors have all recently been regarded as relevant for understanding epilepsy-associated depression and cognitive deficits. Recent evidence supports the utility of imaging studies as potential biomarkers. The role of such biomarker may be far beyond the diagnosis of comorbidities, as accumulating clinical data indicate that comorbidities can predict epilepsy outcomes. Future research is required to reveal whether molecular changes in specific signaling pathways or advanced imaging techniques could be detected in the clinical settings and correlate

Versatile quantitative phase imaging system applied to high-speed, low noise and multimodal imaging (Conference Presentation)

Science.gov (United States)

Federici, Antoine; Aknoun, Sherazade; Savatier, Julien; Wattellier, Benoit F.

2017-02-01

Quadriwave lateral shearing interferometry (QWLSI) is a well-established quantitative phase imaging (QPI) technique based on the analysis of interference patterns of four diffraction orders by an optical grating set in front of an array detector [1]. As a QPI modality, this is a non-invasive imaging technique which allow to measure the optical path difference (OPD) of semi-transparent samples. We present a system enabling QWLSI with high-performance sCMOS cameras [2] and apply it to perform high-speed imaging, low noise as well as multimodal imaging. This modified QWLSI system contains a versatile optomechanical device which images the optical grating near the detector plane. Such a device is coupled with any kind of camera by varying its magnification. In this paper, we study the use of a sCMOS Zyla5.5 camera from Andor along with our modified QWLSI system. We will present high-speed live cell imaging, up to 200Hz frame rate, in order to follow intracellular fast motions while measuring the quantitative phase information. The structural and density information extracted from the OPD signal is complementary to the specific and localized fluorescence signal [2]. In addition, QPI detects cells even when the fluorophore is not expressed. This is very useful to follow a protein expression with time. The 10 µm spatial pixel resolution of our modified QWLSI associated to the high sensitivity of the Zyla5.5 enabling to perform high quality fluorescence imaging, we have carried out multimodal imaging revealing fine structures cells, like actin filaments, merged with the morphological information of the phase. References [1]. P. Bon, G. Maucort, B. Wattellier, and S. Monneret, "Quadriwave lateral shearing interferometry for quantitative phase microscopy of living cells," Opt. Express, vol. 17, pp. 13080-13094, 2009. [2] P. Bon, S. Lécart, E. Fort and S. Lévêque-Fort, "Fast label-free cytoskeletal network imaging in living mammalian cells," Biophysical journal, 106

Fast automatic quantitative cell replication with fluorescent live cell imaging

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Wang Ching-Wei

2012-01-01

Full Text Available Abstract Background live cell imaging is a useful tool to monitor cellular activities in living systems. It is often necessary in cancer research or experimental research to quantify the dividing capabilities of cells or the cell proliferation level when investigating manipulations of the cells or their environment. Manual quantification of fluorescence microscopic image is difficult because human is neither sensitive to fine differences in color intensity nor effective to count and average fluorescence level among cells. However, auto-quantification is not a straightforward problem to solve. As the sampling location of the microscopy changes, the amount of cells in individual microscopic images varies, which makes simple measurement methods such as the sum of stain intensity values or the total number of positive stain within each image inapplicable. Thus, automated quantification with robust cell segmentation techniques is required. Results An automated quantification system with robust cell segmentation technique are presented. The experimental results in application to monitor cellular replication activities show that the quantitative score is promising to represent the cell replication level, and scores for images from different cell replication groups are demonstrated to be statistically significantly different using ANOVA, LSD and Tukey HSD tests (p-value Conclusion A robust automated quantification method of live cell imaging is built to measure the cell replication level, providing a robust quantitative analysis system in fluorescent live cell imaging. In addition, the presented unsupervised entropy based cell segmentation for live cell images is demonstrated to be also applicable for nuclear segmentation of IHC tissue images.

Rapid and Quantitative Assessment of Cancer Treatment Response Using In Vivo Bioluminescence Imaging

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Alnawaz Rehemtulla

2000-01-01

Full Text Available Current assessment of orthotopic tumor models in animals utilizes survival as the primary therapeutic end point. In vivo bioluminescence imaging (BLI is a sensitive imaging modality that is rapid and accessible, and may comprise an ideal tool for evaluating antineoplastic therapies [1 ]. Using human tumor cell lines constitutively expressing luciferase, the kinetics of tumor growth and response to therapy have been assessed in intraperitoneal [2], subcutaneous, and intravascular [3] cancer models. However, use of this approach for evaluating orthotopic tumor models has not been demonstrated. In this report, the ability of BLI to noninvasively quantitate the growth and therapeuticinduced cell kill of orthotopic rat brain tumors derived from 9L gliosarcoma cells genetically engineered to stably express firefly luciferase (9LLuc was investigated. Intracerebral tumor burden was monitored over time by quantitation of photon emission and tumor volume using a cryogenically cooled CCD camera and magnetic resonance imaging (MRI, respectively. There was excellent correlation (r=0.91 between detected photons and tumor volume. A quantitative comparison of tumor cell kill determined from serial MRI volume measurements and BLI photon counts following 1,3-bis(2-chloroethyl-1-nitrosourea (BCNU treatment revealed that both imaging modalities yielded statistically similar cell kill values (P=.951. These results provide direct validation of BLI imaging as a powerful and quantitative tool for the assessment of antineoplastic therapies in living animals.

Isotropic differential phase contrast microscopy for quantitative phase bio-imaging.

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Chen, Hsi-Hsun; Lin, Yu-Zi; Luo, Yuan

2018-05-16

Quantitative phase imaging (QPI) has been investigated to retrieve optical phase information of an object and applied to biological microscopy and related medical studies. In recent examples, differential phase contrast (DPC) microscopy can recover phase image of thin sample under multi-axis intensity measurements in wide-field scheme. Unlike conventional DPC, based on theoretical approach under partially coherent condition, we propose a new method to achieve isotropic differential phase contrast (iDPC) with high accuracy and stability for phase recovery in simple and high-speed fashion. The iDPC is simply implemented with a partially coherent microscopy and a programmable thin-film transistor (TFT) shield to digitally modulate structured illumination patterns for QPI. In this article, simulation results show consistency of our theoretical approach for iDPC under partial coherence. In addition, we further demonstrate experiments of quantitative phase images of a standard micro-lens array, as well as label-free live human cell samples. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative assessment of videolaryngostroboscopic images in patients with glottic pathologies.

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Niebudek-Bogusz, Ewa; Kopczynski, Bartosz; Strumillo, Pawel; Morawska, Joanna; Wiktorowicz, Justyna; Sliwinska-Kowalska, Mariola

2017-07-01

Digital imaging techniques enable exploration of novel visualization modalities of the vocal folds during phonation and definition of parameters, facilitating more precise diagnosis of voice disorders. Application of computer vision algorithms for analysis of videolaryngostroboscopic (VLS) images aimed at qualitative and quantitative description of phonatory vibrations. VLS examinations were conducted for 45 females, including 15 subjects with vocal nodules, 15 subjects with glottal incompetence, and 15 normophonic females. The recorded VLS images were preprocessed, the glottis area was segmented out, and the glottal cycles were identified. The glottovibrograms were built, and then the glottal area waveforms (GAW) were quantitatively described by computing the following parameters: open quotient (OQ), closing quotient (CQ), speed quotient (SQ), minimal relative glottal area (MRGA), and a new parameter termed closure difference index (CDI). Profiles of the glottal widths assessed along the glottal length differentiated the study groups (P diagnostics. Results of the performed ROC curve analysis suggest that the evaluated parameters can distinguish patients with voice disorders from normophonic subjects.

Analysis of vaginal microbicide film hydration kinetics by quantitative imaging refractometry.

Directory of Open Access Journals (Sweden)

Matthew Rinehart

Full Text Available We have developed a quantitative imaging refractometry technique, based on holographic phase microscopy, as a tool for investigating microscopic structural changes in water-soluble polymeric materials. Here we apply the approach to analyze the structural degradation of vaginal topical microbicide films due to water uptake. We implemented transmission imaging of 1-mm diameter film samples loaded into a flow chamber with a 1.5×2 mm field of view. After water was flooded into the chamber, interference images were captured and analyzed to obtain high resolution maps of the local refractive index and subsequently the volume fraction and mass density of film material at each spatial location. Here, we compare the hydration dynamics of a panel of films with varying thicknesses and polymer compositions, demonstrating that quantitative imaging refractometry can be an effective tool for evaluating and characterizing the performance of candidate microbicide film designs for anti-HIV drug delivery.

Quantitative imaging of coronary blood flow

Directory of Open Access Journals (Sweden)

Adam M. Alessio

2010-04-01

Full Text Available Adam M. Alessio received his PhD in Electrical Engineering from the University of Notre Dame in 2003. During his graduate studies he developed tomographic reconstruction methods for correlated data and helped construct a high-resolution PET system. He is currently a Research Assistant Professor in Radiology at the University of Washington. His research interests focus on improved data processing and reconstruction algorithms for PET/CT systems with an emphasis on quantitative imaging. Erik Butterworth recieved the BA degree in Mathematics from the University of Chicago in 1977. Between 1977 and 1987 he worked as a computer programmer/analyst for several small commercial software firms. Since 1988, he has worked as a software engineer on various research projects at the University of Washington. Between 1988 and 1993 he developed a real-time data aquisition for the analysis of estuarine sediment transport in the department of Geophysics. Between 1988 and 2002 he developed I4, a system for the display and analysis of cardic PET images in the department of Cardiology. Since 1993 he has worked on physiological simulation systems (XSIM from 1993 to 1999, JSim since 1999 at the National Simulation Resource Facility in Cirulatory Mass Transport and Exchange, in the Department of Bioengineering. His research interests include simulation systems and medical imaging. James H. Caldwell, MD, University of Missouri-Columbia 1970, is Professor of Medicine (Cardiology and Radiology and Adjunct Professor of Bioengineering at the University of Washington School of Medicine and Acting Head, Division of Cardiology and Director of Nuclear Cardiology for the University of Washington Hospitals, Seattle WA, USA. James B. Bassingthwaighte, MD, Toronto 1955, PhD Mayo Grad Sch Med 1964, was Professor of Physiology and of Medicine at Mayo Clinic until 1975 when he moved to the University of Washington to chair Bioengineering. He is Professor of Bioengineering and

Real Time Imaging of Biomarkers in the Parkinson's Brain Using Mini-Implantable Biosensors. II. Pharmaceutical Therapy with Bromocriptine

Directory of Open Access Journals (Sweden)

Patricia A. Broderick

2009-12-01

Full Text Available We used Neuromolecular Imaging (NMI and trademarked BRODERICK PROBE® mini-implantable biosensors, to selectively and separately detect neurotransmitters in vivo, on line, within seconds in the dorsal striatal brain of the Parkinson’s Disease (PD animal model. We directly compared our results derived from PD to the normal striatal brain of the non-Parkinson’s Disease (non-PD animal. This advanced biotechnology enabled the imaging of dopamine (DA, serotonin (5-HT, homovanillic acid (HVA a metabolite of DA, L-tryptophan (L-TP a precursor to 5-HT and peptides, dynorphin A 1-17 (Dyn A and somatostatin (somatostatin releasing inhibitory factor (SRIF. Each neurotransmitter and neurochemical was imaged at a signature electroactive oxidation/half-wave potential in dorsal striatum of the PD as compared with the non-PD animal. Both endogenous and bromocriptine-treated neurochemical profiles in PD and non-PD were imaged using the same experimental paradigm and detection sensitivities. Results showed that we have found significant neurotransmitter peptide biomarkers in the dorsal striatal brain of endogenous and bromocriptine-treated PD animals. The peptide biomarkers were not imaged in dorsal striatal brain of non-PD animals, either endogenously or bromocriptine-treated. These findings provide new pharmacotherapeutic strategies for PD patients. Thus, our findings are highly applicable to the clinical treatment of PD.

Multi-component quantitative magnetic resonance imaging by phasor representation

NARCIS (Netherlands)

Vergeldt, F.J.; Prusova, A.; Fereidouni, F.; Amerongen, H.V.; As, H. Van; Scheenen, T.W.J.; Bader, A.N.

2017-01-01

Quantitative magnetic resonance imaging (qMRI) is a versatile, non-destructive and non-invasive tool in life, material, and medical sciences. When multiple components contribute to the signal in a single pixel, however, it is difficult to quantify their individual contributions and characteristic

Multiparametric Quantitative Ultrasound Imaging in Assessment of Chronic Kidney Disease.

Science.gov (United States)

Gao, Jing; Perlman, Alan; Kalache, Safa; Berman, Nathaniel; Seshan, Surya; Salvatore, Steven; Smith, Lindsey; Wehrli, Natasha; Waldron, Levi; Kodali, Hanish; Chevalier, James

2017-11-01

To evaluate the value of multiparametric quantitative ultrasound imaging in assessing chronic kidney disease (CKD) using kidney biopsy pathologic findings as reference standards. We prospectively measured multiparametric quantitative ultrasound markers with grayscale, spectral Doppler, and acoustic radiation force impulse imaging in 25 patients with CKD before kidney biopsy and 10 healthy volunteers. Based on all pathologic (glomerulosclerosis, interstitial fibrosis/tubular atrophy, arteriosclerosis, and edema) scores, the patients with CKD were classified into mild (no grade 3 and quantitative ultrasound parameters included kidney length, cortical thickness, pixel intensity, parenchymal shear wave velocity, intrarenal artery peak systolic velocity (PSV), end-diastolic velocity (EDV), and resistive index. We tested the difference in quantitative ultrasound parameters among mild CKD, moderate to severe CKD, and healthy controls using analysis of variance, analyzed correlations of quantitative ultrasound parameters with pathologic scores and the estimated glomerular filtration rate (GFR) using Pearson correlation coefficients, and examined the diagnostic performance of quantitative ultrasound parameters in determining moderate CKD and an estimated GFR of less than 60 mL/min/1.73 m 2 using receiver operating characteristic curve analysis. There were significant differences in cortical thickness, pixel intensity, PSV, and EDV among the 3 groups (all P quantitative ultrasound parameters, the top areas under the receiver operating characteristic curves for PSV and EDV were 0.88 and 0.97, respectively, for determining pathologic moderate to severe CKD, and 0.76 and 0.86 for estimated GFR of less than 60 mL/min/1.73 m 2 . Moderate to good correlations were found for PSV, EDV, and pixel intensity with pathologic scores and estimated GFR. The PSV, EDV, and pixel intensity are valuable in determining moderate to severe CKD. The value of shear wave velocity in

Multi-component quantitative magnetic resonance imaging by phasor representation

NARCIS (Netherlands)

Vergeldt, Frank J.; Prusova, Alena; Fereidouni, Farzad; Amerongen, Van Herbert; As, Van Henk; Scheenen, Tom W.J.; Bader, Arjen N.

2017-01-01

Quantitative magnetic resonance imaging (qMRI) is a versatile, non-destructive and non-invasive tool in life, material, and medical sciences. When multiple components contribute to the signal in a single pixel, however, it is difficult to quantify their individual contributions and characteristic

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine

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Chen, Zhidan; Coy, Stephen L.; Pannkuk, Evan L.; Laiakis, Evagelia C.; Fornace, Albert J.; Vouros, Paul

2018-05-01

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. [Figure not available: see fulltext.

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine.

Science.gov (United States)

Chen, Zhidan; Coy, Stephen L; Pannkuk, Evan L; Laiakis, Evagelia C; Fornace, Albert J; Vouros, Paul

2018-05-07

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. Graphical Abstract.

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis.

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Attiyeh, Marc A; Chakraborty, Jayasree; Doussot, Alexandre; Langdon-Embry, Liana; Mainarich, Shiana; Gönen, Mithat; Balachandran, Vinod P; D'Angelica, Michael I; DeMatteo, Ronald P; Jarnagin, William R; Kingham, T Peter; Allen, Peter J; Simpson, Amber L; Do, Richard K

2018-04-01

Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients. A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation. A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 [integrated Brier score (IBS) 0.224] on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data. We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.

A novel iris transillumination grading scale allowing flexible assessment with quantitative image analysis and visual matching.

Science.gov (United States)

Wang, Chen; Brancusi, Flavia; Valivullah, Zaheer M; Anderson, Michael G; Cunningham, Denise; Hedberg-Buenz, Adam; Power, Bradley; Simeonov, Dimitre; Gahl, William A; Zein, Wadih M; Adams, David R; Brooks, Brian

2018-01-01

To develop a sensitive scale of iris transillumination suitable for clinical and research use, with the capability of either quantitative analysis or visual matching of images. Iris transillumination photographic images were used from 70 study subjects with ocular or oculocutaneous albinism. Subjects represented a broad range of ocular pigmentation. A subset of images was subjected to image analysis and ranking by both expert and nonexpert reviewers. Quantitative ordering of images was compared with ordering by visual inspection. Images were binned to establish an 8-point scale. Ranking consistency was evaluated using the Kendall rank correlation coefficient (Kendall's tau). Visual ranking results were assessed using Kendall's coefficient of concordance (Kendall's W) analysis. There was a high degree of correlation among the image analysis, expert-based and non-expert-based image rankings. Pairwise comparisons of the quantitative ranking with each reviewer generated an average Kendall's tau of 0.83 ± 0.04 (SD). Inter-rater correlation was also high with Kendall's W of 0.96, 0.95, and 0.95 for nonexpert, expert, and all reviewers, respectively. The current standard for assessing iris transillumination is expert assessment of clinical exam findings. We adapted an image-analysis technique to generate quantitative transillumination values. Quantitative ranking was shown to be highly similar to a ranking produced by both expert and nonexpert reviewers. This finding suggests that the image characteristics used to quantify iris transillumination do not require expert interpretation. Inter-rater rankings were also highly similar, suggesting that varied methods of transillumination ranking are robust in terms of producing reproducible results.

Refining prognosis in patients with hepatocellular carcinoma through incorporation of metabolic imaging biomarkers

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Takeuchi, Satoshi [Hokkaido University Graduate School of Medicine, Department of Medical Oncology, Sapporo (Japan); The University of Texas MD Anderson Cancer Center, Department of Nuclear Medicine, Houston, TX (United States); Rohren, Eric M. [The University of Texas MD Anderson Cancer Center, Department of Nuclear Medicine, Houston, TX (United States); Baylor College of Medicine, Department of Radiology, Houston, TX (United States); Abdel-Wahab, Reham [The University of Texas MD Anderson Cancer Center, Department of Gastrointestinal Medical Oncology, Houston, TX (United States); Assiut University Hospital, Clinical Oncology Department, Assiut (Egypt); Xiao, Lianchun; Morris, Jeffrey S. [The University of Texas MD Anderson Cancer Center, Department of Biostatistics, Houston, TX (United States); Macapinlac, Homer A. [The University of Texas MD Anderson Cancer Center, Department of Nuclear Medicine, Houston, TX (United States); Hassan, Manal M. [Baylor College of Medicine, Department of Radiology, Houston, TX (United States); Kaseb, Ahmed O. [The University of Texas MD Anderson Cancer Center, Department of Gastrointestinal Medical Oncology, Houston, TX (United States)

2017-06-15

{sup 18}F-fluorodeoxyglucose positron emission tomopraphy/computed tomography (FDGPET/CT) has been proven to be useful for imaging many types of cancer; however, its role is not well defined in hepatocellular carcinoma (HCC). We assessed the prognostic value of metabolic imaging biomarkers as established by baseline pretreatment FDG PET/CT in patients with HCC. We retrospectively analyzed the records of patients with HCC who underwent FDG PET/CT before initial treatment from May 2013 through May 2014. Four PET/CT parameters were measured: maximum standardized uptake value (SUV{sub max}), total lesion glycolysis (TLG), metabolic tumor volume (MTV), and tumor-to-normal-liver SUV ratio (TNR). Optimal cut-off values for the PET/CT parameters to stratify patients in terms of overall survival (OS) were determined. Multivariate analysis was performed to determine whether the PET/CT parameters could add to the prognostic value of the Cancer of the Liver Italian Program (CLIP) scoring system and the Barcelona-Clinic Liver Cancer (BCLC) staging system. The analysis included 56 patients. Univariate analysis of the association between OS and continuous variables, including the PET/CT parameters SUV{sub max}, TLG, tumor size, total bilirubin level, and alkaline phosphatase level were significant predictors of OS. SUV{sub max} ≥ 11.7, TLG ≥ 1,341, MTV ≥ 230 mL, and TNR ≥ 4.8 were identified as cut-off values. Multivariate analysis revealed that SUV{sub max} ≥ 11.7 and TNR ≥ 4.8 were independent factors predicting a poor prognosis in both the CLIP scoring system and the BCLC staging system, as was TLG in the BCLC staging system. Pretreatment FDG PET/CT in patients with HCC can add to the prognostic value of standard clinical measures. Incorporation of imaging biomarkers derived from FDG PET/CT into HCC staging systems should be considered. (orig.)

Some selected quantitative methods of thermal image analysis in Matlab.

Science.gov (United States)

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative Myocardial Perfusion with Dynamic Contrast-Enhanced Imaging in MRI and CT: Theoretical Models and Current Implementation

Directory of Open Access Journals (Sweden)

G. J. Pelgrim

2016-01-01

Full Text Available Technological advances in magnetic resonance imaging (MRI and computed tomography (CT, including higher spatial and temporal resolution, have made the prospect of performing absolute myocardial perfusion quantification possible, previously only achievable with positron emission tomography (PET. This could facilitate integration of myocardial perfusion biomarkers into the current workup for coronary artery disease (CAD, as MRI and CT systems are more widely available than PET scanners. Cardiac PET scanning remains expensive and is restricted by the requirement of a nearby cyclotron. Clinical evidence is needed to demonstrate that MRI and CT have similar accuracy for myocardial perfusion quantification as PET. However, lack of standardization of acquisition protocols and tracer kinetic model selection complicates comparison between different studies and modalities. The aim of this overview is to provide insight into the different tracer kinetic models for quantitative myocardial perfusion analysis and to address typical implementation issues in MRI and CT. We compare different models based on their theoretical derivations and present the respective consequences for MRI and CT acquisition parameters, highlighting the interplay between tracer kinetic modeling and acquisition settings.

ADC texture—An imaging biomarker for high-grade glioma?

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Brynolfsson, Patrik; Hauksson, Jón; Karlsson, Mikael; Garpebring, Anders; Nyholm, Tufve, E-mail: tufve.nyholm@radfys.umu.se [Department of Radiation Sciences, Radiation Physics, Umeå University, Umeå SE-901 87 (Sweden); Nilsson, David; Trygg, Johan [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, Umeå SE-901 87 (Sweden); Henriksson, Roger [Department of Radiation Sciences, Oncology, Umeå University, Umeå SE-901 87, Sweden and Regionalt Cancercentrum Stockholm, Karolinska Universitetssjukhuset, Solna, Stockholm SE-102 39 (Sweden); Birgander, Richard [Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå SE-901 87 (Sweden); Asklund, Thomas [Department of Radiation Sciences, Oncology, Umeå University, Umeå SE-901 87 (Sweden)

2014-10-15

Purpose: Survival for high-grade gliomas is poor, at least partly explained by intratumoral heterogeneity contributing to treatment resistance. Radiological evaluation of treatment response is in most cases limited to assessment of tumor size months after the initiation of therapy. Diffusion-weighted magnetic resonance imaging (MRI) and its estimate of the apparent diffusion coefficient (ADC) has been widely investigated, as it reflects tumor cellularity and proliferation. The aim of this study was to investigate texture analysis of ADC images in conjunction with multivariate image analysis as a means for identification of pretreatment imaging biomarkers. Methods: Twenty-three consecutive high-grade glioma patients were treated with radiotherapy (2 Gy/60 Gy) with concomitant and adjuvant temozolomide. ADC maps and T1-weighted anatomical images with and without contrast enhancement were collected prior to treatment, and (residual) tumor contrast enhancement was delineated. A gray-level co-occurrence matrix analysis was performed on the ADC maps in a cuboid encapsulating the tumor in coronal, sagittal, and transversal planes, giving a total of 60 textural descriptors for each tumor. In addition, similar examinations and analyses were performed at day 1, week 2, and week 6 into treatment. Principal component analysis (PCA) was applied to reduce dimensionality of the data, and the five largest components (scores) were used in subsequent analyses. MRI assessment three months after completion of radiochemotherapy was used for classifying tumor progression or regression. Results: The score scatter plots revealed that the first, third, and fifth components of the pretreatment examinations exhibited a pattern that strongly correlated to survival. Two groups could be identified: one with a median survival after diagnosis of 1099 days and one with 345 days, p = 0.0001. Conclusions: By combining PCA and texture analysis, ADC texture characteristics were identified, which seems

Using Non-Invasive Multi-Spectral Imaging to Quantitatively Assess Tissue Vasculature

Energy Technology Data Exchange (ETDEWEB)

Vogel, A; Chernomordik, V; Riley, J; Hassan, M; Amyot, F; Dasgeb, B; Demos, S G; Pursley, R; Little, R; Yarchoan, R; Tao, Y; Gandjbakhche, A H

2007-10-04

This research describes a non-invasive, non-contact method used to quantitatively analyze the functional characteristics of tissue. Multi-spectral images collected at several near-infrared wavelengths are input into a mathematical optical skin model that considers the contributions from different analytes in the epidermis and dermis skin layers. Through a reconstruction algorithm, we can quantify the percent of blood in a given area of tissue and the fraction of that blood that is oxygenated. Imaging normal tissue confirms previously reported values for the percent of blood in tissue and the percent of blood that is oxygenated in tissue and surrounding vasculature, for the normal state and when ischemia is induced. This methodology has been applied to assess vascular Kaposi's sarcoma lesions and the surrounding tissue before and during experimental therapies. The multi-spectral imaging technique has been combined with laser Doppler imaging to gain additional information. Results indicate that these techniques are able to provide quantitative and functional information about tissue changes during experimental drug therapy and investigate progression of disease before changes are visibly apparent, suggesting a potential for them to be used as complementary imaging techniques to clinical assessment.

Magnetic resonance imaging and liver histology as biomarkers of hepatic steatosis in children with nonalcoholic fatty liver disease.

Science.gov (United States)

Schwimmer, Jeffrey B; Middleton, Michael S; Behling, Cynthia; Newton, Kimberly P; Awai, Hannah I; Paiz, Melissa N; Lam, Jessica; Hooker, Jonathan C; Hamilton, Gavin; Fontanesi, John; Sirlin, Claude B

2015-06-01

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in children. In order to advance the field of NAFLD, noninvasive imaging methods for measuring liver fat are needed. Advanced magnetic resonance imaging (MRI) has shown great promise for the quantitative assessment of hepatic steatosis but has not been validated in children. Therefore, this study was designed to evaluate the correlation and diagnostic accuracy of MRI-estimated liver proton density fat fraction (PDFF), a biomarker for hepatic steatosis, compared to histologic steatosis grade in children. The study included 174 children with a mean age of 14.0 years. Liver PDFF estimated by MRI was significantly (P steatosis grade. The correlation of MRI-estimated liver PDFF and steatosis grade was influenced by both sex and fibrosis stage. The correlation was significantly (P steatosis and mild steatosis ranged from 0.69 to 0.82. The overall accuracy of predicting the histologic steatosis grade from MRI-estimated liver PDFF was 56%. No single threshold had sufficient sensitivity and specificity to be considered diagnostic for an individual child. Advanced magnitude-based MRI can be used to estimate liver PDFF in children, and those PDFF values correlate well with steatosis grade by liver histology. Thus, magnitude-based MRI has the potential for clinical utility in the evaluation of NAFLD, but at this time no single threshold value has sufficient accuracy to be considered diagnostic for an individual child. © 2015 by the American Association for the Study of Liver Diseases.

Quantitative assessment for pneumoconiosis severity diagnosis using 3D CT images

Science.gov (United States)

Hino, Koki; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Kato, Katsuya; Kishimoto, Takumi; Ashizawa, Kazuto

2018-02-01

Pneumoconiosis is an occupational respiratory illness that occur by inhaling dust to the lungs. 240,000 participants are screened for diagnosis of pneumoconiosis every year in Japan. Radiograph is used for staging of severity rate in pneumoconiosis worldwide. CT imaging is useful for the differentiation of requirements for industrial accident approval because it can detect small lesions in comparison with radiograph. In this paper, we extracted lung nodules from 3D pneumoconiosis CT images by two manual processes and automatic process, and created a database of pneumoconiosis CT images. We used the database to analyze, compare, and evaluate visual diagnostic results of radiographs and quantitative assessment (number, size and volume) of lung nodules. This method was applied to twenty pneumoconiosis patients. Initial results showed that the proposed method can assess severity rate in pneumoconiosis quantitatively. This study demonstrates effectiveness on diagnosis and prognosis of pneumoconiosis in CT screening.

Cell-based quantification of biomarkers from an ultra-fast microfluidic immunofluorescent staining: application to human breast cancer cell lines

Science.gov (United States)

Migliozzi, D.; Nguyen, H. T.; Gijs, M. A. M.

2018-02-01

Immunohistochemistry (IHC) is one of the main techniques currently used in the clinics for biomarker characterization. It consists in colorimetric labeling with specific antibodies followed by microscopy analysis. The results are then used for diagnosis and therapeutic targeting. Well-known drawbacks of such protocols are their limited accuracy and precision, which prevent the clinicians from having quantitative and robust IHC results. With our work, we combined rapid microfluidic immunofluorescent staining with efficient image-based cell segmentation and signal quantification to increase the robustness of both experimental and analytical protocols. The experimental protocol is very simple and based on fast-fluidic-exchange in a microfluidic chamber created on top of the formalin-fixed-paraffin-embedded (FFPE) slide by clamping it a silicon chip with a polydimethyl siloxane (PDMS) sealing ring. The image-processing protocol is based on enhancement and subsequent thresholding of the local contrast of the obtained fluorescence image. As a case study, given that the human epidermal growth factor receptor 2 (HER2) protein is often used as a biomarker for breast cancer, we applied our method to HER2+ and HER2- cell lines. We report very fast (5 minutes) immunofluorescence staining of both HER2 and cytokeratin (a marker used to define the tumor region) on FFPE slides. The image-processing program can segment cells correctly and give a cell-based quantitative immunofluorescent signal. With this method, we found a reproducible well-defined separation for the HER2-to-cytokeratin ratio for positive and negative control samples.

Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET

International Nuclear Information System (INIS)

Ahn, Sangtae; Asma, Evren; Cheng, Lishui; Manjeshwar, Ravindra M; Ross, Steven G; Miao, Jun; Jin, Xiao; Wollenweber, Scott D

2015-01-01

Ordered subset expectation maximization (OSEM) is the most widely used algorithm for clinical PET image reconstruction. OSEM is usually stopped early and post-filtered to control image noise and does not necessarily achieve optimal quantitation accuracy. As an alternative to OSEM, we have recently implemented a penalized likelihood (PL) image reconstruction algorithm for clinical PET using the relative difference penalty with the aim of improving quantitation accuracy without compromising visual image quality. Preliminary clinical studies have demonstrated visual image quality including lesion conspicuity in images reconstructed by the PL algorithm is better than or at least as good as that in OSEM images. In this paper we evaluate lesion quantitation accuracy of the PL algorithm with the relative difference penalty compared to OSEM by using various data sets including phantom data acquired with an anthropomorphic torso phantom, an extended oval phantom and the NEMA image quality phantom; clinical data; and hybrid clinical data generated by adding simulated lesion data to clinical data. We focus on mean standardized uptake values and compare them for PL and OSEM using both time-of-flight (TOF) and non-TOF data. The results demonstrate improvements of PL in lesion quantitation accuracy compared to OSEM with a particular improvement in cold background regions such as lungs. (paper)

The use of the lumbosacral enlargement as an intrinsic imaging biomarker: feasibility of grey matter and white matter cross-sectional area measurements using MRI at 3T.

Directory of Open Access Journals (Sweden)

Marios C Yiannakas

Full Text Available Histopathological studies have demonstrated the involvement of spinal cord grey matter (GM and white matter (WM in several diseases and recent research has suggested the use of magnetic resonance imaging (MRI as a promising tool for in vivo assessment of the upper spinal cord. However, many neurological conditions would benefit from quantitative assessment of tissue integrity at different levels and relatively little work has been done, mainly due to technical challenges associated with imaging the lower spinal cord. In this study, the value of the lumbosacral enlargement (LSE as an intrinsic imaging biomarker was determined by exploring the feasibility of obtaining within it reliable GM and WM cross-sectional area (CSA measurements by means of a commercially available MRI system at 3 tesla (T. 10 healthy volunteers (mean age 27.5 years, 6 female gave written informed consent and high resolution images of the LSE were acquired and analysed using an optimised MRI acquisition and analysis protocol. GM and WM mean CSA measurements were obtained from a 15 mm section at the level of the LSE and the reproducibility of the measurements was determined by means of scan-rescan, intra- and inter-observer assessments. Mean (±SD LSE cross-sectional area (LSE-CSA was 62.3 (±4.1 mm2 and mean (±SD LSE grey matter cross-sectional area (LSE-GM-CSA was 19.8 (±3.3 mm2. The mean scan-rescan, intra- and inter-observer % coefficient of variation (COV for measuring the LSE-CSA were 2%, 2% and 2.5%, respectively and for measuring the LSE-GM-CSA were 7.8%, 8% and 8.6%, respectively. This study has shown that the LSE can be used reliably as an intrinsic imaging biomarker. The method presented here can be potentially extended to study the LSE in the diseased state and could provide a solid foundation for subsequent multi-parametric MRI investigations.

Nuclear medicine and imaging research. Instrumentation and quantitative methods of evaluation. Progress report, January 15, 1984-January 14, 1985

International Nuclear Information System (INIS)

Beck, R.N.; Cooper, M.D.

1984-09-01

This program addresses problems involving the basic science and technology of radioactive tracer methods as they relate to nuclear medicine and imaging. The broad goal is to develop new instruments and methods for image formation, processing, quantitation and display, so as to maximize the diagnostic information per unit of absorbed radiation dose to the patient. Project I addresses problems associated with the quantitative imaging of single-photon emitters; Project II addresses similar problems associated with the quantitative imaging of positron emitters; Project III addresses methodological problems associated with the quantitative evaluation of the efficacy of diagnostic imaging procedures

A Quantitative Three-Dimensional Image Analysis Tool for Maximal Acquisition of Spatial Heterogeneity Data.

Science.gov (United States)

Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios

2017-02-01

Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.

Biomarkers in Prostate Cancer Epidemiology

Directory of Open Access Journals (Sweden)

Mudit Verma

2011-09-01

Full Text Available Understanding the etiology of a disease such as prostate cancer may help in identifying populations at high risk, timely intervention of the disease, and proper treatment. Biomarkers, along with exposure history and clinical data, are useful tools to achieve these goals. Individual risk and population incidence of prostate cancer result from the intervention of genetic susceptibility and exposure. Biochemical, epigenetic, genetic, and imaging biomarkers are used to identify people at high risk for developing prostate cancer. In cancer epidemiology, epigenetic biomarkers offer advantages over other types of biomarkers because they are expressed against a person’s genetic background and environmental exposure, and because abnormal events occur early in cancer development, which includes several epigenetic alterations in cancer cells. This article describes different biomarkers that have potential use in studying the epidemiology of prostate cancer. We also discuss the characteristics of an ideal biomarker for prostate cancer, and technologies utilized for biomarker assays. Among epigenetic biomarkers, most reports indicate GSTP1 hypermethylation as the diagnostic marker for prostate cancer; however, NKX2-5, CLSTN1, SPOCK2, SLC16A12, DPYS, and NSE1 also have been reported to be regulated by methylation mechanisms in prostate cancer. Current challenges in utilization of biomarkers in prostate cancer diagnosis and epidemiologic studies and potential solutions also are discussed.

Quantitative MR imaging in fracture dating--Initial results.

Science.gov (United States)

Baron, Katharina; Neumayer, Bernhard; Widek, Thomas; Schick, Fritz; Scheicher, Sylvia; Hassler, Eva; Scheurer, Eva

2016-04-01

For exact age determinations of bone fractures in a forensic context (e.g. in cases of child abuse) improved knowledge of the time course of the healing process and use of non-invasive modern imaging technology is of high importance. To date, fracture dating is based on radiographic methods by determining the callus status and thereby relying on an expert's experience. As a novel approach, this study aims to investigate the applicability of magnetic resonance imaging (MRI) for bone fracture dating by systematically investigating time-resolved changes in quantitative MR characteristics after a fracture event. Prior to investigating fracture healing in children, adults were examined for this study in order to test the methodology for this application. Altogether, 31 MR examinations in 17 subjects (♀: 11 ♂: 6; median age 34 ± 15 y, scanned 1-5 times over a period of up to 200 days after the fracture event) were performed on a clinical 3T MR scanner (TimTrio, Siemens AG, Germany). All subjects were treated conservatively for a fracture in either a long bone or in the collar bone. Both, qualitative and quantitative MR measurements were performed in all subjects. MR sequences for a quantitative measurement of relaxation times T1 and T2 in the fracture gap and musculature were applied. Maps of quantitative MR parameters T1, T2, and magnetisation transfer ratio (MTR) were calculated and evaluated by investigating changes over time in the fractured area by defined ROIs. Additionally, muscle areas were examined as reference regions to validate this approach. Quantitative evaluation of 23 MR data sets (12 test subjects, ♀: 7 ♂: 5) showed an initial peak in T1 values in the fractured area (T1=1895 ± 607 ms), which decreased over time to a value of 1094 ± 182 ms (200 days after the fracture event). T2 values also peaked for early-stage fractures (T2=115 ± 80 ms) and decreased to 73 ± 33 ms within 21 days after the fracture event. After that time point, no

Monitoring and quantitative assessment of tumor burden using in vivo bioluminescence imaging

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Chen, C.-C. [Cancer Research Division, National Health Research Institute, Miaoli 350, Taiwan (China); Hwang, Jeng-Jong [Institute of Radiological Sciences, National Yang-Ming University, Taipei 112, Taiwan (China)]. E-mail: jjhwang@ym.edu.tw; Ting, G. [Cancer Research Division, National Health Research Institute, Miaoli 350, Taiwan (China); Tseng, Y.-L. [Taiwan Liposome Company, Taipei 115, Taiwan (China); Wang, S.-J. [Department of Nuclear Medicine, Veterans General Hospital, Taipei 112, Taiwan (China); Whang-Peng, J. [Cancer Research Division, National Health Research Institute, Miaoli 350, Taiwan (China)

2007-02-01

In vivo bioluminescence imaging (BLI) is a sensitive imaging modality that is rapid and accessible, and may comprise an ideal tool for evaluating tumor growth. In this study, the kinetic of tumor growth has been assessed in C26 colon carcinoma bearing BALB/c mouse model. The ability of BLI to noninvasively quantitate the growth of subcutaneous tumors transplanted with C26 cells genetically engineered to stably express firefly luciferase and herpes simplex virus type-1 thymidine kinase (C26/tk-luc). A good correlation (R {sup 2}=0.998) of photon emission to the cell number was found in vitro. Tumor burden and tumor volume were monitored in vivo over time by quantitation of photon emission using Xenogen IVIS 50 and standard external caliper measurement, respectively. At various time intervals, tumor-bearing mice were imaged to determine the correlation of in vivo BLI to tumor volume. However, a correlation of BLI to tumor volume was observed when tumor volume was smaller than 1000 mm{sup 3} (R {sup 2}=0.907). {gamma} Scintigraphy combined with [{sup 131}I]FIAU was another imaging modality used for verifying the previous results. In conclusion, this study showed that bioluminescence imaging is a powerful and quantitative tool for the direct assay to monitor tumor growth in vivo. The dual reporter genes transfected tumor-bearing animal model can be applied in the evaluation of the efficacy of new developed anti-cancer drugs.

Monitoring and quantitative assessment of tumor burden using in vivo bioluminescence imaging

International Nuclear Information System (INIS)

Chen, C.-C.; Hwang, Jeng-Jong; Ting, G.; Tseng, Y.-L.; Wang, S.-J.; Whang-Peng, J.

2007-01-01

In vivo bioluminescence imaging (BLI) is a sensitive imaging modality that is rapid and accessible, and may comprise an ideal tool for evaluating tumor growth. In this study, the kinetic of tumor growth has been assessed in C26 colon carcinoma bearing BALB/c mouse model. The ability of BLI to noninvasively quantitate the growth of subcutaneous tumors transplanted with C26 cells genetically engineered to stably express firefly luciferase and herpes simplex virus type-1 thymidine kinase (C26/tk-luc). A good correlation (R 2 =0.998) of photon emission to the cell number was found in vitro. Tumor burden and tumor volume were monitored in vivo over time by quantitation of photon emission using Xenogen IVIS 50 and standard external caliper measurement, respectively. At various time intervals, tumor-bearing mice were imaged to determine the correlation of in vivo BLI to tumor volume. However, a correlation of BLI to tumor volume was observed when tumor volume was smaller than 1000 mm 3 (R 2 =0.907). γ Scintigraphy combined with [ 131 I]FIAU was another imaging modality used for verifying the previous results. In conclusion, this study showed that bioluminescence imaging is a powerful and quantitative tool for the direct assay to monitor tumor growth in vivo. The dual reporter genes transfected tumor-bearing animal model can be applied in the evaluation of the efficacy of new developed anti-cancer drugs

Biomarkers of the Dementia

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Mikio Shoji

2011-01-01

Full Text Available Recent advances in biomarker studies on dementia are summarized here. CSF Aβ40, Aβ42, total tau, and phosphorylated tau are the most sensitive biomarkers for diagnosis of Alzheimer's disease (AD and prediction of onset of AD from mild cognitive impairment (MCI. Based on this progress, new diagnostic criteria for AD, MCI, and preclinical AD were proposed by National Institute of Aging (NIA and Alzheimer's Association in August 2010. In these new criteria, progress in biomarker identification and amyloid imaging studies in the past 10 years have added critical information. Huge contributions of basic and clinical studies have established clinical evidence supporting these markers. Based on this progress, essential therapy for cure of AD is urgently expected.

Quantitative imaging of the human upper airway: instrument design and clinical studies

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Leigh, M. S.; Armstrong, J. J.; Paduch, A.; Sampson, D. D.; Walsh, J. H.; Hillman, D. R.; Eastwood, P. R.

2006-08-01

Imaging of the human upper airway is widely used in medicine, in both clinical practice and research. Common imaging modalities include video endoscopy, X-ray CT, and MRI. However, no current modality is both quantitative and safe to use for extended periods of time. Such a capability would be particularly valuable for sleep research, which is inherently reliant on long observation sessions. We have developed an instrument capable of quantitative imaging of the human upper airway, based on endoscopic optical coherence tomography. There are no dose limits for optical techniques, and the minimally invasive imaging probe is safe for use in overnight studies. We report on the design of the instrument and its use in preliminary clinical studies, and we present results from a range of initial experiments. The experiments show that the instrument is capable of imaging during sleep, and that it can record dynamic changes in airway size and shape. This information is useful for research into sleep disorders, and potentially for clinical diagnosis and therapies.

A collimator optimization method for quantitative imaging: application to Y-90 bremsstrahlung SPECT.

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Rong, Xing; Frey, Eric C

2013-08-01

Post-therapy quantitative 90Y bremsstrahlung single photon emission computed tomography (SPECT) has shown great potential to provide reliable activity estimates, which are essential for dose verification. Typically 90Y imaging is performed with high- or medium-energy collimators. However, the energy spectrum of 90Y bremsstrahlung photons is substantially different than typical for these collimators. In addition, dosimetry requires quantitative images, and collimators are not typically optimized for such tasks. Optimizing a collimator for 90Y imaging is both novel and potentially important. Conventional optimization methods are not appropriate for 90Y bremsstrahlung photons, which have a continuous and broad energy distribution. In this work, the authors developed a parallel-hole collimator optimization method for quantitative tasks that is particularly applicable to radionuclides with complex emission energy spectra. The authors applied the proposed method to develop an optimal collimator for quantitative 90Y bremsstrahlung SPECT in the context of microsphere radioembolization. To account for the effects of the collimator on both the bias and the variance of the activity estimates, the authors used the root mean squared error (RMSE) of the volume of interest activity estimates as the figure of merit (FOM). In the FOM, the bias due to the null space of the image formation process was taken in account. The RMSE was weighted by the inverse mass to reflect the application to dosimetry; for a different application, more relevant weighting could easily be adopted. The authors proposed a parameterization for the collimator that facilitates the incorporation of the important factors (geometric sensitivity, geometric resolution, and septal penetration fraction) determining collimator performance, while keeping the number of free parameters describing the collimator small (i.e., two parameters). To make the optimization results for quantitative 90Y bremsstrahlung SPECT more

In Vivo Fluorescence Lifetime Imaging Monitors Binding of Specific Probes to Cancer Biomarkers

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Ardeshirpour, Yasaman; Chernomordik, Victor; Zielinski, Rafal; Capala, Jacek; Griffiths, Gary; Vasalatiy, Olga; Smirnov, Aleksandr V.; Knutson, Jay R.; Lyakhov, Ilya; Achilefu, Samuel; Gandjbakhche, Amir; Hassan, Moinuddin

2012-01-01

One of the most important factors in choosing a treatment strategy for cancer is characterization of biomarkers in cancer cells. Particularly, recent advances in Monoclonal Antibodies (MAB) as primary-specific drugs targeting tumor receptors show that their efficacy depends strongly on characterization of tumor biomarkers. Assessment of their status in individual patients would facilitate selection of an optimal treatment strategy, and the continuous monitoring of those biomarkers and their binding process to the therapy would provide a means for early evaluation of the efficacy of therapeutic intervention. In this study we have demonstrated for the first time in live animals that the fluorescence lifetime can be used to detect the binding of targeted optical probes to the extracellular receptors on tumor cells in vivo. The rationale was that fluorescence lifetime of a specific probe is sensitive to local environment and/or affinity to other molecules. We attached Near-InfraRed (NIR) fluorescent probes to Human Epidermal Growth Factor 2 (HER2/neu)-specific Affibody molecules and used our time-resolved optical system to compare the fluorescence lifetime of the optical probes that were bound and unbound to tumor cells in live mice. Our results show that the fluorescence lifetime changes in our model system delineate HER2 receptor bound from the unbound probe in vivo. Thus, this method is useful as a specific marker of the receptor binding process, which can open a new paradigm in the “image and treat” concept, especially for early evaluation of the efficacy of the therapy. PMID:22384092

In vivo fluorescence lifetime imaging monitors binding of specific probes to cancer biomarkers.

Directory of Open Access Journals (Sweden)

Yasaman Ardeshirpour

Full Text Available One of the most important factors in choosing a treatment strategy for cancer is characterization of biomarkers in cancer cells. Particularly, recent advances in Monoclonal Antibodies (MAB as primary-specific drugs targeting tumor receptors show that their efficacy depends strongly on characterization of tumor biomarkers. Assessment of their status in individual patients would facilitate selection of an optimal treatment strategy, and the continuous monitoring of those biomarkers and their binding process to the therapy would provide a means for early evaluation of the efficacy of therapeutic intervention. In this study we have demonstrated for the first time in live animals that the fluorescence lifetime can be used to detect the binding of targeted optical probes to the extracellular receptors on tumor cells in vivo. The rationale was that fluorescence lifetime of a specific probe is sensitive to local environment and/or affinity to other molecules. We attached Near-InfraRed (NIR fluorescent probes to Human Epidermal Growth Factor 2 (HER2/neu-specific Affibody molecules and used our time-resolved optical system to compare the fluorescence lifetime of the optical probes that were bound and unbound to tumor cells in live mice. Our results show that the fluorescence lifetime changes in our model system delineate HER2 receptor bound from the unbound probe in vivo. Thus, this method is useful as a specific marker of the receptor binding process, which can open a new paradigm in the "image and treat" concept, especially for early evaluation of the efficacy of the therapy.

Prognostic Metabolite Biomarkers for Soft Tissue Sarcomas Discovered by Mass Spectrometry Imaging

Science.gov (United States)

Lou, Sha; Balluff, Benjamin; Cleven, Arjen H. G.; Bovée, Judith V. M. G.; McDonnell, Liam A.

2017-02-01

Metabolites can be an important read-out of disease. The identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients is one of the main current research aspects. Mass spectrometry has become the technique of choice for metabolomics studies, and mass spectrometry imaging (MSI) enables their visualization in patient tissues. In this study, we used MSI to identify prognostic metabolite biomarkers in high grade sarcomas; 33 high grade sarcoma patients, comprising osteosarcoma, leiomyosarcoma, myxofibrosarcoma, and undifferentiated pleomorphic sarcoma were analyzed. Metabolite MSI data were obtained from sections of fresh frozen tissue specimens with matrix-assisted laser/desorption ionization (MALDI) MSI in negative polarity using 9-aminoarcridine as matrix. Subsequent annotation of tumor regions by expert pathologists resulted in tumor-specific metabolite signatures, which were then tested for association with patient survival. Metabolite signals with significant clinical value were further validated and identified by high mass resolution Fourier transform ion cyclotron resonance (FTICR) MSI. Three metabolite signals were found to correlate with overall survival ( m/z 180.9436 and 241.0118) and metastasis-free survival ( m/z 160.8417). FTICR-MSI identified m/z 241.0118 as inositol cyclic phosphate and m/z 160.8417 as carnitine.

Alzheimer Disease Biomarkers as Outcome Measures for Clinical Trials in MCI.

Science.gov (United States)

Caroli, Anna; Prestia, Annapaola; Wade, Sara; Chen, Kewei; Ayutyanont, Napatkamon; Landau, Susan M; Madison, Cindee M; Haense, Cathleen; Herholz, Karl; Reiman, Eric M; Jagust, William J; Frisoni, Giovanni B

2015-01-01

The aim of this study was to compare the performance and power of the best-established diagnostic biological markers as outcome measures for clinical trials in patients with mild cognitive impairment (MCI). Magnetic resonance imaging, F-18 fluorodeoxyglucose positron emission tomography markers, and Alzheimer's Disease Assessment Scale-cognitive subscale were compared in terms of effect size and statistical power over different follow-up periods in 2 MCI groups, selected from Alzheimer's Disease Neuroimaging Initiative data set based on cerebrospinal fluid (abnormal cerebrospinal fluid Aβ1-42 concentration-ABETA+) or magnetic resonance imaging evidence of Alzheimer disease (positivity to hippocampal atrophy-HIPPO+). Biomarkers progression was modeled through mixed effect models. Scaled slope was chosen as measure of effect size. Biomarkers power was estimated using simulation algorithms. Seventy-four ABETA+ and 51 HIPPO+ MCI patients were included in the study. Imaging biomarkers of neurodegeneration, especially MR measurements, showed highest performance. For all biomarkers and both MCI groups, power increased with increasing follow-up time, irrespective of biomarker assessment frequency. These findings provide information about biomarker enrichment and outcome measurements that could be employed to reduce MCI patient samples and treatment duration in future clinical trials.

Protein biomarkers on tissue as imaged via MALDI mass spectrometry: A systematic approach to study the limits of detection.

Science.gov (United States)

van de Ven, Stephanie M W Y; Bemis, Kyle D; Lau, Kenneth; Adusumilli, Ravali; Kota, Uma; Stolowitz, Mark; Vitek, Olga; Mallick, Parag; Gambhir, Sanjiv S

2016-06-01

MALDI mass spectrometry imaging (MSI) is emerging as a tool for protein and peptide imaging across tissue sections. Despite extensive study, there does not yet exist a baseline study evaluating the potential capabilities for this technique to detect diverse proteins in tissue sections. In this study, we developed a systematic approach for characterizing MALDI-MSI workflows in terms of limits of detection, coefficients of variation, spatial resolution, and the identification of endogenous tissue proteins. Our goal was to quantify these figures of merit for a number of different proteins and peptides, in order to gain more insight in the feasibility of protein biomarker discovery efforts using this technique. Control proteins and peptides were deposited in serial dilutions on thinly sectioned mouse xenograft tissue. Using our experimental setup, coefficients of variation were biomarkers and a new benchmarking strategy that can be used for comparing diverse MALDI-MSI workflows. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A quantitative performance evaluation of the EM algorithm applied to radiographic images

International Nuclear Information System (INIS)

Brailean, J.C.; Sullivan, B.J.; Giger, M.L.; Chen, C.T.

1991-01-01

In this paper, the authors quantitatively evaluate the performance of the Expectation Maximization (EM) algorithm as a restoration technique for radiographic images. The perceived signal-to-noise ratio (SNR), of simple radiographic patterns processed by the EM algorithm are calculated on the basis of a statistical decision theory model that includes both the observer's visual response function and a noise component internal to the eye-brain system. The relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to quantitatively compare the effects of the EM algorithm to two popular image enhancement techniques: contrast enhancement (windowing) and unsharp mask filtering

Characterization of regional left ventricular function in nonhuman primates using magnetic resonance imaging biomarkers: a test-retest repeatability and inter-subject variability study.

Directory of Open Access Journals (Sweden)

Smita Sampath

Full Text Available Pre-clinical animal models are important to study the fundamental biological and functional mechanisms involved in the longitudinal evolution of heart failure (HF. Particularly, large animal models, like nonhuman primates (NHPs, that possess greater physiological, biochemical, and phylogenetic similarity to humans are gaining interest. To assess the translatability of these models into human diseases, imaging biomarkers play a significant role in non-invasive phenotyping, prediction of downstream remodeling, and evaluation of novel experimental therapeutics. This paper sheds insight into NHP cardiac function through the quantification of magnetic resonance (MR imaging biomarkers that comprehensively characterize the spatiotemporal dynamics of left ventricular (LV systolic pumping and LV diastolic relaxation. MR tagging and phase contrast (PC imaging were used to quantify NHP cardiac strain and flow. Temporal inter-relationships between rotational mechanics, myocardial strain and LV chamber flow are presented, and functional biomarkers are evaluated through test-retest repeatability and inter subject variability analyses. The temporal trends observed in strain and flow was similar to published data in humans. Our results indicate a dominant dimension based pumping during early systole, followed by a torsion dominant pumping action during late systole. Early diastole is characterized by close to 65% of untwist, the remainder of which likely contributes to efficient filling during atrial kick. Our data reveal that moderate to good intra-subject repeatability was observed for peak strain, strain-rates, E/circumferential strain-rate (CSR ratio, E/longitudinal strain-rate (LSR ratio, and deceleration time. The inter-subject variability was high for strain dyssynchrony, diastolic strain-rates, peak torsion and peak untwist rate. We have successfully characterized cardiac function in NHPs using MR imaging. Peak strain, average systolic strain

Comparison of quantitative myocardial perfusion imaging CT to fluorescent microsphere-based flow from high-resolution cryo-images

Science.gov (United States)

Eck, Brendan L.; Fahmi, Rachid; Levi, Jacob; Fares, Anas; Wu, Hao; Li, Yuemeng; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

2016-03-01

Myocardial perfusion imaging using CT (MPI-CT) has the potential to provide quantitative measures of myocardial blood flow (MBF) which can aid the diagnosis of coronary artery disease. We evaluated the quantitative accuracy of MPI-CT in a porcine model of balloon-induced LAD coronary artery ischemia guided by fractional flow reserve (FFR). We quantified MBF at baseline (FFR=1.0) and under moderate ischemia (FFR=0.7) using MPI-CT and compared to fluorescent microsphere-based MBF from high-resolution cryo-images. Dynamic, contrast-enhanced CT images were obtained using a spectral detector CT (Philips Healthcare). Projection-based mono-energetic images were reconstructed and processed to obtain MBF. Three MBF quantification approaches were evaluated: singular value decomposition (SVD) with fixed Tikhonov regularization (ThSVD), SVD with regularization determined by the L-Curve criterion (LSVD), and Johnson-Wilson parameter estimation (JW). The three approaches over-estimated MBF compared to cryo-images. JW produced the most accurate MBF, with average error 33.3+/-19.2mL/min/100g, whereas LSVD and ThSVD had greater over-estimation, 59.5+/-28.3mL/min/100g and 78.3+/-25.6 mL/min/100g, respectively. Relative blood flow as assessed by a flow ratio of LAD-to-remote myocardium was strongly correlated between JW and cryo-imaging, with R2=0.97, compared to R2=0.88 and 0.78 for LSVD and ThSVD, respectively. We assessed tissue impulse response functions (IRFs) from each approach for sources of error. While JW was constrained to physiologic solutions, both LSVD and ThSVD produced IRFs with non-physiologic properties due to noise. The L-curve provided noise-adaptive regularization but did not eliminate non-physiologic IRF properties or optimize for MBF accuracy. These findings suggest that model-based MPI-CT approaches may be more appropriate for quantitative MBF estimation and that cryo-imaging can support the development of MPI-CT by providing spatial distributions of MBF.

Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

International Nuclear Information System (INIS)

Karaçalı, Bilge; Vamvakidou, Alexandra P; Tözeren, Aydın

2007-01-01

Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development

Recommendations for the use of PET imaging biomarkers in the diagnosis of neurodegenerative conditions associated with dementia: SEMNIM and SEN consensus.

Science.gov (United States)

Arbizu, Javier; García-Ribas, Guillermo; Carrió, Ignasi; Garrastachu, Puy; Martínez-Lage, Pablo; Molinuevo, José Luis

2015-01-01

The new diagnostic criteria for Alzheimer's disease (AD) acknowledges the interest given to biomarkers to improve the specificity in subjects with dementia and to facilitate an early diagnosis of the pathophysiological process of AD in the prodromal or pre-dementia stage. The current availability of PET imaging biomarkers of synaptic dysfunction (PET-FDG) and beta amyloid deposition using amyloid-PET provides clinicians with the opportunity to apply the new criteria and improve diagnostic accuracy in their clinical practice. Therefore, it seems essential for the scientific societies involved to use the new clinical diagnostic support tools to establish clear, evidence-based and agreed set of recommendations for their appropriate use. The present work includes a systematic review of the literature on the utility of FDG-PET and amyloid-PET for the diagnosis of AD and related neurodegenerative diseases that occur with dementia. Thus, we propose a series of recommendations agreed on by the Spanish Society of Nuclear Medicine and Spanish Society of Neurology as a consensus statement on the appropriate use of PET imaging biomarkers. Copyright © 2015 Elsevier España, S.L.U. and SEMNIM. All rights reserved.

Application of an image processing software for quantitative autoradiography

International Nuclear Information System (INIS)

Sobeslavsky, E.; Bergmann, R.; Kretzschmar, M.; Wenzel, U.

1993-01-01

The present communication deals with the utilization of an image processing device for quantitative whole-body autoradiography, cell counting and also for interpretation of chromatograms. It is shown that the system parameters allow an adequate and precise determination of optical density values. Also shown are the main error sources limiting the applicability of the system. (orig.)

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

Energy Technology Data Exchange (ETDEWEB)

Guo, Xuejiang; Tang, Keqi

2017-06-14

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers would ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM) mode

WE-G-207-05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis

Energy Technology Data Exchange (ETDEWEB)

Lee, J; Nishikawa, R [University of Pittsburgh, Pittsburgh, PA (United States); Reiser, I [The University of Chicago, Chicago, IL (United States); Boone, J [UC Davis Medical Center, Sacramento, CA (United States)

2015-06-15

Purpose: Segmentation quality can affect quantitative image feature analysis. The objective of this study is to examine the relationship between computed tomography (CT) image quality, segmentation performance, and quantitative image feature analysis. Methods: A total of 90 pathology proven breast lesions in 87 dedicated breast CT images were considered. An iterative image reconstruction (IIR) algorithm was used to obtain CT images with different quality. With different combinations of 4 variables in the algorithm, this study obtained a total of 28 different qualities of CT images. Two imaging tasks/objectives were considered: 1) segmentation and 2) classification of the lesion as benign or malignant. Twenty-three image features were extracted after segmentation using a semi-automated algorithm and 5 of them were selected via a feature selection technique. Logistic regression was trained and tested using leave-one-out-cross-validation and its area under the ROC curve (AUC) was recorded. The standard deviation of a homogeneous portion and the gradient of a parenchymal portion of an example breast were used as an estimate of image noise and sharpness. The DICE coefficient was computed using a radiologist’s drawing on the lesion. Mean DICE and AUC were used as performance metrics for each of the 28 reconstructions. The relationship between segmentation and classification performance under different reconstructions were compared. Distributions (median, 95% confidence interval) of DICE and AUC for each reconstruction were also compared. Results: Moderate correlation (Pearson’s rho = 0.43, p-value = 0.02) between DICE and AUC values was found. However, the variation between DICE and AUC values for each reconstruction increased as the image sharpness increased. There was a combination of IIR parameters that resulted in the best segmentation with the worst classification performance. Conclusion: There are certain images that yield better segmentation or classification

Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies.

Science.gov (United States)

Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura; Prah, Melissa; Hectors, Stefanie; Arlinghaus, Lori; Muzi, Mark; Solaiyappan, Meiyappan; Jacobs, Michael; Fung, Maggie; Shukla-Dave, Amita; McManus, Kevin; Boss, Michael; Taouli, Bachir; Yankeelov, Thomas E; Quarles, Christopher Chad; Schmainda, Kathleen; Chenevert, Thomas L; Newitt, David C

2018-01-01

This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.

Carotid Intraplaque Hemorrhage Imaging with Quantitative Vessel Wall T1 Mapping: Technical Development and Initial Experience.

Science.gov (United States)

Qi, Haikun; Sun, Jie; Qiao, Huiyu; Chen, Shuo; Zhou, Zechen; Pan, Xinlei; Wang, Yishi; Zhao, Xihai; Li, Rui; Yuan, Chun; Chen, Huijun

2018-04-01

Purpose To develop a three-dimensional (3D) high-spatial-resolution time-efficient sequence for use in quantitative vessel wall T1 mapping. Materials and Methods A previously described sequence, simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP) imaging, was extended by introducing 3D golden angle radial k-space sampling (GOAL-SNAP). Sliding window reconstruction was adopted to reconstruct images at different inversion delay times (different T1 contrasts) for voxelwise T1 fitting. Phantom studies were performed to test the accuracy of T1 mapping with GOAL-SNAP against a two-dimensional inversion recovery (IR) spin-echo (SE) sequence. In vivo studies were performed in six healthy volunteers (mean age, 27.8 years ± 3.0 [standard deviation]; age range, 24-32 years; five male) and five patients with atherosclerosis (mean age, 66.4 years ± 5.5; range, 60-73 years; five male) to compare T1 measurements between vessel wall sections (five per artery) with and without intraplaque hemorrhage (IPH). Statistical analyses included Pearson correlation coefficient, Bland-Altman analysis, and Wilcoxon rank-sum test with data permutation by subject. Results Phantom T1 measurements with GOAL-SNAP and IR SE sequences showed excellent correlation (R 2 = 0.99), with a mean bias of -25.8 msec ± 43.6 and a mean percentage error of 4.3% ± 2.5. Minimum T1 was significantly different between sections with IPH and those without it (mean, 371 msec ± 93 vs 944 msec ± 120; P = .01). Estimated T1 of normal vessel wall and muscle were 1195 msec ± 136 and 1117 msec ± 153, respectively. Conclusion High-spatial-resolution (0.8 mm isotropic) time-efficient (5 minutes) vessel wall T1 mapping is achieved by using the GOAL-SNAP sequence. This sequence may yield more quantitative reproducible biomarkers with which to characterize IPH and monitor its progression. © RSNA, 2017.

dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM.

Science.gov (United States)

Herz, Christian; Fillion-Robin, Jean-Christophe; Onken, Michael; Riesmeier, Jörg; Lasso, Andras; Pinter, Csaba; Fichtinger, Gabor; Pieper, Steve; Clunie, David; Kikinis, Ron; Fedorov, Andriy

2017-11-01

Quantitative analysis of clinical image data is an active area of research that holds promise for precision medicine, early assessment of treatment response, and objective characterization of the disease. Interoperability, data sharing, and the ability to mine the resulting data are of increasing importance, given the explosive growth in the number of quantitative analysis methods being proposed. The Digital Imaging and Communications in Medicine (DICOM) standard is widely adopted for image and metadata in radiology. dcmqi (DICOM for Quantitative Imaging) is a free, open source library that implements conversion of the data stored in commonly used research formats into the standard DICOM representation. dcmqi source code is distributed under BSD-style license. It is freely available as a precompiled binary package for every major operating system, as a Docker image, and as an extension to 3D Slicer. Installation and usage instructions are provided in the GitHub repository at https://github.com/qiicr/dcmqi Cancer Res; 77(21); e87-90. ©2017 AACR . ©2017 American Association for Cancer Research.

An innovative phantom for quantitative and qualitative investigation of advanced x-ray imaging technologies

International Nuclear Information System (INIS)

Chiarot, C B; Siewerdsen, J H; Haycocks, T; Moseley, D J; Jaffray, D A

2005-01-01

Development, characterization, and quality assurance of advanced x-ray imaging technologies require phantoms that are quantitative and well suited to such modalities. This note reports on the design, construction, and use of an innovative phantom developed for advanced imaging technologies (e.g., multi-detector CT and the numerous applications of flat-panel detectors in dual-energy imaging, tomosynthesis, and cone-beam CT) in diagnostic and image-guided procedures. The design addresses shortcomings of existing phantoms by incorporating criteria satisfied by no other single phantom: (1) inserts are fully 3D-spherically symmetric rather than cylindrical; (2) modules are quantitative, presenting objects of known size and contrast for quality assurance and image quality investigation; (3) features are incorporated in ideal and semi-realistic (anthropomorphic) contexts; and (4) the phantom allows devices to be inserted and manipulated in an accessible module (right lung). The phantom consists of five primary modules: (1) head, featuring contrast-detail spheres approximate to brain lesions; (2) left lung, featuring contrast-detail spheres approximate to lung modules; (3) right lung, an accessible hull in which devices may be placed and manipulated; (4) liver, featuring conrast-detail spheres approximate to metastases; and (5) abdomen/pelvis, featuring simulated kidneys, colon, rectum, bladder, and prostate. The phantom represents a two-fold evolution in design philosophy-from 2D (cylindrically symmetric) to fully 3D, and from exclusively qualitative or quantitative to a design accommodating quantitative study within an anatomical context. It has proven a valuable tool in investigations throughout our institution, including low-dose CT, dual-energy radiography, and cone-beam CT for image-guided radiation therapy and surgery. (note)

Molecular Imaging of Tumors Using a Quantitative T1 Mapping Technique via Magnetic Resonance Imaging

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Kelsey Herrmann

2015-07-01

Full Text Available Magnetic resonance imaging (MRI of glioblastoma multiforme (GBM with molecular imaging agents would allow for the specific localization of brain tumors. Prior studies using T1-weighted MR imaging demonstrated that the SBK2-Tris-(Gd-DOTA3 molecular imaging agent labeled heterotopic xenograft models of brain tumors more intensely than non-specific contrast agents using conventional T1-weighted imaging techniques. In this study, we used a dynamic quantitative T1 mapping strategy to more objectively compare intra-tumoral retention of the SBK2-Tris-(Gd-DOTA3 agent over time in comparison to non-targeted control agents. Our results demonstrate that the targeted SBK2-Tris-(Gd-DOTA3 agent, a scrambled-Tris-(Gd-DOTA3 control agent, and the non-specific clinical contrast agent Optimark™ all enhanced flank tumors of human glioma cells with similar maximal changes on T1 mapping. However, the retention of the agents differs. The non-specific agents show significant recovery within 20 min by an increase in T1 while the specific agent SBK2-Tris-(Gd-DOTA3 is retained in the tumors and shows little recovery over 60 min. The retention effect is demonstrated by percent change in T1 values and slope calculations as well as by calculations of gadolinium concentration in tumor compared to muscle. Quantitative T1 mapping demonstrates the superior binding and retention in tumors of the SBK2-Tris-(Gd-DOTA3 agent over time compared to the non-specific contrast agent currently in clinical use.

Fastr: a workflow engine for advanced data flows in medical image analysis

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Hakim Christiaan Achterberg

2016-08-01

Full Text Available With the increasing number of datasets encountered in imaging studies, the increasingcomplexity of processing workflows, and a growing awareness for data stewardship, thereis a need for managed, automated workflows. In this paper we introduce Fastr, an automatedworkflow engine with support for advanced data flows. Fastr has built-in data provenance forrecording processing trails and ensuring reproducible results. The extensible plugin-based designallows the system to interface with virtually any image archive and processing infrastructure. Thisworkflow engine is designed to consolidate quantitative imaging biomarker pipelines in order toenable easy application to new data.

Predictive values of semi-quantitative procalcitonin test and common biomarkers for the clinical outcomes of community-acquired pneumonia.

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Ugajin, Motoi; Yamaki, Kenichi; Hirasawa, Natsuko; Yagi, Takeo

2014-04-01

The semi-quantitative serum procalcitonin test (Brahms PCT-Q) is available conveniently in clinical practice. However, there are few data on the relationship between results for this semi-quantitative procalcitonin test and clinical outcomes of community-acquired pneumonia (CAP). We investigated the usefulness of this procalcitonin test for predicting the clinical outcomes of CAP in comparison with severity scoring systems and the blood urea nitrogen/serum albumin (B/A) ratio, which has been reported to be a simple but reliable prognostic indicator in our prior CAP study. This retrospective study included data from subjects who were hospitalized for CAP from August 2010 through October 2012 and who were administered the semi-quantitative serum procalcitonin test on admission. The demographic characteristics; laboratory biomarkers; microbiological test results; Pneumonia Severity Index scores; confusion, urea nitrogen, breathing frequency, blood pressure, ≥ 65 years of age (CURB-65) scale scores; and age, dehydration, respiratory failure, orientation disturbance, pressure (A-DROP) scale scores on hospital admission were retrieved from their medical charts. The outcomes were mortality within 28 days of hospital admission and the need for intensive care. Of the 213 subjects with CAP who were enrolled in the study, 20 died within 28 days of hospital admission, and 32 required intensive care. Mortality did not differ significantly among subjects with different semi-quantitative serum procalcitonin levels; however, subjects with serum procalcitonin levels ≥ 10.0 ng/mL were more likely to require intensive care than those with lower levels (P pneumonia. Using the receiver operating characteristic curves for mortality, the area under the curve was 0.86 for Pneumonia Severity Index class, 0.81 for B/A ratio, 0.81 for A-DROP, 0.80 for CURB-65, and 0.57 for semi-quantitative procalcitonin test. The semi-quantitative serum procalcitonin level on hospital admission was less

Quantitation without Calibration: Response Profile as an Indicator of Target Amount.

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Debnath, Mrittika; Farace, Jessica M; Johnson, Kristopher D; Nesterova, Irina V

2018-06-21

Quantitative assessment of biomarkers is essential in numerous contexts from decision-making in clinical situations to food quality monitoring to interpretation of life-science research findings. However, appropriate quantitation techniques are not as widely addressed as detection methods. One of the major challenges in biomarker's quantitation is the need to have a calibration for correlating a measured signal to a target amount. The step complicates the methodologies and makes them less sustainable. In this work we address the issue via a new strategy: relying on position of response profile rather than on an absolute signal value for assessment of a target's amount. In order to enable the capability we develop a target-probe binding mechanism based on a negative cooperativity effect. A proof-of-concept example demonstrates that the model is suitable for quantitative analysis of nucleic acids over a wide concentration range. The general principles of the platform will be applicable toward a variety of biomarkers such as nucleic acids, proteins, peptides, and others.

Quantitative image analysis for investigating cell-matrix interactions

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Burkel, Brian; Notbohm, Jacob

2017-07-01

The extracellular matrix provides both chemical and physical cues that control cellular processes such as migration, division, differentiation, and cancer progression. Cells can mechanically alter the matrix by applying forces that result in matrix displacements, which in turn may localize to form dense bands along which cells may migrate. To quantify the displacements, we use confocal microscopy and fluorescent labeling to acquire high-contrast images of the fibrous material. Using a technique for quantitative image analysis called digital volume correlation, we then compute the matrix displacements. Our experimental technology offers a means to quantify matrix mechanics and cell-matrix interactions. We are now using these experimental tools to modulate mechanical properties of the matrix to study cell contraction and migration.

Hemopexin as biomarkers for analyzing the biological responses associated with exposure to silica nanoparticles

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Higashisaka, Kazuma; Yoshioka, Yasuo; Yamashita, Kohei; Morishita, Yuki; Pan, Huiyan; Ogura, Toshinobu; Nagano, Takashi; Kunieda, Akiyoshi; Nagano, Kazuya; Abe, Yasuhiro; Kamada, Haruhiko; Tsunoda, Shin-ichi; Nabeshi, Hiromi; Yoshikawa, Tomoaki; Tsutsumi, Yasuo

2012-10-01

Practical uses of nanomaterials are rapidly spreading to a wide variety of fields. However, potential harmful effects of nanomaterials are raising concerns about their safety. Therefore, it is important that a risk assessment system is developed so that the safety of nanomaterials can be evaluated or predicted. Here, we attempted to identify novel biomarkers of nanomaterial-induced health effects by a comprehensive screen of plasma proteins using two-dimensional differential in gel electrophoresis (2D-DIGE) analysis. Initially, we used 2D-DIGE to analyze changes in the level of plasma proteins in mice after intravenous injection via tail veins of 0.8 mg/mouse silica nanoparticles with diameters of 70 nm (nSP70) or saline as controls. By quantitative image analysis, protein spots representing >2.0-fold alteration in expression were found and identified by mass spectrometry. Among these proteins, we focused on hemopexin as a potential biomarker. The levels of hemopexin in the plasma increased as the silica particle size decreased. In addition, the production of hemopexin depended on the characteristics of the nanomaterials. These results suggested that hemopexin could be an additional biomarker for analyzing the biological responses associated with exposure to silica nanoparticles. We believe that this study will contribute to the development of biomarkers to ensure the safety of silica nanoparticles.

Using image analysis as a tool for assessment of prognostic and predictive biomarkers for breast cancer: How reliable is it?

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Mark C Lloyd

2010-01-01

Full Text Available Background : Estrogen receptor (ER, progesterone receptor (PR and human epidermal growth factor receptor-2 (HER2 are important and well-established prognostic and predictive biomarkers for breast cancers and routinely tested on patient′s tumor samples by immunohistochemical (IHC study. The accuracy of these test results has substantial impact on patient management. A critical factor that contributes to the result is the interpretation (scoring of IHC. This study investigates how computerized image analysis can play a role in a reliable scoring, and identifies potential pitfalls with common methods. Materials and Methods : Whole slide images of 33 invasive ductal carcinoma (IDC (10 ER and 23 HER2 were scored by pathologist under the light microscope and confirmed by another pathologist. The HER2 results were additionally confirmed by fluorescence in situ hybridization (FISH. The scoring criteria were adherent to the guidelines recommended by the American Society of Clinical Oncology/College of American Pathologists. Whole slide stains were then scored by commercially available image analysis algorithms from Definiens (Munich, Germany and Aperio Technologies (Vista, CA, USA. Each algorithm was modified specifically for each marker and tissue. The results were compared with the semi-quantitative manual scoring, which was considered the gold standard in this study. Results : For HER2 positive group, each algorithm scored 23/23 cases within the range established by the pathologist. For ER, both algorithms scored 10/10 cases within range. The performance of each algorithm varies somewhat from the percentage of staining as compared to the pathologist′s reading. Conclusions : Commercially available computerized image analysis can be useful in the evaluation of ER and HER2 IHC results. In order to achieve accurate results either manual pathologist region selection is necessary, or an automated region selection tool must be employed. Specificity can

Individual patient dosimetry using quantitative SPECT imaging

International Nuclear Information System (INIS)

Gonzalez, J.; Oliva, J.; Baum, R.; Fisher, S.

2002-01-01

An approach is described to provide individual patient dosimetry for routine clinical use. Accurate quantitative SPECT imaging was achieved using appropriate methods. The volume of interest (VOI) was defined semi-automatically using a fixed threshold value obtained from phantom studies. The calibration factor to convert the voxel counts from SPECT images into activity values was determine from calibrated point source using the same threshold value as in phantom studies. From selected radionuclide the dose within and outside a sphere of voxel dimension at different distances was computed through dose point-kernels to obtain a discrete absorbed dose kernel representation around the volume source with uniform activity distribution. The spatial activity distribution from SPECT imaging was convolved with this kernel representation using the discrete Fourier transform method to yield three-dimensional absorbed dose rate distribution. The accuracy of dose rates calculation was validated by software phantoms. The absorbed dose was determined by integration of the dose rate distribution for each volume of interest (VOI). Parameters for treatment optimization such as dose rate volume histograms and dose rate statistic are provided. A patient example was used to illustrate our dosimetric calculations

Quantitative phase imaging with scanning holographic microscopy: an experimental assesment

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Tada Yoshitaka

2006-11-01

Full Text Available Abstract This paper demonstrates experimentally how quantitative phase information can be obtained in scanning holographic microscopy. Scanning holography can operate in both coherent and incoherent modes, simultaneously if desired, with different detector geometries. A spatially integrating detector provides an incoherent hologram of the object's intensity distribution (absorption and/or fluorescence, for example, while a point detector in a conjugate plane of the pupil provides a coherent hologram of the object's complex amplitude, from which a quantitative measure of its phase distribution can be extracted. The possibility of capturing simultaneously holograms of three-dimensional specimens, leading to three-dimensional reconstructions with absorption contrast, reflectance contrast, fluorescence contrast, as was previously demonstrated, and quantitative phase contrast, as shown here for the first time, opens up new avenues for multimodal imaging in biological studies.

Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers

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Daniel M Spagnolo

2016-01-01

Full Text Available Background: Measures of spatial intratumor heterogeneity are potentially important diagnostic biomarkers for cancer progression, proliferation, and response to therapy. Spatial relationships among cells including cancer and stromal cells in the tumor microenvironment (TME are key contributors to heterogeneity. Methods: We demonstrate how to quantify spatial heterogeneity from immunofluorescence pathology samples, using a set of 3 basic breast cancer biomarkers as a test case. We learn a set of dominant biomarker intensity patterns and map the spatial distribution of the biomarker patterns with a network. We then describe the pairwise association statistics for each pattern within the network using pointwise mutual information (PMI and visually represent heterogeneity with a two-dimensional map. Results: We found a salient set of 8 biomarker patterns to describe cellular phenotypes from a tissue microarray cohort containing 4 different breast cancer subtypes. After computing PMI for each pair of biomarker patterns in each patient and tumor replicate, we visualize the interactions that contribute to the resulting association statistics. Then, we demonstrate the potential for using PMI as a diagnostic biomarker, by comparing PMI maps and heterogeneity scores from patients across the 4 different cancer subtypes. Estrogen receptor positive invasive lobular carcinoma patient, AL13-6, exhibited the highest heterogeneity score among those tested, while estrogen receptor negative invasive ductal carcinoma patient, AL13-14, exhibited the lowest heterogeneity score. Conclusions: This paper presents an approach for describing intratumor heterogeneity, in a quantitative fashion (via PMI, which departs from the purely qualitative approaches currently used in the clinic. PMI is generalizable to highly multiplexed/hyperplexed immunofluorescence images, as well as spatial data from complementary in situ methods including FISSEQ and CyTOF, sampling many different

Image registration of BANG[reg] gel dose maps for quantitative dosimetry verification

International Nuclear Information System (INIS)

Meeks, Sanford L.; Bova, Frank J.; Maryanski, Marek J.; Kendrick, Lance A.; Ranade, Manisha K.; Buatti, John M.; Friedman, William A.

1999-01-01

Background: The BANG[reg] (product symbol SGEL, MGS Research Inc., Guilford, CT) polymer gel has been shown to be a valuable dosimeter for determining three-dimensional (3D) dose distributions. Because the proton relaxation rate (R2) of the gel changes as a function of absorbed dose, MR scans of the irradiated gel can be used to generate 3D dose maps. Previous work with the gel, however, has not relied on precise localization of the measured dose distribution. This has limited its quantitative use, as no precise correlation exists with the planned distribution. This paper reports on a technique for providing this correlation, thus providing a quality assurance tool that includes all of the steps of imaging, treatment planning, dose calculation, and treatment localization. Methods and Materials: The BANG[reg] gel formulation was prepared and poured into spherical flasks (15.3-cm inner diameter). A stereotactic head ring was attached to each flask. Three magnetic resonance imaging (MRI) and computed tomography (CT) compatible fiducial markers were placed on the flask, thus defining the central axial plane. A high-resolution CT scan was obtained of each flask. These images were transferred to a radiosurgery treatment-planning program, where treatment plans were developed. The gels were irradiated using our systems for stereotactic radiosurgery or fractionated stereotactic radiotherapy. The gels were MR imaged, and a relative 3D dose map was created from an R2 map of these images. The dose maps were transferred to an image-correlation program, and then fused to the treatment-planning CT scan through a rigid body match of the MRI/CT-compatible fiducial markers. The fused dose maps were imported into the treatment-planning system for quantitative comparison with the calculated treatment plans. Results: Calculated and measured isodose surfaces agreed to within 2 mm at the worst points within the in-plane dose distributions. This agreement is excellent, considering that

MRI technique for the snapshot imaging of quantitative velocity maps using RARE

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Shiko, G.; Sederman, A. J.; Gladden, L. F.

2012-03-01

A quantitative PGSE-RARE pulse sequence was developed and successfully applied to the in situ dissolution of two pharmaceutical formulations dissolving over a range of timescales. The new technique was chosen over other existing fast velocity imaging techniques because it is T2 weighted, not T2∗ weighted, and is, therefore, robust for imaging time-varying interfaces and flow in magnetically heterogeneous systems. The complex signal was preserved intact by separating odd and even echoes to obtain two phase maps which are then averaged in post-processing. Initially, the validity of the technique was shown when imaging laminar flow in a pipe. Subsequently, the dissolution of two drugs was followed in situ, where the technique enables the imaging and quantification of changes in the form of the tablet and the flow field surrounding it at high spatial and temporal resolution. First, the complete 3D velocity field around an eroding salicylic acid tablet was acquired at a resolution of 98 × 49 μm2, within 20 min, and monitored over ˜13 h. The tablet was observed to experience a heterogeneous flow field and, hence a heterogeneous shear field, which resulted in the non-symmetric erosion of the tablet. Second, the dissolution of a fast dissolving immediate release tablet was followed using one-shot 2D velocity images acquired every 5.2 s at a resolution of 390 × 390 μm2. The quantitative nature of the technique and fast acquisition times provided invaluable information on the dissolution behaviour of this tablet, which had not been attainable previously with conventional quantitative MRI techniques.

MRI technique for the snapshot imaging of quantitative velocity maps using RARE.

Science.gov (United States)

Shiko, G; Sederman, A J; Gladden, L F

2012-03-01

A quantitative PGSE-RARE pulse sequence was developed and successfully applied to the in situ dissolution of two pharmaceutical formulations dissolving over a range of timescales. The new technique was chosen over other existing fast velocity imaging techniques because it is T(2) weighted, not T(2)(∗) weighted, and is, therefore, robust for imaging time-varying interfaces and flow in magnetically heterogeneous systems. The complex signal was preserved intact by separating odd and even echoes to obtain two phase maps which are then averaged in post-processing. Initially, the validity of the technique was shown when imaging laminar flow in a pipe. Subsequently, the dissolution of two drugs was followed in situ, where the technique enables the imaging and quantification of changes in the form of the tablet and the flow field surrounding it at high spatial and temporal resolution. First, the complete 3D velocity field around an eroding salicylic acid tablet was acquired at a resolution of 98×49 μm(2), within 20 min, and monitored over ∼13 h. The tablet was observed to experience a heterogeneous flow field and, hence a heterogeneous shear field, which resulted in the non-symmetric erosion of the tablet. Second, the dissolution of a fast dissolving immediate release tablet was followed using one-shot 2D velocity images acquired every 5.2 s at a resolution of 390×390 μm(2). The quantitative nature of the technique and fast acquisition times provided invaluable information on the dissolution behaviour of this tablet, which had not been attainable previously with conventional quantitative MRI techniques. Copyright © 2012 Elsevier Inc. All rights reserved.

The effect of image sharpness on quantitative eye movement data and on image quality evaluation while viewing natural images

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Vuori, Tero; Olkkonen, Maria

2006-01-01

The aim of the study is to test both customer image quality rating (subjective image quality) and physical measurement of user behavior (eye movements tracking) to find customer satisfaction differences in imaging technologies. Methodological aim is to find out whether eye movements could be quantitatively used in image quality preference studies. In general, we want to map objective or physically measurable image quality to subjective evaluations and eye movement data. We conducted a series of image quality tests, in which the test subjects evaluated image quality while we recorded their eye movements. Results show that eye movement parameters consistently change according to the instructions given to the user, and according to physical image quality, e.g. saccade duration increased with increasing blur. Results indicate that eye movement tracking could be used to differentiate image quality evaluation strategies that the users have. Results also show that eye movements would help mapping between technological and subjective image quality. Furthermore, these results give some empirical emphasis to top-down perception processes in image quality perception and evaluation by showing differences between perceptual processes in situations when cognitive task varies.

Mass spectrometry for protein quantification in biomarker discovery.

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Wang, Mu; You, Jinsam

2012-01-01

Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

A quantitative measure of myelination development in infants, using MR images

International Nuclear Information System (INIS)

Carmody, Dennis P.; Dunn, Stanley M.; Boddie-Willis, Akiza S.; DeMarco, J. Kevin; Lewis, Michael

2004-01-01

The objective of this study was to measure myelination of frontal lobe changes in infants and young children. Twenty-four cases of infants and children (age range 12-121 months) were evaluated by a quantitative assessment of T2-weighted MR image features. Reliable quantitative changes between white and gray matter correlated with developmental age in a group of children with no neurological findings. Myelination appears to be an increasing exponential function with the greatest rate of change occurring over the first 3 years of life. The quantitative changes observed were in accordance with previous qualitative judgments of myelination development. Children with periventricular leukomalacia (PVL) showed delays in achieving levels of myelination when compared to normal children and adjusted for chronological age. The quantitative measure of myelination development may prove to be useful in assessing the stages of development and helpful in the quantitative descriptions of white matter disorders such as PVL. (orig.)

A quantitative measure of myelination development in infants, using MR images

Energy Technology Data Exchange (ETDEWEB)

Carmody, Dennis P. [Robert Wood Johnson Medical School, New Brunswick, NJ (United States); Dunn, Stanley M.; Boddie-Willis, Akiza S. [The State University of New Jersey, Rutgers, New Brunswick, NJ (United States); DeMarco, J. Kevin [Laurie Imaging Center, New Brunswick, NJ (United States); Lewis, Michael [Robert Wood Johnson Medical School, New Brunswick, NJ (United States); Robert Wood Johnson Medical School, University of Medicine and Dentistry of New Jersey, Institute for the Study of Child Development, New Brunswick (United States)

2004-09-01

The objective of this study was to measure myelination of frontal lobe changes in infants and young children. Twenty-four cases of infants and children (age range 12-121 months) were evaluated by a quantitative assessment of T2-weighted MR image features. Reliable quantitative changes between white and gray matter correlated with developmental age in a group of children with no neurological findings. Myelination appears to be an increasing exponential function with the greatest rate of change occurring over the first 3 years of life. The quantitative changes observed were in accordance with previous qualitative judgments of myelination development. Children with periventricular leukomalacia (PVL) showed delays in achieving levels of myelination when compared to normal children and adjusted for chronological age. The quantitative measure of myelination development may prove to be useful in assessing the stages of development and helpful in the quantitative descriptions of white matter disorders such as PVL. (orig.)

Diffusion Tensor Imaging as a Biomarker to Differentiate Acute Disseminated Encephalomyelitis From Multiple Sclerosis at First Demyelination.

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Aung, Wint Yan; Massoumzadeh, Parinaz; Najmi, Safa; Salter, Amber; Heaps, Jodi; Benzinger, Tammie L S; Mar, Soe

2018-01-01

There are no clinical features or biomarkers that can reliably differentiate acute disseminated encephalomyelitis from multiple sclerosis at the first demyelination attack. Consequently, a final diagnosis is sometimes delayed by months and years of follow-up. Early treatment for multiple sclerosis is recommended to reduce long-term disability. Therefore, we intend to explore neuroimaging biomarkers that can reliably distinguish between the two diagnoses. We reviewed prospectively collected clinical, standard MRI and diffusion tensor imaging data from 12 pediatric patients who presented with acute demyelination with and without encephalopathy. Patients were followed for an average of 6.5 years to determine the accuracy of final diagnosis. Final diagnosis was determined using 2013 International Pediatric MS Study Group criteria. Control subjects consisted of four age-matched healthy individuals for each patient. The study population consisted of six patients with central nervous system demyelination with encephalopathy with a presumed diagnosis of acute disseminated encephalomyelitis and six without encephalopathy with a presumed diagnosis of multiple sclerosis or clinically isolated syndrome at high risk for multiple sclerosis. During follow-up, two patients with initial diagnosis of acute disseminated encephalomyelitis were later diagnosed with multiple sclerosis. Diffusion tensor imaging region of interest analysis of baseline scans showed differences between final diagnosis of multiple sclerosis and acute disseminated encephalomyelitis patients, whereby low fractional anisotropy and high radial diffusivity occurred in multiple sclerosis patients compared with acute disseminated encephalomyelitis patients and the age-matched controls. Fractional anisotropy and radial diffusivity measures may have the potential to serve as biomarkers for distinguishing acute disseminated encephalomyelitis from multiple sclerosis at the onset. Copyright © 2017 Elsevier Inc. All

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

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Sung, Myong-Hee

2013-01-01

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

Quantitative analysis of γ-oryzanol content in cold pressed rice bran oil by TLC-image analysis method.

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Sakunpak, Apirak; Suksaeree, Jirapornchai; Monton, Chaowalit; Pathompak, Pathamaporn; Kraisintu, Krisana

2014-02-01

To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. TLC-densitometric and TLC-image analysis methods were developed, validated, and used for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. The results obtained by these two different quantification methods were compared by paired t-test. Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. The TLC-densitometric and TLC-image analysis methods provided a similar reproducibility, accuracy and selectivity for the quantitative determination of γ-oryzanol in cold pressed rice bran oil. A statistical comparison of the quantitative determinations of γ-oryzanol in samples did not show any statistically significant difference between TLC-densitometric and TLC-image analysis methods. As both methods were found to be equal, they therefore can be used for the determination of γ-oryzanol in cold pressed rice bran oil.

Phase II cancer clinical trials for biomarker-guided treatments.

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Jung, Sin-Ho

2018-01-01

The design and analysis of cancer clinical trials with biomarker depend on various factors, such as the phase of trials, the type of biomarker, whether the used biomarker is validated or not, and the study objectives. In this article, we demonstrate the design and analysis of two Phase II cancer clinical trials, one with a predictive biomarker and the other with an imaging prognostic biomarker. Statistical testing methods and their sample size calculation methods are presented for each trial. We assume that the primary endpoint of these trials is a time to event variable, but this concept can be used for any type of endpoint.

A quantitative experimental phantom study on MRI image uniformity.

Science.gov (United States)

Felemban, Doaa; Verdonschot, Rinus G; Iwamoto, Yuri; Uchiyama, Yuka; Kakimoto, Naoya; Kreiborg, Sven; Murakami, Shumei

2018-05-02

Our goal was to assess MR image uniformity by investigating aspects influencing said uniformity via a method laid out by the National Electrical Manufacturers Association (NEMA). Six metallic materials embedded in a glass phantom were scanned (i.e., Au, Ag, Al, Au-Ag-Pd alloy, Ti and Co-Cr alloy) as well as a reference image. Sequences included Spin Echo (SE) and gradient echo (GRE) scanned in three planes (i.e., Axial, Coronal, and Sagittal). Moreover, three surface coil types (i.e., Head and Neck or HN, Brain, and TMJ coils) and two image correction methods (i.e., Surface Coil Intensity Correction or SCIC, Phased array Uniformity Enhancement or PURE) were employed to evaluate their effectiveness on image uniformity. Image uniformity was assessed using the NEMA peak-deviation non-uniformity method. Results showed that TMJ coils elicited the least uniform image and Brain coils outperformed HN coils when metallic materials were present. Additionally, when metallic materials were present, SE outperformed GRE especially for Co-Cr (particularly in the axial plane). Furthermore, both SCIC and PURE improved image uniformity compared to uncorrected images, and SCIC slightly surpassed PURE when metallic metals were present. Lastly, Co-Cr elicited the least uniform image while other metallic materials generally showed similar patterns (i.e., no significant deviation from images without metallic metals). Overall, a quantitative understanding of the factors influencing MR image uniformity (e.g., coil type, imaging method, metal susceptibility, and post-hoc correction method) is advantageous to optimize image quality, assists clinical interpretation, and may result in improved medical and dental care.

Hepatic iron overload: Quantitative MR imaging

International Nuclear Information System (INIS)

Gomori, J.M.; Horev, G.; Tamary, H.; Zandback, J.; Kornreich, L.; Zaizov, R.; Freud, E.; Krief, O.; Ben-Meir, J.; Rotem, H.

1991-01-01

Iron deposits demonstrate characteristically shortened T2 relaxation times. Several previously published studies reported poor correlation between the in vivo hepatic 1/T2 measurements made by means of midfield magnetic resonance (MR) units and the hepatic iron content of iron-overloaded patients. In this study, the authors assessed the use of in vivo 1/T2 measurements obtained by means of MR imaging at 0.5 T using short echo times (13.4 and 30 msec) and single-echo-sequences as well as computed tomographic (CT) attenuation as a measure of liver iron concentration in 10 severely iron-overloaded patients with beta-thalassemia major. The iron concentrations in surgical wedge biopsy samples of the liver, which varied between 3 and 9 mg/g of wet weight (normal, less than or equal to 0.5 mg/g), correlated well (r = .93, P less than or equal to .0001) with the preoperative in vivo hepatic 1/T2 measurements. The CT attenuation did not correlate with liver iron concentration. Quantitative MR imaging is a readily available noninvasive method for the assessment of hepatic iron concentration in iron-overloaded patients, reducing the need for needle biopsies of the liver

Transferring biomarker into molecular probe: melanin nanoparticle as a naturally active platform for multimodality imaging.

Science.gov (United States)

Fan, Quli; Cheng, Kai; Hu, Xiang; Ma, Xiaowei; Zhang, Ruiping; Yang, Min; Lu, Xiaomei; Xing, Lei; Huang, Wei; Gambhir, Sanjiv Sam; Cheng, Zhen

2014-10-29

Developing multifunctional and easily prepared nanoplatforms with integrated different modalities is highly challenging for molecular imaging. Here, we report the successful transfer of an important molecular target, melanin, into a novel multimodality imaging nanoplatform. Melanin is abundantly expressed in melanotic melanomas and thus has been actively studied as a target for melanoma imaging. In our work, the multifunctional biopolymer nanoplatform based on ultrasmall (passive nanoplatforms require complicated and time-consuming processes for prebuilding reporting moieties or chemical modifications using active groups to integrate different contrast properties into one entity. In comparison, utilizing functional biomarker melanin can greatly simplify the building process. We further conjugated αvβ3 integrins, cyclic c(RGDfC) peptide, to MNPs to allow for U87MG tumor accumulation due to its targeting property combined with the enhanced permeability and retention (EPR) effect. The multimodal properties of MNPs demonstrate the high potential of endogenous materials with multifunctions as nanoplatforms for molecular theranostics and clinical translation.

Quantitative aspects of myocardial perfusion imaging

International Nuclear Information System (INIS)

Vogel, R.A.

1980-01-01

Myocardial perfusion measurements have traditionally been performed in a quantitative fashion using application of the Sapirstein, Fick, Kety-Schmidt, or compartmental analysis principles. Although global myocardial blood flow measurements have not proven clinically useful, regional determinations have substantially advanced our understanding of and ability to detect myocardial ischemia. With the introduction of thallium-201, such studies have become widely available, although these have generally undergone qualitative evaluation. Using computer-digitized data, several methods for the quantification of myocardial perfusion images have been introduced. These include orthogonal and polar coordinate systems and anatomically oriented region of interest segmentation. Statistical ranges of normal and time-activity analyses have been applied to these data, resulting in objective and reproducible means of data evaluation

Quantitative magnetic resonance imaging for stroke research in the pharmaceutical industry

International Nuclear Information System (INIS)

Eis, M.; Neumaier, M.; Pschorn, U.

1998-01-01

In conclusion, quantitative NMR imaging is a valuable method for monitoring the volume and degree of severity of cerebral lesions and therapeutic effects over time. Thus, it is an important tool for evaluating the efficacy of cerebroprotective drugs in vivo. (orig.)

Comparative study of quantitative phase imaging techniques for refractometry of optical fibers

Science.gov (United States)

de Dorlodot, Bertrand; Bélanger, Erik; Bérubé, Jean-Philippe; Vallée, Réal; Marquet, Pierre

2018-02-01

The refractive index difference profile of optical fibers is the key design parameter because it determines, among other properties, the insertion losses and propagating modes. Therefore, an accurate refractive index profiling method is of paramount importance to their development and optimization. Quantitative phase imaging (QPI) is one of the available tools to retrieve structural characteristics of optical fibers, including the refractive index difference profile. Having the advantage of being non-destructive, several different QPI methods have been developed over the last decades. Here, we present a comparative study of three different available QPI techniques, namely the transport-of-intensity equation, quadriwave lateral shearing interferometry and digital holographic microscopy. To assess the accuracy and precision of those QPI techniques, quantitative phase images of the core of a well-characterized optical fiber have been retrieved for each of them and a robust image processing procedure has been applied in order to retrieve their refractive index difference profiles. As a result, even if the raw images for all the three QPI methods were suffering from different shortcomings, our robust automated image-processing pipeline successfully corrected these. After this treatment, all three QPI techniques yielded accurate, reliable and mutually consistent refractive index difference profiles in agreement with the accuracy and precision of the refracted near-field benchmark measurement.

T2-weighted MR imaging of the liver: Qualitative and quantitative comparison of SPACE MR imaging with turbo spin-echo MR imaging

Energy Technology Data Exchange (ETDEWEB)

Dohan, Anthony, E-mail: anthony.dohan@lrb.aphp.fr [Department of Body and Interventional Imaging, Hôpital Lariboisière, AP-HP, 2 Rue Ambroise Paré, 75475 Paris Cedex 10 (France); Université Paris-Diderot, Sorbonne Paris Cité, 10 Rue de Verdun, 75010 Paris (France); UMR INSERM 965, Hôpital Lariboisière, 2 Rue Amboise Paré, 75010 Paris (France); Gavini, Jean-Philippe, E-mail: jpgavini@gmail.com [Department of Body and Interventional Imaging, Hôpital Lariboisière, AP-HP, 2 Rue Ambroise Paré, 75475 Paris Cedex 10 (France); Université Paris-Diderot, Sorbonne Paris Cité, 10 Rue de Verdun, 75010 Paris (France); Placé, Vinciane, E-mail: vinciane.place@gmail.com [Department of Body and Interventional Imaging, Hôpital Lariboisière, AP-HP, 2 Rue Ambroise Paré, 75475 Paris Cedex 10 (France); Sebbag, Delphine, E-mail: delphinesebbag@gmail.com [Department of Body and Interventional Imaging, Hôpital Lariboisière, AP-HP, 2 Rue Ambroise Paré, 75475 Paris Cedex 10 (France); Université Paris-Diderot, Sorbonne Paris Cité, 10 Rue de Verdun, 75010 Paris (France); Vignaud, Alexandre, E-mail: alexandre.vignaud@cea.fr [LRMN, Neurospin, CEA-SACLAY, Bâtiment 145, 91 191 Gif-sur-Yvette Cedex (France); and others

2013-11-01

Objective: To qualitatively and quantitatively compare T2-weighted MR imaging of the liver using volumetric spin-echo with sampling perfection with application-optimized contrast using different flip angle evolutions (SPACE) with conventional turbo spin-echo (TSE) sequence for fat-suppressed T2-weighted MR imaging of the liver. Materials and methods: Thirty-three patients with suspected focal liver lesions had SPACE MR imaging and conventional fat-suppressed TSE MR imaging. Images were analyzed quantitatively by measuring the lesion-to-liver contrast-to-noise ratio (CNR), and the signal-to-noise ratio (SNR) of main focal hepatic lesions, hepatic and splenic parenchyma and qualitatively by evaluating the presence of vascular, respiratory motion and cardiac artifacts. Wilcoxon signed rank test was used to search for differences between the two sequences. Results: SPACE MR imaging showed significantly greater CNR for focal liver lesions (median = 22.82) than TSE MR imaging (median = 14.15) (P < .001). No differences were found for SNR of hepatic parenchyma (P = .097), main focal hepatic lesions (P = .35), and splenic parenchyma (P = .25). SPACE sequence showed less artifacts than TSE sequence (vascular, P < .001; respiratory motion, P < .001; cardiac, P < .001) but needed a longer acquisition time (228.4 vs. 162.1 s; P < .001). Conclusion: SPACE MR imaging provides a significantly increased CNR for focal liver lesions and less artifacts by comparison with the conventional TSE sequence. These results should stimulate further clinical studies with a surgical standard of reference to compare the two techniques in terms of sensitivity for malignant lesions.

Objective evaluation of reconstruction methods for quantitative SPECT imaging in the absence of ground truth.

Science.gov (United States)

Jha, Abhinav K; Song, Na; Caffo, Brian; Frey, Eric C

2015-04-13

Quantitative single-photon emission computed tomography (SPECT) imaging is emerging as an important tool in clinical studies and biomedical research. There is thus a need for optimization and evaluation of systems and algorithms that are being developed for quantitative SPECT imaging. An appropriate objective method to evaluate these systems is by comparing their performance in the end task that is required in quantitative SPECT imaging, such as estimating the mean activity concentration in a volume of interest (VOI) in a patient image. This objective evaluation can be performed if the true value of the estimated parameter is known, i.e. we have a gold standard. However, very rarely is this gold standard known in human studies. Thus, no-gold-standard techniques to optimize and evaluate systems and algorithms in the absence of gold standard are required. In this work, we developed a no-gold-standard technique to objectively evaluate reconstruction methods used in quantitative SPECT when the parameter to be estimated is the mean activity concentration in a VOI. We studied the performance of the technique with realistic simulated image data generated from an object database consisting of five phantom anatomies with all possible combinations of five sets of organ uptakes, where each anatomy consisted of eight different organ VOIs. Results indicate that the method provided accurate ranking of the reconstruction methods. We also demonstrated the application of consistency checks to test the no-gold-standard output.

Applying quantitative benefit-risk analysis to aid regulatory decision making in diagnostic imaging: methods, challenges, and opportunities.

Science.gov (United States)

Agapova, Maria; Devine, Emily Beth; Bresnahan, Brian W; Higashi, Mitchell K; Garrison, Louis P

2014-09-01

Health agencies making regulatory marketing-authorization decisions use qualitative and quantitative approaches to assess expected benefits and expected risks associated with medical interventions. There is, however, no universal standard approach that regulatory agencies consistently use to conduct benefit-risk assessment (BRA) for pharmaceuticals or medical devices, including for imaging technologies. Economics, health services research, and health outcomes research use quantitative approaches to elicit preferences of stakeholders, identify priorities, and model health conditions and health intervention effects. Challenges to BRA in medical devices are outlined, highlighting additional barriers in radiology. Three quantitative methods--multi-criteria decision analysis, health outcomes modeling and stated-choice survey--are assessed using criteria that are important in balancing benefits and risks of medical devices and imaging technologies. To be useful in regulatory BRA, quantitative methods need to: aggregate multiple benefits and risks, incorporate qualitative considerations, account for uncertainty, and make clear whose preferences/priorities are being used. Each quantitative method performs differently across these criteria and little is known about how BRA estimates and conclusions vary by approach. While no specific quantitative method is likely to be the strongest in all of the important areas, quantitative methods may have a place in BRA of medical devices and radiology. Quantitative BRA approaches have been more widely applied in medicines, with fewer BRAs in devices. Despite substantial differences in characteristics of pharmaceuticals and devices, BRA methods may be as applicable to medical devices and imaging technologies as they are to pharmaceuticals. Further research to guide the development and selection of quantitative BRA methods for medical devices and imaging technologies is needed. Copyright © 2014 AUR. Published by Elsevier Inc. All rights

Identification and validation of biomarkers of IgV(H) mutation status in chronic lymphocytic leukemia using microfluidics quantitative real-time polymerase chain reaction technology.

Science.gov (United States)

Abruzzo, Lynne V; Barron, Lynn L; Anderson, Keith; Newman, Rachel J; Wierda, William G; O'brien, Susan; Ferrajoli, Alessandra; Luthra, Madan; Talwalkar, Sameer; Luthra, Rajyalakshmi; Jones, Dan; Keating, Michael J; Coombes, Kevin R

2007-09-01

To develop a model incorporating relevant prognostic biomarkers for untreated chronic lymphocytic leukemia patients, we re-analyzed the raw data from four published gene expression profiling studies. We selected 88 candidate biomarkers linked to immunoglobulin heavy-chain variable region gene (IgV(H)) mutation status and produced a reliable and reproducible microfluidics quantitative real-time polymerase chain reaction array. We applied this array to a training set of 29 purified samples from previously untreated patients. In an unsupervised analysis, the samples clustered into two groups. Using a cutoff point of 2% homology to the germline IgV(H) sequence, one group contained all 14 IgV(H)-unmutated samples; the other contained all 15 mutated samples. We confirmed the differential expression of 37 of the candidate biomarkers using two-sample t-tests. Next, we constructed 16 different models to predict IgV(H) mutation status and evaluated their performance on an independent test set of 20 new samples. Nine models correctly classified 11 of 11 IgV(H)-mutated cases and eight of nine IgV(H)-unmutated cases, with some models using three to seven genes. Thus, we can classify cases with 95% accuracy based on the expression of as few as three genes.

Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning

Science.gov (United States)

Nguyen, Tan H.; Sridharan, Shamira; Macias, Virgilia; Kajdacsy-Balla, Andre; Melamed, Jonathan; Do, Minh N.; Popescu, Gabriel

2017-03-01

We present an approach for automatic diagnosis of tissue biopsies. Our methodology consists of a quantitative phase imaging tissue scanner and machine learning algorithms to process these data. We illustrate the performance by automatic Gleason grading of prostate specimens. The imaging system operates on the principle of interferometry and, as a result, reports on the nanoscale architecture of the unlabeled specimen. We use these data to train a random forest classifier to learn textural behaviors of prostate samples and classify each pixel in the image into different classes. Automatic diagnosis results were computed from the segmented regions. By combining morphological features with quantitative information from the glands and stroma, logistic regression was used to discriminate regions with Gleason grade 3 versus grade 4 cancer in prostatectomy tissue. The overall accuracy of this classification derived from a receiver operating curve was 82%, which is in the range of human error when interobserver variability is considered. We anticipate that our approach will provide a clinically objective and quantitative metric for Gleason grading, allowing us to corroborate results across instruments and laboratories and feed the computer algorithms for improved accuracy.

Use of local noise power spectrum and wavelet analysis in quantitative image quality assurance for EPIDs

Energy Technology Data Exchange (ETDEWEB)

Lee, Soyoung [Department of Radiation Oncology, University Hospitals Case and Medical Center, Cleveland, Ohio 44106 (United States); Yan, Guanghua; Bassett, Philip; Samant, Sanjiv, E-mail: samant@ufl.edu [Department of Radiation Oncology, University of Florida College of Medicine, Gainesville, Florida 32608 (United States); Gopal, Arun [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201 (United States)

2016-09-15

Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanel of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two

Simple and fast spectral domain algorithm for quantitative phase imaging of living cells with digital holographic microscopy

Science.gov (United States)

Min, Junwei; Yao, Baoli; Ketelhut, Steffi; Kemper, Björn

2017-02-01

The modular combination of optical microscopes with digital holographic microscopy (DHM) has been proven to be a powerful tool for quantitative live cell imaging. The introduction of condenser and different microscope objectives (MO) simplifies the usage of the technique and makes it easier to measure different kinds of specimens with different magnifications. However, the high flexibility of illumination and imaging also causes variable phase aberrations that need to be eliminated for high resolution quantitative phase imaging. The existent phase aberrations compensation methods either require add additional elements into the reference arm or need specimen free reference areas or separate reference holograms to build up suitable digital phase masks. These inherent requirements make them unpractical for usage with highly variable illumination and imaging systems and prevent on-line monitoring of living cells. In this paper, we present a simple numerical method for phase aberration compensation based on the analysis of holograms in spatial frequency domain with capabilities for on-line quantitative phase imaging. From a single shot off-axis hologram, the whole phase aberration can be eliminated automatically without numerical fitting or pre-knowledge of the setup. The capabilities and robustness for quantitative phase imaging of living cancer cells are demonstrated.

Nuclear medicine and imaging research. Instrumentation and quantitative methods of evaluation. Progress report, January 15, 1985-January 14, 1986

International Nuclear Information System (INIS)

Beck, R.N.; Cooper, M.D.

1985-09-01

This program of research addresses problems involving the basic science and technology of radioactive tracer methods as they relate to nuclear medicine and imaging. The broad goal is to develop new instruments and methods for image formation, processing, quantitation, and display, so as to maximize the diagnostic information per unit of absorbed radiation dose to the patient. These developments are designed to meet the needs imposed by new radiopharmaceuticals developed to solve specific biomedical problems, as well as to meet the instrumentation needs associated with radiopharmaceutical production and quantitative clinical feasibility studies of the brain with PET VI. Project I addresses problems associated with the quantitative imaging of single-photon emitters; Project II addresses similar problems associated with the quantitative imaging of positron emitters; Project III addresses methodological problems associated with the quantitative evaluation of the efficacy of diagnostic imaging procedures. The original proposal covered work to be carried out over the three-year contract period. This report covers progress made during Year Three. 36 refs., 1 tab

Image evaluation of HIV encephalopathy: a multimodal approach using quantitative MR techniques

Energy Technology Data Exchange (ETDEWEB)

Prado, Paulo T.C.; Escorsi-Rosset, Sara [University of Sao Paulo, Radiology Section, Internal Medicine Department, Ribeirao Preto School of Medicine, Sao Paulo (Brazil); Cervi, Maria C. [University of Sao Paulo, Department of Pediatrics, Ribeirao Preto School of Medicine, Sao Paulo (Brazil); Santos, Antonio Carlos [University of Sao Paulo, Radiology Section, Internal Medicine Department, Ribeirao Preto School of Medicine, Sao Paulo (Brazil); Hospital das Clinicas da FMRP-USP, Ribeirao Preto, SP (Brazil)

2011-11-15

A multimodal approach of the human immunodeficiency virus (HIV) encephalopathy using quantitative magnetic resonance (MR) techniques can demonstrate brain changes not detectable only with conventional magnetic resonance imaging (MRI). The aim of this study was to compare conventional MRI and MR quantitative techniques, such as magnetic resonance spectroscopy (MRS) and relaxometry and to determine whether quantitative techniques are more sensitive than conventional imaging for brain changes caused by HIV infection. We studied prospectively nine HIV positive children (mean age 6 years, from 5 to 8 years old) and nine controls (mean age 7.3 years; from 3 to 10 years), using MRS and relaxometry. Examinations were carried on 1.5-T equipment. HIV-positive patients presented with only minor findings and all control patients had normal conventional MR findings. MRS findings showed an increase in choline to creatine (CHO/CRE) ratios bilaterally in both frontal gray and white matter, in the left parietal white matter, and in total CHO/CRE ratio. In contrast, N-acetylaspartate to creatine (NAA/CRE) ratios did not present with any significant difference between both groups. Relaxometry showed significant bilateral abnormalities, with lengthening of the relaxation time in HIV positive in many regions. Conventional MRI is not sensitive for early brain changes caused by HIV infection. Quantitative techniques such as MRS and relaxometry appear as valuable tools in the diagnosis of these early changes. Therefore, a multimodal quantitative study can be useful in demonstrating and understanding the physiopathology of the disease. (orig.)

AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

Science.gov (United States)

Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

2011-01-01

Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method

Quantitative imaging of a non-combusting diesel spray using structured laser illumination planar imaging

Science.gov (United States)

Berrocal, E.; Kristensson, E.; Hottenbach, P.; Aldén, M.; Grünefeld, G.

2012-12-01

Due to its transient nature, high atomization process, and rapid generation of fine evaporating droplets, diesel sprays have been, and still remain, one of the most challenging sprays to be fully analyzed and understood by means of non-intrusive diagnostics. The main limitation of laser techniques for quantitative measurements of diesel sprays concerns the detection of the multiple light scattering resulting from the high optical density of such a scattering medium. A second limitation is the extinction of the incident laser radiation as it crosses the spray, as well as the attenuation of the signal which is to be detected. All these issues have strongly motivated, during the past decade, the use of X-ray instead of visible light for dense spray diagnostics. However, we demonstrate in this paper that based on an affordable Nd:YAG laser system, structured laser illumination planar imaging (SLIPI) can provide accurate quantitative description of a non-reacting diesel spray injected at 1,100 bar within a room temperature vessel pressurized at 18.6 bar. The technique is used at λ = 355 nm excitation wavelength with 1.0 mol% TMPD dye concentration, for simultaneous LIF/Mie imaging. Furthermore, a novel dual-SLIPI configuration is tested with Mie scattering detection only. The results confirm that a mapping of both the droplet Sauter mean diameter and extinction coefficient can be obtained by such complementary approaches. These new insights are provided in this article at late times after injection start. It is demonstrated that the application of SLIPI to diesel sprays provides valuable quantitative information which was not previously accessible.

Quantitative image of bone mineral content

International Nuclear Information System (INIS)

Katoh, Tsuguhisa

1990-01-01

A dual energy subtraction system was constructed on an experimental basis for the quantitative image of bone mineral content. The system consists of a radiographing system and an image processor. Two radiograms were taken with dual x-ray energy in a single exposure using an x-ray beam dichromized by a tin filter. In this system, a film cassette was used where a low speed film-screen system, a copper filter and a high speed film-screen system were layered on top of each other. The images were read by a microdensitometer and processed by a personal computer. The image processing included the corrections of the film characteristics and heterogeneity in the x-ray field, and the dual energy subtraction in which the effect of the high energy component of the dichromized beam on the tube side image was corrected. In order to determine the accuracy of the system, experiments using wedge phantoms made of mixtures of epoxy resin and bone mineral-equivalent materials in various fractions were performed for various tube potentials and film processing conditions. The results indicated that the relative precision of the system was within ±4% and that the propagation of the film noise was within ±11 mg/cm 2 for the 0.2 mm pixels. The results also indicated that the system response was independent of the tube potential and the film processing condition. The bone mineral weight in each phalanx of the freshly dissected hand of a rhesus monkey was measured by this system and compared with the ash weight. The results showed an error of ±10%, slightly larger than that of phantom experiments, which is probably due to the effect of fat and the variation of focus-object distance. The air kerma in free air at the object was approximately 0.5 mGy for one exposure. The results indicate that this system is applicable to clinical use and provides useful information for evaluating a time-course of localized bone disease. (author)

NOTE: An innovative phantom for quantitative and qualitative investigation of advanced x-ray imaging technologies

Science.gov (United States)

Chiarot, C. B.; Siewerdsen, J. H.; Haycocks, T.; Moseley, D. J.; Jaffray, D. A.

2005-11-01

Development, characterization, and quality assurance of advanced x-ray imaging technologies require phantoms that are quantitative and well suited to such modalities. This note reports on the design, construction, and use of an innovative phantom developed for advanced imaging technologies (e.g., multi-detector CT and the numerous applications of flat-panel detectors in dual-energy imaging, tomosynthesis, and cone-beam CT) in diagnostic and image-guided procedures. The design addresses shortcomings of existing phantoms by incorporating criteria satisfied by no other single phantom: (1) inserts are fully 3D—spherically symmetric rather than cylindrical; (2) modules are quantitative, presenting objects of known size and contrast for quality assurance and image quality investigation; (3) features are incorporated in ideal and semi-realistic (anthropomorphic) contexts; and (4) the phantom allows devices to be inserted and manipulated in an accessible module (right lung). The phantom consists of five primary modules: (1) head, featuring contrast-detail spheres approximate to brain lesions; (2) left lung, featuring contrast-detail spheres approximate to lung modules; (3) right lung, an accessible hull in which devices may be placed and manipulated; (4) liver, featuring conrast-detail spheres approximate to metastases; and (5) abdomen/pelvis, featuring simulated kidneys, colon, rectum, bladder, and prostate. The phantom represents a two-fold evolution in design philosophy—from 2D (cylindrically symmetric) to fully 3D, and from exclusively qualitative or quantitative to a design accommodating quantitative study within an anatomical context. It has proven a valuable tool in investigations throughout our institution, including low-dose CT, dual-energy radiography, and cone-beam CT for image-guided radiation therapy and surgery.

Quantitative volumetric Raman imaging of three dimensional cell cultures

KAUST Repository

Kallepitis, Charalambos

2017-03-22

The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell–material interactions. Here, we present a computational framework for label-free quantitative volumetric Raman imaging (qVRI). We apply qVRI to a selection of biological systems: human pluripotent stem cells with their cardiac derivatives, monocytes and monocyte-derived macrophages in conventional cell culture systems and mesenchymal stem cells inside biomimetic hydrogels that supplied a 3D cell culture environment. We demonstrate visualization and quantification of fine details in cell shape, cytoplasm, nucleus, lipid bodies and cytoskeletal structures in 3D with unprecedented biomolecular specificity for vibrational microspectroscopy.

Quantitative volumetric Raman imaging of three dimensional cell cultures

Science.gov (United States)

Kallepitis, Charalambos; Bergholt, Mads S.; Mazo, Manuel M.; Leonardo, Vincent; Skaalure, Stacey C.; Maynard, Stephanie A.; Stevens, Molly M.

2017-03-01

The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell-material interactions. Here, we present a computational framework for label-free quantitative volumetric Raman imaging (qVRI). We apply qVRI to a selection of biological systems: human pluripotent stem cells with their cardiac derivatives, monocytes and monocyte-derived macrophages in conventional cell culture systems and mesenchymal stem cells inside biomimetic hydrogels that supplied a 3D cell culture environment. We demonstrate visualization and quantification of fine details in cell shape, cytoplasm, nucleus, lipid bodies and cytoskeletal structures in 3D with unprecedented biomolecular specificity for vibrational microspectroscopy.

[Quantitative magnetic resonance imaging of brain iron deposition: comparison between quantitative susceptibility mapping and transverse relaxation rate (R2*) mapping].

Science.gov (United States)

Guan, Ji-Jing; Feng, Yan-Qiu

2018-03-20

To evaluate the accuracy and sensitivity of quantitative susceptibility mapping (QSM) and transverse relaxation rate (R2*) mapping in the measurement of brain iron deposition. Super paramagnetic iron oxide (SPIO) phantoms and mouse models of Parkinson's disease (PD) related to iron deposition in the substantia nigra (SN) underwent 7.0 T magnetic resonance (MR) scans (Bruker, 70/16) with a multi-echo 3D gradient echo sequence, and the acquired data were processed to obtain QSM and R2*. Linear regression analysis was performed for susceptibility and R2* in the SPIO phantoms containing 5 SPIO concentrations (30, 15, 7.5, 3.75 and 1.875 µg/mL) to evaluate the accuracy of QSM and R2* in quantitative iron analysis. The sensitivities of QSM and R2* mapping in quantitative detection of brain iron deposition were assessed using mouse models of PD induced by 1-methyl-4-phenyl-1,2,3,6-tetrahy-dropyridine (MPTP) in comparison with the control mice. In SPIO phantoms, QSM provided a higher accuracy than R2* mapping and their goodness-of-fit coefficients (R 2 ) were 0.98 and 0.89, respectively. In the mouse models of PD and control mice, the susceptibility of the SN was significantly higher in the PD models (5.19∓1.58 vs 2.98∓0.88, n=5; Pbrain iron deposition than R2*, and the susceptibility derived by QSM can be a potentially useful biomarker for studying PD.

Searching for non-genetic molecular and imaging PTSD risk and resilience markers: Systematic review of literature and design of the German Armed Forces PTSD biomarker study.

Science.gov (United States)

Schmidt, Ulrike; Willmund, Gerd-Dieter; Holsboer, Florian; Wotjak, Carsten T; Gallinat, Jürgen; Kowalski, Jens T; Zimmermann, Peter

2015-01-01

Biomarkers allowing the identification of individuals with an above average vulnerability or resilience for posttraumatic stress disorder (PTSD) would especially serve populations at high risk for trauma exposure like firefighters, police officers and combat soldiers. Aiming to identify the most promising putative PTSD vulnerability markers, we conducted the first systematic review on potential imaging and non-genetic molecular markers for PTSD risk and resilience. Following the PRISMA guidelines, we systematically screened the PubMed database for prospective longitudinal clinical studies and twin studies reporting on pre-trauma and post-trauma PTSD risk and resilience biomarkers. Using 25 different combinations of search terms, we retrieved 8151 articles of which we finally included and evaluated 9 imaging and 27 molecular studies. In addition, we briefly illustrate the design of the ongoing prospective German Armed Forces (Bundeswehr) PTSD biomarker study (Bw-BioPTSD) which not only aims to validate these previous findings but also to identify novel and clinically applicable molecular, psychological and imaging risk, resilience and disease markers for deployment-related psychopathology in a cohort of German soldiers who served in Afghanistan. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quantitative imaging analysis of posterior fossa ependymoma location in children.

Science.gov (United States)

Sabin, Noah D; Merchant, Thomas E; Li, Xingyu; Li, Yimei; Klimo, Paul; Boop, Frederick A; Ellison, David W; Ogg, Robert J

2016-08-01

Imaging descriptions of posterior fossa ependymoma in children have focused on magnetic resonance imaging (MRI) signal and local anatomic relationships with imaging location only recently used to classify these neoplasms. We developed a quantitative method for analyzing the location of ependymoma in the posterior fossa, tested its effectiveness in distinguishing groups of tumors, and examined potential associations of distinct tumor groups with treatment and prognostic factors. Pre-operative MRI examinations of the brain for 38 children with histopathologically proven posterior fossa ependymoma were analyzed. Tumor margin contours and anatomic landmarks were manually marked and used to calculate the centroid of each tumor. Landmarks were used to calculate a transformation to align, scale, and rotate each patient's image coordinates to a common coordinate space. Hierarchical cluster analysis of the location and morphological variables was performed to detect multivariate patterns in tumor characteristics. The ependymomas were also characterized as "central" or "lateral" based on published radiological criteria. Therapeutic details and demographic, recurrence, and survival information were obtained from medical records and analyzed with the tumor location and morphology to identify prognostic tumor characteristics. Cluster analysis yielded two distinct tumor groups based on centroid location The cluster groups were associated with differences in PFS (p = .044), "central" vs. "lateral" radiological designation (p = .035), and marginally associated with multiple operative interventions (p = .064). Posterior fossa ependymoma can be objectively classified based on quantitative analysis of tumor location, and these classifications are associated with prognostic and treatment factors.

Non-contact assessment of obstructive sleep apnea cardiovascular biomarkers using photoplethysmography imaging

Science.gov (United States)

Amelard, Robert; Pfisterer, Kaylen J.; Jagani, Shubh; Clausi, David A.; Wong, Alexander

2018-02-01

Obstructive sleep apnea (OSA) affects 20% of the adult population, and is associated with cardiovascular and cognitive morbidities. However, it is estimated that up to 80% of treatable OSA cases remain undiagnosed. Cur- rent methods for diagnosing OSA are expensive, labor-intensive, and involve uncomfortable wearable sensors. This study explored the feasibility of non-contact biophotonic assessment of OSA cardiovascular biomarkers via photoplethysmography imaging (PPGI). In particular, PPGI was used to monitor the hemodynamic response to obstructive respiratory events. Sleep apnea onset was simulated using Muller's maneuver in which breathing was obstructed by a respiratory clamp. A custom PPGI system, coded hemodynamic imaging (CHI), was positioned 1 m above the bed and illuminated the participant's head with 850 nm light, providing non-intrusive illumination for night-time monitoring. A video was recorded before, during and following an apnea event at 60 fps, yielding 17 ms temporal resolution. Per-pixel absorbance signals were extracted using a Beer-Lambert derived light transport model, and subsequently denoised. The extracted hemodynamic signal exhibited dynamic temporal modulation during and following the apnea event. In particular, the pulse wave amplitude (PWA) decreased during obstructed breathing, indicating vasoconstriction. Upon successful inhalation, the PWA gradually increased toward homeostasis following a temporal phase delay. This temporal vascular tone modulation provides insight into autonomic and vascular response, and may be used to assess sleep apnea using non-contact biophotonic imaging.

Activated sludge characterization through microscopy: A review on quantitative image analysis and chemometric techniques

Energy Technology Data Exchange (ETDEWEB)

Mesquita, Daniela P. [IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057 Braga (Portugal); Amaral, A. Luís [IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057 Braga (Portugal); Instituto Politécnico de Coimbra, ISEC, DEQB, Rua Pedro Nunes, Quinta da Nora, 3030-199 Coimbra (Portugal); Ferreira, Eugénio C., E-mail: ecferreira@deb.uminho.pt [IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057 Braga (Portugal)

2013-11-13

Graphical abstract: -- Highlights: •Quantitative image analysis shows potential to monitor activated sludge systems. •Staining techniques increase the potential for detection of operational problems. •Chemometrics combined with quantitative image analysis is valuable for process monitoring. -- Abstract: In wastewater treatment processes, and particularly in activated sludge systems, efficiency is quite dependent on the operating conditions, and a number of problems may arise due to sludge structure and proliferation of specific microorganisms. In fact, bacterial communities and protozoa identification by microscopy inspection is already routinely employed in a considerable number of cases. Furthermore, quantitative image analysis techniques have been increasingly used throughout the years for the assessment of aggregates and filamentous bacteria properties. These procedures are able to provide an ever growing amount of data for wastewater treatment processes in which chemometric techniques can be a valuable tool. However, the determination of microbial communities’ properties remains a current challenge in spite of the great diversity of microscopy techniques applied. In this review, activated sludge characterization is discussed highlighting the aggregates structure and filamentous bacteria determination by image analysis on bright-field, phase-contrast, and fluorescence microscopy. An in-depth analysis is performed to summarize the many new findings that have been obtained, and future developments for these biological processes are further discussed.

Quantitative morphologic evaluation of magnetic resonance imaging during and after treatment of childhood leukemia

Energy Technology Data Exchange (ETDEWEB)

Reddick, Wilburn E.; Glass, John O. [St. Jude Children' s Research Hospital, Division of Translational Imaging Research (MS 210), Department of Radiological Sciences, Memphis, TN (United States); Laningham, Fred H. [St. Jude Children' s Research Hospital, Division of Diagnostic Imaging, Memphis, TN (United States); Pui, Ching-Hon [St. Jude Children' s Research Hospital, Department of Oncology, Memphis, TN (United States)

2007-11-15

Medical advances over the last several decades, including CNS prophylaxis, have greatly increased survival in children with leukemia. As survival rates have increased, clinicians and scientists have been afforded the opportunity to further develop treatments to improve the quality of life of survivors by minimizing the long-term adverse effects. When evaluating the effect of antileukemia therapy on the developing brain, magnetic resonance (MR) imaging has been the preferred modality because it quantifies morphologic changes objectively and noninvasively. Computer-aided detection of changes on neuroimages enables us to objectively differentiate leukoencephalopathy from normal maturation of the developing brain. Quantitative tissue segmentation algorithms and relaxometry measures have been used to determine the prevalence, extent, and intensity of white matter changes that occur during therapy. More recently, diffusion tensor imaging has been used to quantify microstructural changes in the integrity of the white matter fiber tracts. MR perfusion imaging can be used to noninvasively monitor vascular changes during therapy. Changes in quantitative MR measures have been associated, to some degree, with changes in neurocognitive function during and after treatment. In this review, we present recent advances in quantitative evaluation of MR imaging and discuss how these methods hold the promise to further elucidate the pathophysiologic effects of treatment for childhood leukemia. (orig.)

Quantitative morphologic evaluation of magnetic resonance imaging during and after treatment of childhood leukemia

International Nuclear Information System (INIS)

Reddick, Wilburn E.; Glass, John O.; Laningham, Fred H.; Pui, Ching-Hon

2007-01-01

Medical advances over the last several decades, including CNS prophylaxis, have greatly increased survival in children with leukemia. As survival rates have increased, clinicians and scientists have been afforded the opportunity to further develop treatments to improve the quality of life of survivors by minimizing the long-term adverse effects. When evaluating the effect of antileukemia therapy on the developing brain, magnetic resonance (MR) imaging has been the preferred modality because it quantifies morphologic changes objectively and noninvasively. Computer-aided detection of changes on neuroimages enables us to objectively differentiate leukoencephalopathy from normal maturation of the developing brain. Quantitative tissue segmentation algorithms and relaxometry measures have been used to determine the prevalence, extent, and intensity of white matter changes that occur during therapy. More recently, diffusion tensor imaging has been used to quantify microstructural changes in the integrity of the white matter fiber tracts. MR perfusion imaging can be used to noninvasively monitor vascular changes during therapy. Changes in quantitative MR measures have been associated, to some degree, with changes in neurocognitive function during and after treatment. In this review, we present recent advances in quantitative evaluation of MR imaging and discuss how these methods hold the promise to further elucidate the pathophysiologic effects of treatment for childhood leukemia. (orig.)

Development of Scanning-Imaging X-Ray Microscope for Quantitative Three-Dimensional Phase Contrast Microimaging

International Nuclear Information System (INIS)

Takeuchi, Akihisa; Suzuki, Yoshio; Uesugi, Kentaro

2013-01-01

A novel x-ray microscope system has been developed for the purpose of quantitative and sensitive three-dimensional (3D) phase-contrast x-ray microimaging. The optical system is a hybrid that consists of a scanning microscope optics with a one-dimensional (1D) focusing (line-focusing) device and an imaging microscope optics with a 1D objective. These two optics are orthogonally arranged regarding their common optical axis. Each is used for forming each dimension of two-dimensional (2D) image. The same data acquisition process as that of the scanning microscope system enables quantitative and sensitive x-ray imaging such as phase contrast and absorption contrast. Because a 2D image is measured with only 1D translation scan, much shorter measurement time than that of conventional scanning optics has been realized. By combining a computed tomography (CT) technique, some 3D CT application examples are demonstrated

Impact of deep learning on the normalization of reconstruction kernel effects in imaging biomarker quantification: a pilot study in CT emphysema

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Jin, Hyeongmin; Heo, Changyong; Kim, Jong Hyo

2018-02-01

Differing reconstruction kernels are known to strongly affect the variability of imaging biomarkers and thus remain as a barrier in translating the computer aided quantification techniques into clinical practice. This study presents a deep learning application to CT kernel conversion which converts a CT image of sharp kernel to that of standard kernel and evaluates its impact on variability reduction of a pulmonary imaging biomarker, the emphysema index (EI). Forty cases of low-dose chest CT exams obtained with 120kVp, 40mAs, 1mm thickness, of 2 reconstruction kernels (B30f, B50f) were selected from the low dose lung cancer screening database of our institution. A Fully convolutional network was implemented with Keras deep learning library. The model consisted of symmetric layers to capture the context and fine structure characteristics of CT images from the standard and sharp reconstruction kernels. Pairs of the full-resolution CT data set were fed to input and output nodes to train the convolutional network to learn the appropriate filter kernels for converting the CT images of sharp kernel to standard kernel with a criterion of measuring the mean squared error between the input and target images. EIs (RA950 and Perc15) were measured with a software package (ImagePrism Pulmo, Seoul, South Korea) and compared for the data sets of B50f, B30f, and the converted B50f. The effect of kernel conversion was evaluated with the mean and standard deviation of pair-wise differences in EI. The population mean of RA950 was 27.65 +/- 7.28% for B50f data set, 10.82 +/- 6.71% for the B30f data set, and 8.87 +/- 6.20% for the converted B50f data set. The mean of pair-wise absolute differences in RA950 between B30f and B50f is reduced from 16.83% to 1.95% using kernel conversion. Our study demonstrates the feasibility of applying the deep learning technique for CT kernel conversion and reducing the kernel-induced variability of EI quantification. The deep learning model has a

Quantitative comparison of PZT and CMUT probes for photoacoustic imaging: Experimental validation.

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Vallet, Maëva; Varray, François; Boutet, Jérôme; Dinten, Jean-Marc; Caliano, Giosuè; Savoia, Alessandro Stuart; Vray, Didier

2017-12-01

Photoacoustic (PA) signals are short ultrasound (US) pulses typically characterized by a single-cycle shape, often referred to as N-shape. The spectral content of such wideband signals ranges from a few hundred kilohertz to several tens of megahertz. Typical reception frequency responses of classical piezoelectric US imaging transducers, based on PZT technology, are not sufficiently broadband to fully preserve the entire information contained in PA signals, which are then filtered, thus limiting PA imaging performance. Capacitive micromachined ultrasonic transducers (CMUT) are rapidly emerging as a valid alternative to conventional PZT transducers in several medical ultrasound imaging applications. As compared to PZT transducers, CMUTs exhibit both higher sensitivity and significantly broader frequency response in reception, making their use attractive in PA imaging applications. This paper explores the advantages of the CMUT larger bandwidth in PA imaging by carrying out an experimental comparative study using various CMUT and PZT probes from different research laboratories and manufacturers. PA acquisitions are performed on a suture wire and on several home-made bimodal phantoms with both PZT and CMUT probes. Three criteria, based on the evaluation of pure receive impulse response, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) respectively, have been used for a quantitative comparison of imaging results. The measured fractional bandwidths of the CMUT arrays are larger compared to PZT probes. Moreover, both SNR and CNR are enhanced by at least 6 dB with CMUT technology. This work highlights the potential of CMUT technology for PA imaging through qualitative and quantitative parameters.

Nuclear medicine and image research: instrumentation and quantitative methods of evaluation. Comprehensive 3-year progress report, January 15, 1983-January 14, 1986

International Nuclear Information System (INIS)

Beck, R.N.; Cooper, M.D.

1985-09-01

This program of research addresses problems involving the basic science and technology of radioactive tracer methods as they relate to nuclear medicine and imaging. The broad goal is to develop new instruments and methods for image formation, processing, quantitation, and display, so as to maximize the diagnostic information per unit of absorbed radiation dose to the patient. Project I addresses problems with the quantitative imaging a single-photon emitters; Project II addresses similar problems associated with the quantitative imaging of positron emitters; Project III addresses methodological problems associated with the quantitative evaluation of the efficacy of diagnostic imaging procedures

Magnetic Resonance Fingerprinting - a promising new approach to obtain standardized imaging biomarkers from MRI.

Science.gov (United States)

2015-04-01

Current routine MRI examinations rely on the acquisition of qualitative images that have a contrast "weighted" for a mixture of (magnetic) tissue properties. Recently, a novel approach was introduced, namely MR Fingerprinting (MRF) with a completely different approach to data acquisition, post-processing and visualization. Instead of using a repeated, serial acquisition of data for the characterization of individual parameters of interest, MRF uses a pseudo randomized acquisition that causes the signals from different tissues to have a unique signal evolution or 'fingerprint' that is simultaneously a function of the multiple material properties under investigation. The processing after acquisition involves a pattern recognition algorithm to match the fingerprints to a predefined dictionary of predicted signal evolutions. These can then be translated into quantitative maps of the magnetic parameters of interest. MR Fingerprinting (MRF) is a technique that could theoretically be applied to most traditional qualitative MRI methods and replaces them with acquisition of truly quantitative tissue measures. MRF is, thereby, expected to be much more accurate and reproducible than traditional MRI and should improve multi-center studies and significantly reduce reader bias when diagnostic imaging is performed. Key Points • MR fingerprinting (MRF) is a new approach to data acquisition, post-processing and visualization.• MRF provides highly accurate quantitative maps of T1, T2, proton density, diffusion.• MRF may offer multiparametric imaging with high reproducibility, and high potential for multicenter/ multivendor studies.

Imaging biomarkers to predict response to anti-HER2 (ErbB2) therapy in preclinical models of breast cancer

Science.gov (United States)

Shah, Chirayu; Miller, Todd W.; Wyatt, Shelby K.; McKinley, Eliot T.; Olivares, Maria Graciela; Sanchez, Violeta; Nolting, Donald D.; Buck, Jason R.; Zhao, Ping; Ansari, M. Sib; Baldwin, Ronald M.; Gore, John C.; Schiff, Rachel; Arteaga, Carlos L.; Manning, H. Charles

2010-01-01

Purpose To evaluate non-invasive imaging methods as predictive biomarkers of response to trastuzumab in mouse models of HER2-overexpressing breast cancer. The correlation between tumor regression and molecular imaging of apoptosis, glucose metabolism, and cellular proliferation was evaluated longitudinally in responding and non-responding tumor-bearing cohorts. Experimental Design Mammary tumors from MMTV/HER2 transgenic female mice were transplanted into syngeneic female mice. BT474 human breast carcinoma cell line xenografts were grown in athymic nude mice. Tumor cell apoptosis (NIR700-Annexin-V accumulation), glucose metabolism ([18F]FDG-PET), and proliferation ([18F]FLT-PET) were evaluated throughout a bi-weekly trastuzumab regimen. Imaging metrics were validated by direct measurement of tumor size and immunohistochemical (IHC) analysis of cleaved caspase-3, phosphorylated AKT (p-AKT) and Ki67. Results NIR700-Annexin-V accumulated significantly in trastuzumab-treated MMTV/HER2 and BT474 tumors that ultimately regressed, but not in non-responding or vehicle-treated tumors. Uptake of [18F]FDG was not affected by trastuzumab treatment in MMTV/HER2 or BT474 tumors. [18F]FLT PET imaging predicted trastuzumab response in BT474 tumors but not in MMTV/HER2 tumors, which exhibited modest uptake of [18F]FLT. Close agreement was observed between imaging metrics and IHC analysis. Conclusions Molecular imaging of apoptosis accurately predicts trastuzumab-induced regression of HER2(+) tumors and may warrant clinical exploration to predict early response to neoadjuvant trastuzumab. Trastuzumab does not appear to alter glucose metabolism substantially enough to afford [18F]FDG-PET significant predictive value in this setting. Although promising in one preclinical model, further studies are required to determine the overall value of [18F]FLT-PET as a biomarker of response to trastuzumab in HER2+ breast cancer. PMID:19584166

Quantitative phase imaging of living cells with a swept laser source

Science.gov (United States)

Chen, Shichao; Zhu, Yizheng

2016-03-01

Digital holographic phase microscopy is a well-established quantitative phase imaging technique. However, interference artifacts from inside the system, typically induced by elements whose optical thickness are within the source coherence length, limit the imaging quality as well as sensitivity. In this paper, a swept laser source based technique is presented. Spectra acquired at a number of wavelengths, after Fourier Transform, can be used to identify the sources of the interference artifacts. With proper tuning of the optical pathlength difference between sample and reference arms, it is possible to avoid these artifacts and achieve sensitivity below 0.3nm. Performance of the proposed technique is examined in live cell imaging.

MR Imaging Biomarkers to Monitor Early Response to Hypoxia-Activated Prodrug TH-302 in Pancreatic Cancer Xenografts.

Directory of Open Access Journals (Sweden)

Xiaomeng Zhang

Full Text Available TH-302 is a hypoxia-activated prodrug known to activate selectively under the hypoxic conditions commonly found in solid tumors. It is currently being evaluated in clinical trials, including two trials in Pancreatic Ductal Adenocarcinomas (PDAC. The current study was undertaken to evaluate imaging biomarkers for prediction and response monitoring of TH-302 efficacy in xenograft models of PDAC. Dynamic contrast-enhanced (DCE and diffusion weighted (DW magnetic resonance imaging (MRI were used to monitor acute effects on tumor vasculature and cellularity, respectively. Three human PDAC xenografts with known differential responses to TH-302 were imaged prior to, and at 24 h and 48 hours following a single dose of TH-302 or vehicle to determine if imaging changes presaged changes in tumor volumes. DW-MRI was performed at five b-values to generate apparent diffusion coefficient of water (ADC maps. For DCE-MRI, a standard clinically available contrast reagent, Gd-DTPA, was used to determine blood flow into the tumor region of interest. TH-302 induced a dramatic decrease in the DCE transfer constant (Ktrans within 48 hours after treatment in the sensitive tumors, Hs766t and Mia PaCa-2, whereas TH-302 had no effect on the perfusion behavior of resistant SU.86.86 tumors. Tumor cellularity, estimated from ADC, was significantly increased 24 and 48 hours after treatment in Hs766t, but was not observed in the Mia PaCa-2 and SU.86.86 groups. Notably, growth inhibition of Hs766t was observed immediately (day 3 following initiation of treatment, but was not observed in MiaPaCa-2 tumors until 8 days after initiation of treatment. Based on these preclinical findings, DCE-MRI measures of vascular perfusion dynamics and ADC measures of cell density are suggested as potential TH-302 response biomarkers in clinical trials.

MR Imaging Biomarkers to Monitor Early Response to Hypoxia-Activated Prodrug TH-302 in Pancreatic Cancer Xenografts.

Science.gov (United States)

Zhang, Xiaomeng; Wojtkowiak, Jonathan W; Martinez, Gary V; Cornnell, Heather H; Hart, Charles P; Baker, Amanda F; Gillies, Robert

2016-01-01

TH-302 is a hypoxia-activated prodrug known to activate selectively under the hypoxic conditions commonly found in solid tumors. It is currently being evaluated in clinical trials, including two trials in Pancreatic Ductal Adenocarcinomas (PDAC). The current study was undertaken to evaluate imaging biomarkers for prediction and response monitoring of TH-302 efficacy in xenograft models of PDAC. Dynamic contrast-enhanced (DCE) and diffusion weighted (DW) magnetic resonance imaging (MRI) were used to monitor acute effects on tumor vasculature and cellularity, respectively. Three human PDAC xenografts with known differential responses to TH-302 were imaged prior to, and at 24 h and 48 hours following a single dose of TH-302 or vehicle to determine if imaging changes presaged changes in tumor volumes. DW-MRI was performed at five b-values to generate apparent diffusion coefficient of water (ADC) maps. For DCE-MRI, a standard clinically available contrast reagent, Gd-DTPA, was used to determine blood flow into the tumor region of interest. TH-302 induced a dramatic decrease in the DCE transfer constant (Ktrans) within 48 hours after treatment in the sensitive tumors, Hs766t and Mia PaCa-2, whereas TH-302 had no effect on the perfusion behavior of resistant SU.86.86 tumors. Tumor cellularity, estimated from ADC, was significantly increased 24 and 48 hours after treatment in Hs766t, but was not observed in the Mia PaCa-2 and SU.86.86 groups. Notably, growth inhibition of Hs766t was observed immediately (day 3) following initiation of treatment, but was not observed in MiaPaCa-2 tumors until 8 days after initiation of treatment. Based on these preclinical findings, DCE-MRI measures of vascular perfusion dynamics and ADC measures of cell density are suggested as potential TH-302 response biomarkers in clinical trials.

Hyperspectral and differential CARS microscopy for quantitative chemical imaging in human adipocytes

Science.gov (United States)

Di Napoli, Claudia; Pope, Iestyn; Masia, Francesco; Watson, Peter; Langbein, Wolfgang; Borri, Paola

2014-01-01

In this work, we demonstrate the applicability of coherent anti-Stokes Raman scattering (CARS) micro-spectroscopy for quantitative chemical imaging of saturated and unsaturated lipids in human stem-cell derived adipocytes. We compare dual-frequency/differential CARS (D-CARS), which enables rapid imaging and simple data analysis, with broadband hyperspectral CARS microscopy analyzed using an unsupervised phase-retrieval and factorization method recently developed by us for quantitative chemical image analysis. Measurements were taken in the vibrational fingerprint region (1200–2000/cm) and in the CH stretch region (2600–3300/cm) using a home-built CARS set-up which enables hyperspectral imaging with 10/cm resolution via spectral focussing from a single broadband 5 fs Ti:Sa laser source. Through a ratiometric analysis, both D-CARS and phase-retrieved hyperspectral CARS determine the concentration of unsaturated lipids with comparable accuracy in the fingerprint region, while in the CH stretch region D-CARS provides only a qualitative contrast owing to its non-linear behavior. When analyzing hyperspectral CARS images using the blind factorization into susceptibilities and concentrations of chemical components recently demonstrated by us, we are able to determine vol:vol concentrations of different lipid components and spatially resolve inhomogeneities in lipid composition with superior accuracy compared to state-of-the art ratiometric methods. PMID:24877002

Local and Systemic Inflammatory Biomarkers of Diabetic Retinopathy: An Integrative Approach.

Science.gov (United States)

Vujosevic, Stela; Simó, Rafael

2017-05-01

To review the usefulness of local and systemic inflammatory biomarkers of diabetic retinopathy (DR) to implement a more personalized treatment. An integrated research (from ophthalmologist and diabetologist point of view) of most significant literature on serum, vitreous, and aqueous humor (AH) biochemical biomarkers related to inflammation at early and advanced stages of DR (including diabetic macular edema [DME] and proliferative DR) was performed. Moreover, novel imaging retinal biomarkers of local "inflammatory condition" were described. Multiple inflammatory cytokines and chemokines are increased in DR in both serum as well as in the eye (vitreous and AH). Nevertheless, local rather than systemic production of proinflammatory cytokines seems more relevant in the pathogenesis of both DR and DME. In the eye, retinal glia cells (macroglia and microglia) together with RPE are major sources of proinflammatory and angiogenic modulators. Retinal imaging allows for noninvasive clinical evaluation of retinal inflammatory response induced by diabetes mellitus. Proinflammatory cytokines/chemokines play an essential role in the pathogenesis of DR. Therefore, circulating biomarkers and retinal imaging aimed at assessing inflammation have emerged as useful tools for monitoring the onset and progression of DR. In addition, "liquid biopsy" of AH seems a good option in patients with advanced stages of DR requiring intravitreous injections. This strategy may permit us to implement a more personalized treatment with better visual function outcome. Further evaluation and validation of circulating and local biomarkers, as well as multimodal imaging is needed to gain new insights into this issue.

Activation autoradiography: imaging and quantitative determination of endogenous and exogenous oxygen in the rat brain

International Nuclear Information System (INIS)

Kawashima, K.; Iwata, R.; Kogure, K.; Ohtomo, H.; Orihara, H.; Ido, T.

1987-01-01

Endogenous and exogenous oxygen in the rat brain were quantitatively determined using an autoradiographic technique. The oxygen images of frozen and dried rat brain sections were obtained as 18 F images by using the 16 O ( 3 He,p) 18 F reaction for endogenous 16 O images and the 18 O(p,n) 18 F reaction for endogenous and exogenous 18 O images. These autoradiograms demonstrated the different distribution of oxygen between gray and white matter. These images also allowed differentiation of the individual structures of hippocampal formation, owing to the differing water content of the various structures. Local oxygen contents were quantitatively determined from autoradiograms of brain sections and standard sections with known oxygen contents. The estimated values were 75.6 +/- 4.6 wt% in gray matter and 72.2 +/- 4.0 wt% in white matter. The systematic error in the present method was estimated to be 4.9%

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

Science.gov (United States)

Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

2015-08-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as 1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

Quantitative live-cell imaging of human immunodeficiency virus (HIV-1) assembly.

Science.gov (United States)

Baumgärtel, Viola; Müller, Barbara; Lamb, Don C

2012-05-01

Advances in fluorescence methodologies make it possible to investigate biological systems in unprecedented detail. Over the last few years, quantitative live-cell imaging has increasingly been used to study the dynamic interactions of viruses with cells and is expected to become even more indispensable in the future. Here, we describe different fluorescence labeling strategies that have been used to label HIV-1 for live cell imaging and the fluorescence based methods used to visualize individual aspects of virus-cell interactions. This review presents an overview of experimental methods and recent experiments that have employed quantitative microscopy in order to elucidate the dynamics of late stages in the HIV-1 replication cycle. This includes cytosolic interactions of the main structural protein, Gag, with itself and the viral RNA genome, the recruitment of Gag and RNA to the plasma membrane, virion assembly at the membrane and the recruitment of cellular proteins involved in HIV-1 release to the nascent budding site.

Quantitative vs. subjective portal verification using digital portal images.

Science.gov (United States)

Bissett, R; Leszczynski, K; Loose, S; Boyko, S; Dunscombe, P

1996-01-15

Off-line, computer-aided prescription (simulator) and treatment (portal) image registration using chamfer matching has been implemented on PC based viewing station. The purposes of this study were (a) to evaluate the performance of interactive anatomy and field edge extraction and subsequent registration, and (b) to compare observer's perceptions of field accuracy with measured discrepancies following anatomical registration. Prescription-treatment image pairs for 48 different patients were examined in this study. Digital prescription images were produced with the aid of a television camera and a digital frame grabber, while the treatment images were obtained directly from an on-line portal imaging system. To facilitate perception of low contrast anatomical detail, on-line portal images were enhanced with selective adaptive histogram equalization prior to extraction of anatomical edges. Following interactive extraction of anatomical and field border information by an experienced observer, the identified anatomy was registered using chamfer matching. The degree of conformity between the prescription and treatment fields was quantified using several parameters, which included relative prescription field coverage and overcoverage, as well as the translational and rotational displacements as measured by chamfer matching applied to the boundaries of the two fields. These quantitative measures were compared with subjective evaluations made by four radiation oncologists. All the images in this series that included a range of the most commonly seen treatment sites were registered and the conformity parameters were found. The mean treatment/prescription field coverage and overcoverage were approximately 95 and 7%, respectively before registration. The mean translational displacement in the transverse and cranio-caudal directions were 2.9 and 3.4 mm, respectively. The mean rotational displacement was approximately 2 degrees. For all four oncologists, the portals classified

On the Potential Role of MRI Biomarkers of COPD to Guide Bronchoscopic Lung Volume Reduction.

Science.gov (United States)

Adams, Colin J; Capaldi, Dante P I; Di Cesare, Robert; McCormack, David G; Parraga, Grace

2018-02-01

In patients with severe emphysema and poor quality of life, bronchoscopic lung volume reduction (BLVR) may be considered and guided based on lobar emphysema severity. In particular, x-ray computed tomography (CT) emphysema measurements are used to identify the most diseased and the second-most diseased lobes as BLVR targets. Inhaled gas magnetic resonance imaging (MRI) also provides chronic obstructive pulmonary disease (COPD) biomarkers of lobar emphysema and ventilation abnormalities. Our objective was to retrospectively evaluate CT and MRI biomarkers of lobar emphysema and ventilation in patients with COPD eligible for BLVR. We hypothesized that MRI would provide complementary biomarkers of emphysema and ventilation that help determine the most appropriate lung lobar targets for BLVR in patients with COPD. We retrospectively evaluated 22 BLVR-eligible patients from the Thoracic Imaging Network of Canada cohort (diffusing capacity of the lung for carbon monoxide = 37 ± 12% predicted , forced expiratory volume in 1 second = 34 ± 7% predicted , total lung capacity = 131 ± 17% predicted , and residual volume = 216 ± 36% predicted ). Lobar CT emphysema, measured using a relative area of concept retrospective analysis, quantitative MRI ventilation and CT emphysema measurements provided different BLVR targets in over 30% of the patients. The presence of large MRI ventilation defects in lobes next to CT-targeted lobes might also change the decision to proceed or to guide BLVR to a different lobar target. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Visualization and quantitative analysis of the CSF pulsatile flow with cine MR phase imaging

International Nuclear Information System (INIS)

Katayama, Shinji; Itoh, Takahiko; Kinugasa, Kazushi; Asari, Shoji; Nishimoto, Akira; Tsuchida, Shohei; Ono, Atsushi; Ikezaki, Yoshikazu; Yoshitome, Eiji.

1991-01-01

The visualization and the quantitative analysis of the CSF pulsatile flow were performed on ten healthy volunteers with cine MR phase imaging, a combination of the phase-contrast technique and the cardiac-gating technique. The velocities appropriate for the visualization and the quantitative analysis of the CSF pulsatile flow were from 6.0 cm/sec to 15.0 cm/sec. The applicability of this method for the quantitative analysis was proven with a steady-flow phantom. Phase images clearly demonstrated a to-and-fro motion of the CSF flow in the anterior subarachnoid space and in the posterior subarachnoid space. The flow pattern of CSF on healthy volunteers depends on the cardiac cycle. In the anterior subarachnoid space, the cephalic CSF flow continued until a 70-msec delay after the R-wave of the ECG and then reversed to caudal. At 130-190 msec, the caudal CSF flow reached its maximum velocity; thereafter it reversed again to cephalic. The same turn appeared following the phase, but then the amplitude decreased. The cephalic peaked at 370-430 msec, while the caudal peaked at 490-550 msec. The flow pattern of the CSF flow in the posterior subarachnoid space was almost identical to that in the anterior subarachnoid space. Cine MR phase imaging is thus useful for the visualization and the quantitative analysis of the CSF pulsative flow. (author)

Heterogeneity as Biomarker in Tumour Imaging (abstract only)

NARCIS (Netherlands)

Alić, L.; Veenland, J.F.

2013-01-01

PURPOSE: Tumour heterogeneity could be a valuable biomarker for differentiation, grading, response monitoring and outcome prediction. Many quantification techniques have been described, however in clinical practice these methods are scarcely used. The aim of this study is to evaluate the performance

An approach for quantitative image quality analysis for CT

Science.gov (United States)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

Models of Hepatocellular Carcinoma and Biomarker Strategy

Energy Technology Data Exchange (ETDEWEB)

Bagi, Cedo M., E-mail: cedo.bagi@pfizer.com; Andresen, Catharine J. [Global Science & Technology, PGRD, Pfizer Inc, Groton, CT 06340 (United States)

2010-07-07

The overwhelming need to improve preclinical models in oncology has stimulated research efforts to refine and validate robust orthotopic models that closely mimic the disease population and therefore have the potential to better predict clinical outcome with novel therapies. Sophisticated technologies including bioluminescence, contrast enhanced ultrasound imaging, positron emission tomography, computed tomography and magnetic resonance imaging have been added to existing serum- and histology-based biomarkers to assist with patient selection and the design of clinical trials. The rationale for the use of human hepatocellular carcinoma (HCC) cell lines, implementation of xenograft and orthotopic animal models and utilization of available biomarkers have been discussed, providing guidelines to facilitate preclinical research for the development of treatments for HCC patients.

A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods.

Science.gov (United States)

Jha, Abhinav K; Caffo, Brian; Frey, Eric C

2016-04-07

The objective optimization and evaluation of nuclear-medicine quantitative imaging methods using patient data is highly desirable but often hindered by the lack of a gold standard. Previously, a regression-without-truth (RWT) approach has been proposed for evaluating quantitative imaging methods in the absence of a gold standard, but this approach implicitly assumes that bounds on the distribution of true values are known. Several quantitative imaging methods in nuclear-medicine imaging measure parameters where these bounds are not known, such as the activity concentration in an organ or the volume of a tumor. We extended upon the RWT approach to develop a no-gold-standard (NGS) technique for objectively evaluating such quantitative nuclear-medicine imaging methods with patient data in the absence of any ground truth. Using the parameters estimated with the NGS technique, a figure of merit, the noise-to-slope ratio (NSR), can be computed, which can rank the methods on the basis of precision. An issue with NGS evaluation techniques is the requirement of a large number of patient studies. To reduce this requirement, the proposed method explored the use of multiple quantitative measurements from the same patient, such as the activity concentration values from different organs in the same patient. The proposed technique was evaluated using rigorous numerical experiments and using data from realistic simulation studies. The numerical experiments demonstrated that the NSR was estimated accurately using the proposed NGS technique when the bounds on the distribution of true values were not precisely known, thus serving as a very reliable metric for ranking the methods on the basis of precision. In the realistic simulation study, the NGS technique was used to rank reconstruction methods for quantitative single-photon emission computed tomography (SPECT) based on their performance on the task of estimating the mean activity concentration within a known volume of interest

A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods

International Nuclear Information System (INIS)

Jha, Abhinav K; Frey, Eric C; Caffo, Brian

2016-01-01

The objective optimization and evaluation of nuclear-medicine quantitative imaging methods using patient data is highly desirable but often hindered by the lack of a gold standard. Previously, a regression-without-truth (RWT) approach has been proposed for evaluating quantitative imaging methods in the absence of a gold standard, but this approach implicitly assumes that bounds on the distribution of true values are known. Several quantitative imaging methods in nuclear-medicine imaging measure parameters where these bounds are not known, such as the activity concentration in an organ or the volume of a tumor. We extended upon the RWT approach to develop a no-gold-standard (NGS) technique for objectively evaluating such quantitative nuclear-medicine imaging methods with patient data in the absence of any ground truth. Using the parameters estimated with the NGS technique, a figure of merit, the noise-to-slope ratio (NSR), can be computed, which can rank the methods on the basis of precision. An issue with NGS evaluation techniques is the requirement of a large number of patient studies. To reduce this requirement, the proposed method explored the use of multiple quantitative measurements from the same patient, such as the activity concentration values from different organs in the same patient. The proposed technique was evaluated using rigorous numerical experiments and using data from realistic simulation studies. The numerical experiments demonstrated that the NSR was estimated accurately using the proposed NGS technique when the bounds on the distribution of true values were not precisely known, thus serving as a very reliable metric for ranking the methods on the basis of precision. In the realistic simulation study, the NGS technique was used to rank reconstruction methods for quantitative single-photon emission computed tomography (SPECT) based on their performance on the task of estimating the mean activity concentration within a known volume of interest

Quantitative evaluation of dual-energy digital mammography for calcification imaging

International Nuclear Information System (INIS)

Kappadath, S Cheenu; Shaw, Chris C

2004-01-01

Dual-energy digital mammography (DEDM), where separate low- and high-energy images are acquired and synthesized to cancel the tissue structures, may improve the ability to detect and visualize microcalcifications. Under ideal imaging conditions, when the mammography image data are free of scatter and other biases, DEDM could be used to determine the thicknesses of the imaged calcifications. We present quantitative evaluation of a DEDM technique for calcification imaging. The phantoms used in the evaluation were constructed by placing aluminium strips of known thicknesses (to simulate calcifications) across breast-tissue-equivalent materials of different glandular-tissue compositions. The images were acquired under narrow-beam geometry and high exposures to suppress the detrimental effects of scatter and random noise. The measured aluminium thicknesses were found to be approximately linear with the true aluminium thicknesses and independent of the underlying glandular-tissue composition. However, the dual-energy images underestimated the true aluminium thickness due to the presence of scatter from adjacent regions. Regions in the DEDM image that contained no aluminium yielded very low aluminium thicknesses (<0.07 mm). The aluminium contrast-to-noise ratio in the dual-energy images increased with the aluminium thickness and decreased with the glandular-tissue composition. The changes to the aluminium contrast-to-noise ratio and the contrast of the tissue structures between the low-energy and DEDM images are also presented

Molecular and phenotypic biomarkers of aging [version 1; referees: 3 approved

Directory of Open Access Journals (Sweden)

Xian Xia

2017-06-01

Full Text Available Individuals of the same age may not age at the same rate. Quantitative biomarkers of aging are valuable tools to measure physiological age, assess the extent of ‘healthy aging’, and potentially predict health span and life span for an individual. Given the complex nature of the aging process, the biomarkers of aging are multilayered and multifaceted. Here, we review the phenotypic and molecular biomarkers of aging. Identifying and using biomarkers of aging to improve human health, prevent age-associated diseases, and extend healthy life span are now facilitated by the fast-growing capacity of multilevel cross-sectional and longitudinal data acquisition, storage, and analysis, particularly for data related to general human populations. Combined with artificial intelligence and machine learning techniques, reliable panels of biomarkers of aging will have tremendous potential to improve human health in aging societies.

Biomarkers in Prodromal Parkinson Disease: a Qualitative Review.

Science.gov (United States)

Cooper, Christine A; Chahine, Lama M

2016-11-01

Over the past several years, the concept of prodromal Parkinson disease (PD) has been increasingly recognized. This term refers to individuals who do not fulfill motor diagnostic criteria for PD, but who have clinical, genetic, or biomarker characteristics suggesting risk of developing PD in the future. Clinical diagnosis of prodromal PD has low specificity, prompting the need for objective biomarkers with higher specificity. In this qualitative review, we discuss objectively defined putative biomarkers for PD and prodromal PD. We searched Pubmed and Embase for articles pertaining to objective biomarkers for PD and their application in prodromal cohorts. Articles were selected based on relevance and methodology. Objective biomarkers of demonstrated utility in prodromal PD include ligand-based imaging and transcranial sonography. Development of serum, cerebrospinal fluid, and tissue-based biomarkers is underway, but their application in prodromal PD has yet to meaningfully occur. Combining objective biomarkers with clinical or genetic prodromal features increases the sensitivity and specificity for identifying prodromal PD. Several objective biomarkers for prodromal PD show promise but require further study, including their application to and validation in prodromal cohorts followed longitudinally. Accurate identification of prodromal PD will likely require a multimodal approach. (JINS, 2016, 22, 956-967).

An update on novel quantitative techniques in the context of evolving whole-body PET imaging

DEFF Research Database (Denmark)

Houshmand, Sina; Salavati, Ali; Hess, Søren

2015-01-01

Since its foundation PET has established itself as one of the standard imaging modalities enabling the quantitative assessment of molecular targets in vivo. In the past two decades, quantitative PET has become a necessity in clinical oncology. Despite introduction of various measures for quantifi...

Quantitative Analysis of Rat Dorsal Root Ganglion Neurons Cultured on Microelectrode Arrays Based on Fluorescence Microscopy Image Processing.

Science.gov (United States)

Mari, João Fernando; Saito, José Hiroki; Neves, Amanda Ferreira; Lotufo, Celina Monteiro da Cruz; Destro-Filho, João-Batista; Nicoletti, Maria do Carmo

2015-12-01

Microelectrode Arrays (MEA) are devices for long term electrophysiological recording of extracellular spontaneous or evocated activities on in vitro neuron culture. This work proposes and develops a framework for quantitative and morphological analysis of neuron cultures on MEAs, by processing their corresponding images, acquired by fluorescence microscopy. The neurons are segmented from the fluorescence channel images using a combination of segmentation by thresholding, watershed transform, and object classification. The positioning of microelectrodes is obtained from the transmitted light channel images using the circular Hough transform. The proposed method was applied to images of dissociated culture of rat dorsal root ganglion (DRG) neuronal cells. The morphological and topological quantitative analysis carried out produced information regarding the state of culture, such as population count, neuron-to-neuron and neuron-to-microelectrode distances, soma morphologies, neuron sizes, neuron and microelectrode spatial distributions. Most of the analysis of microscopy images taken from neuronal cultures on MEA only consider simple qualitative analysis. Also, the proposed framework aims to standardize the image processing and to compute quantitative useful measures for integrated image-signal studies and further computational simulations. As results show, the implemented microelectrode identification method is robust and so are the implemented neuron segmentation and classification one (with a correct segmentation rate up to 84%). The quantitative information retrieved by the method is highly relevant to assist the integrated signal-image study of recorded electrophysiological signals as well as the physical aspects of the neuron culture on MEA. Although the experiments deal with DRG cell images, cortical and hippocampal cell images could also be processed with small adjustments in the image processing parameter estimation.

Serial quantitative MR assessment of optic neuritis in a case of neuromyelitis optica, using gadolinium-'enhanced' STIR imaging

International Nuclear Information System (INIS)

Barkhof, F.; Scheltens, P.; Valk, J.; Waalewijn, C.; Uitdehaag, B.M.J.; Polman, C.H.

1991-01-01

A patient is presented with neuromyelitis optica. MR imaging, using a short inversion time inversion recovery (STIR) technique, clearly depicted the lesion in the left optic nerve. Subsequent serial STIR imaging, with and without Gadolinium-DTPA, allowed quantitative assessment of changes parallel to improved optic nerve function. STIR imaging is a sensitive technique to demonstrate optic nerve lesions, and enables quantitative assessment to be made of the effect of (steroid) medication. (orig.)

Structural and diffusion imaging versus clinical assessment to monitor amyotrophic lateral sclerosis

Directory of Open Access Journals (Sweden)

Arturo Cardenas-Blanco

2016-01-01

Full Text Available Amyotrophic lateral sclerosis is a progressive neurodegenerative disease that affects upper and lower motor neurons. Observational and intervention studies can be tracked using clinical measures such as the revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R but for a complete understanding of disease progression, objective in vivo biomarkers of both central and peripheral motor pathway pathology are highly desirable. The aim of this study was to determine the utility of structural and diffusion imaging as central nervous system biomarkers compared to the standard clinical measure, ALSFRS-R, to track longitudinal evolution using three time-point measurements. N = 34 patients with ALS were scanned and clinically assessed three times at a mean of three month time intervals. The MRI biomarkers were structural T1-weighted volumes for cortical thickness measurement as well as deep grey matter volumetry, voxel-based morphometry and diffusion tensor imaging (DTI. Cortical thickness focused specifically on the precentral gyrus while quantitative DTI biomarkers focused on the corticospinal tracts. The evolution of imaging biomarkers and ALSFRS-R scores over time were analysed using a mixed effects model that accounted for the scanning interval as a fixed effect variable, and, the initial measurements and time from onset as random variables. The mixed effects model showed a significant decrease in the ALSFRS-R score, (p  0.5. In addition, deep grey matter volumetry and voxel-based morphometry also identified no significant changes. Furthermore, the availability of three time points was able to indicate that there was a linear progression in both clinical and fractional anisotropy measures adding to the validity of these results. The results indicate that DTI is clearly a superior imaging marker compared to atrophy for tracking the evolution of the disease and can act as a central nervous biomarker in longitudinal studies. It

TU-CD-BRB-08: Radiomic Analysis of FDG-PET Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated with SBRT

Energy Technology Data Exchange (ETDEWEB)

Cui, Y; Shirato, H [Hokkaido University, Global Institute for Collaborative Research and Educat, Sapporo, Hokkaido (Japan); Song, J; Pollom, E; Chang, D; Koong, A [Stanford University, Palo Alto, CA (United States); Li, R [Hokkaido University, Global Institute for Collaborative Research and Educat, Sapporo, Hokkaido (Japan); Stanford University, Palo Alto, CA (United States)

2015-06-15

Purpose: This study aims to identify novel prognostic imaging biomarkers in locally advanced pancreatic cancer (LAPC) using quantitative, high-throughput image analysis. Methods: 86 patients with LAPC receiving chemotherapy followed by SBRT were retrospectively studied. All patients had a baseline FDG-PET scan prior to SBRT. For each patient, we extracted 435 PET imaging features of five types: statistical, morphological, textural, histogram, and wavelet. These features went through redundancy checks, robustness analysis, as well as a prescreening process based on their concordance indices with respect to the relevant outcomes. We then performed principle component analysis on the remaining features (number ranged from 10 to 16), and fitted a Cox proportional hazard regression model using the first 3 principle components. Kaplan-Meier analysis was used to assess the ability to distinguish high versus low-risk patients separated by median predicted survival. To avoid overfitting, all evaluations were based on leave-one-out cross validation (LOOCV), in which each holdout patient was assigned to a risk group according to the model obtained from a separate training set. Results: For predicting overall survival (OS), the most dominant imaging features were wavelet coefficients. There was a statistically significant difference in OS between patients with predicted high and low-risk based on LOOCV (hazard ratio: 2.26, p<0.001). Similar imaging features were also strongly associated with local progression-free survival (LPFS) (hazard ratio: 1.53, p=0.026) on LOOCV. In comparison, neither SUVmax nor TLG was associated with LPFS (p=0.103, p=0.433) (Table 1). Results for progression-free survival and distant progression-free survival showed similar trends. Conclusion: Radiomic analysis identified novel imaging features that showed improved prognostic value over conventional methods. These features characterize the degree of intra-tumor heterogeneity reflected on FDG

High-resolution morphologic and ultrashort time-to-echo quantitative magnetic resonance imaging of the temporomandibular joint

Energy Technology Data Exchange (ETDEWEB)

Bae, Won C.; Chang, Eric Y.; Biswas, Reni; Statum, Sheronda; Chung, Christine B. [Veterans Administration San Diego Healthcare System, Department of Radiology, San Diego, CA (United States); University of California, San Diego, School of Medicine, Department of Radiology, San Diego, CA (United States); Tafur, Monica; Du, Jiang; Healey, Robert [University of California, San Diego, School of Medicine, Department of Radiology, San Diego, CA (United States); Kwack, Kyu-Sung [Ajou University Medical Center, Department of Radiology, Wonchon-dong, Yeongtong-gu, Gyeonggi-do, Suwon (Korea, Republic of)

2016-03-15

To implement high-resolution morphologic and quantitative magnetic resonance imaging (MRI) of the temporomandibular joint (TMJ) using ultrashort time-to-echo (UTE) techniques in cadavers and volunteers. This study was approved by the institutional review board. TMJs of cadavers and volunteers were imaged on a 3-T MR system. High-resolution morphologic and quantitative sequences using conventional and UTE techniques were performed in cadaveric TMJs. Morphologic and UTE quantitative sequences were performed in asymptomatic and symptomatic volunteers. Morphologic evaluation demonstrated the TMJ structures in open- and closed-mouth position. UTE techniques facilitated the visualization of the disc and fibrocartilage. Quantitative UTE MRI was successfully performed ex vivo and in vivo, reflecting the degree of degeneration. There was a difference in the mean UTE T2* values between asymptomatic and symptomatic volunteers. MRI evaluation of the TMJ using UTE techniques allows characterization of the internal structure and quantification of the MR properties of the disc. Quantitative UTE MRI can be performed in vivo with short scan times. (orig.)

A method for improved clustering and classification of microscopy images using quantitative co-localization coefficients