Sample records for quantitative imaging biomarkers

  1. Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

    PubMed

    Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

    2013-08-01

    A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

  2. Quantitative Imaging Biomarkers of NAFLD

    PubMed Central

    Kinner, Sonja; Reeder, Scott B.

    2016-01-01

    Conventional imaging modalities, including ultrasonography (US), computed tomography (CT), and magnetic resonance (MR), play an important role in the diagnosis and management of patients with nonalcoholic fatty liver disease (NAFLD) by allowing noninvasive diagnosis of hepatic steatosis. However, conventional imaging modalities are limited as biomarkers of NAFLD for various reasons. Multi-parametric quantitative MRI techniques overcome many of the shortcomings of conventional imaging and allow comprehensive and objective evaluation of NAFLD. MRI can provide unconfounded biomarkers of hepatic fat, iron, and fibrosis in a single examination—a virtual biopsy has become a clinical reality. In this article, we will review the utility and limitation of conventional US, CT, and MR imaging for the diagnosis NAFLD. Recent advances in imaging biomarkers of NAFLD are also discussed with an emphasis in multi-parametric quantitative MRI. PMID:26848588

  3. Quantitative imaging test approval and biomarker qualification: interrelated but distinct activities.

    PubMed

    Buckler, Andrew J; Bresolin, Linda; Dunnick, N Reed; Sullivan, Daniel C; Aerts, Hugo J W L; Bendriem, Bernard; Bendtsen, Claus; Boellaard, Ronald; Boone, John M; Cole, Patricia E; Conklin, James J; Dorfman, Gary S; Douglas, Pamela S; Eidsaunet, Willy; Elsinger, Cathy; Frank, Richard A; Gatsonis, Constantine; Giger, Maryellen L; Gupta, Sandeep N; Gustafson, David; Hoekstra, Otto S; Jackson, Edward F; Karam, Lisa; Kelloff, Gary J; Kinahan, Paul E; McLennan, Geoffrey; Miller, Colin G; Mozley, P David; Muller, Keith E; Patt, Rick; Raunig, David; Rosen, Mark; Rupani, Haren; Schwartz, Lawrence H; Siegel, Barry A; Sorensen, A Gregory; Wahl, Richard L; Waterton, John C; Wolf, Walter; Zahlmann, Gudrun; Zimmerman, Brian

    2011-06-01

    Quantitative imaging biomarkers could speed the development of new treatments for unmet medical needs and improve routine clinical care. However, it is not clear how the various regulatory and nonregulatory (eg, reimbursement) processes (often referred to as pathways) relate, nor is it clear which data need to be collected to support these different pathways most efficiently, given the time- and cost-intensive nature of doing so. The purpose of this article is to describe current thinking regarding these pathways emerging from diverse stakeholders interested and active in the definition, validation, and qualification of quantitative imaging biomarkers and to propose processes to facilitate the development and use of quantitative imaging biomarkers. A flexible framework is described that may be adapted for each imaging application, providing mechanisms that can be used to develop, assess, and evaluate relevant biomarkers. From this framework, processes can be mapped that would be applicable to both imaging product development and to quantitative imaging biomarker development aimed at increasing the effectiveness and availability of quantitative imaging. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100800/-/DC1. RSNA, 2011

  4. Metrology Standards for Quantitative Imaging Biomarkers

    PubMed Central

    Obuchowski, Nancy A.; Kessler, Larry G.; Raunig, David L.; Gatsonis, Constantine; Huang, Erich P.; Kondratovich, Marina; McShane, Lisa M.; Reeves, Anthony P.; Barboriak, Daniel P.; Guimaraes, Alexander R.; Wahl, Richard L.

    2015-01-01

    Although investigators in the imaging community have been active in developing and evaluating quantitative imaging biomarkers (QIBs), the development and implementation of QIBs have been hampered by the inconsistent or incorrect use of terminology or methods for technical performance and statistical concepts. Technical performance is an assessment of how a test performs in reference objects or subjects under controlled conditions. In this article, some of the relevant statistical concepts are reviewed, methods that can be used for evaluating and comparing QIBs are described, and some of the technical performance issues related to imaging biomarkers are discussed. More consistent and correct use of terminology and study design principles will improve clinical research, advance regulatory science, and foster better care for patients who undergo imaging studies. © RSNA, 2015 PMID:26267831

  5. Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making.

    PubMed

    Prescott, Jeffrey William

    2013-02-01

    The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

  6. Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

    PubMed

    Raunig, David L; McShane, Lisa M; Pennello, Gene; Gatsonis, Constantine; Carson, Paul L; Voyvodic, James T; Wahl, Richard L; Kurland, Brenda F; Schwarz, Adam J; Gönen, Mithat; Zahlmann, Gudrun; Kondratovich, Marina V; O'Donnell, Kevin; Petrick, Nicholas; Cole, Patricia E; Garra, Brian; Sullivan, Daniel C

    2015-02-01

    Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  7. Quantitative imaging biomarkers: Effect of sample size and bias on confidence interval coverage.

    PubMed

    Obuchowski, Nancy A; Bullen, Jennifer

    2017-01-01

    Introduction Quantitative imaging biomarkers (QIBs) are being increasingly used in medical practice and clinical trials. An essential first step in the adoption of a quantitative imaging biomarker is the characterization of its technical performance, i.e. precision and bias, through one or more performance studies. Then, given the technical performance, a confidence interval for a new patient's true biomarker value can be constructed. Estimating bias and precision can be problematic because rarely are both estimated in the same study, precision studies are usually quite small, and bias cannot be measured when there is no reference standard. Methods A Monte Carlo simulation study was conducted to assess factors affecting nominal coverage of confidence intervals for a new patient's quantitative imaging biomarker measurement and for change in the quantitative imaging biomarker over time. Factors considered include sample size for estimating bias and precision, effect of fixed and non-proportional bias, clustered data, and absence of a reference standard. Results Technical performance studies of a quantitative imaging biomarker should include at least 35 test-retest subjects to estimate precision and 65 cases to estimate bias. Confidence intervals for a new patient's quantitative imaging biomarker measurement constructed under the no-bias assumption provide nominal coverage as long as the fixed bias is <12%. For confidence intervals of the true change over time, linearity must hold and the slope of the regression of the measurements vs. true values should be between 0.95 and 1.05. The regression slope can be assessed adequately as long as fixed multiples of the measurand can be generated. Even small non-proportional bias greatly reduces confidence interval coverage. Multiple lesions in the same subject can be treated as independent when estimating precision. Conclusion Technical performance studies of quantitative imaging biomarkers require moderate sample sizes in

  8. Quantitative imaging as cancer biomarker

    NASA Astrophysics Data System (ADS)

    Mankoff, David A.

    2015-03-01

    The ability to assay tumor biologic features and the impact of drugs on tumor biology is fundamental to drug development. Advances in our ability to measure genomics, gene expression, protein expression, and cellular biology have led to a host of new targets for anticancer drug therapy. In translating new drugs into clinical trials and clinical practice, these same assays serve to identify patients most likely to benefit from specific anticancer treatments. As cancer therapy becomes more individualized and targeted, there is an increasing need to characterize tumors and identify therapeutic targets to select therapy most likely to be successful in treating the individual patient's cancer. Thus far assays to identify cancer therapeutic targets or anticancer drug pharmacodynamics have been based upon in vitro assay of tissue or blood samples. Advances in molecular imaging, particularly PET, have led to the ability to perform quantitative non-invasive molecular assays. Imaging has traditionally relied on structural and anatomic features to detect cancer and determine its extent. More recently, imaging has expanded to include the ability to image regional biochemistry and molecular biology, often termed molecular imaging. Molecular imaging can be considered an in vivo assay technique, capable of measuring regional tumor biology without perturbing it. This makes molecular imaging a unique tool for cancer drug development, complementary to traditional assay methods, and a potentially powerful method for guiding targeted therapy in clinical trials and clinical practice. The ability to quantify, in absolute measures, regional in vivo biologic parameters strongly supports the use of molecular imaging as a tool to guide therapy. This review summarizes current and future applications of quantitative molecular imaging as a biomarker for cancer therapy, including the use of imaging to (1) identify patients whose tumors express a specific therapeutic target; (2) determine

  9. The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions.

    PubMed

    Kessler, Larry G; Barnhart, Huiman X; Buckler, Andrew J; Choudhury, Kingshuk Roy; Kondratovich, Marina V; Toledano, Alicia; Guimaraes, Alexander R; Filice, Ross; Zhang, Zheng; Sullivan, Daniel C

    2015-02-01

    The development and implementation of quantitative imaging biomarkers has been hampered by the inconsistent and often incorrect use of terminology related to these markers. Sponsored by the Radiological Society of North America, an interdisciplinary group of radiologists, statisticians, physicists, and other researchers worked to develop a comprehensive terminology to serve as a foundation for quantitative imaging biomarker claims. Where possible, this working group adapted existing definitions derived from national or international standards bodies rather than invent new definitions for these terms. This terminology also serves as a foundation for the design of studies that evaluate the technical performance of quantitative imaging biomarkers and for studies of algorithms that generate the quantitative imaging biomarkers from clinical scans. This paper provides examples of research studies and quantitative imaging biomarker claims that use terminology consistent with these definitions as well as examples of the rampant confusion in this emerging field. We provide recommendations for appropriate use of quantitative imaging biomarker terminological concepts. It is hoped that this document will assist researchers and regulatory reviewers who examine quantitative imaging biomarkers and will also inform regulatory guidance. More consistent and correct use of terminology could advance regulatory science, improve clinical research, and provide better care for patients who undergo imaging studies. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  10. Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

    PubMed

    Dolled-Filhart, Marisa P; Gustavson, Mark D

    2012-11-01

    Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

  11. Quantitative Imaging Biomarkers: A Review of Statistical Methods for Technical Performance Assessment

    PubMed Central

    2017-01-01

    Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers (QIBs) to measure changes in these features. Critical to the performance of a QIB in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method and metrics used to assess a QIB for clinical use. It is therefore, difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America (RSNA) and the Quantitative Imaging Biomarker Alliance (QIBA) with technical, radiological and statistical experts developed a set of technical performance analysis methods, metrics and study designs that provide terminology, metrics and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of QIB performance studies so that results from multiple studies can be compared, contrasted or combined. PMID:24919831

  12. Quantitative Imaging Biomarkers: A Review of Statistical Methods for Computer Algorithm Comparisons

    PubMed Central

    2014-01-01

    Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. PMID:24919829

  13. Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons.

    PubMed

    Obuchowski, Nancy A; Reeves, Anthony P; Huang, Erich P; Wang, Xiao-Feng; Buckler, Andrew J; Kim, Hyun J Grace; Barnhart, Huiman X; Jackson, Edward F; Giger, Maryellen L; Pennello, Gene; Toledano, Alicia Y; Kalpathy-Cramer, Jayashree; Apanasovich, Tatiyana V; Kinahan, Paul E; Myers, Kyle J; Goldgof, Dmitry B; Barboriak, Daniel P; Gillies, Robert J; Schwartz, Lawrence H; Sullivan, Daniel C

    2015-02-01

    Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  14. Statistical issues in the comparison of quantitative imaging biomarker algorithms using pulmonary nodule volume as an example.

    PubMed

    Obuchowski, Nancy A; Barnhart, Huiman X; Buckler, Andrew J; Pennello, Gene; Wang, Xiao-Feng; Kalpathy-Cramer, Jayashree; Kim, Hyun J Grace; Reeves, Anthony P

    2015-02-01

    Quantitative imaging biomarkers are being used increasingly in medicine to diagnose and monitor patients' disease. The computer algorithms that measure quantitative imaging biomarkers have different technical performance characteristics. In this paper we illustrate the appropriate statistical methods for assessing and comparing the bias, precision, and agreement of computer algorithms. We use data from three studies of pulmonary nodules. The first study is a small phantom study used to illustrate metrics for assessing repeatability. The second study is a large phantom study allowing assessment of four algorithms' bias and reproducibility for measuring tumor volume and the change in tumor volume. The third study is a small clinical study of patients whose tumors were measured on two occasions. This study allows a direct assessment of six algorithms' performance for measuring tumor change. With these three examples we compare and contrast study designs and performance metrics, and we illustrate the advantages and limitations of various common statistical methods for quantitative imaging biomarker studies. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

    Quantitative phase microscopy (QPM) has recently emerged as a powerful label-free technique in the field of living cell imaging allowing to non-invasively measure with a nanometric axial sensitivity cell structure and dynamics. Since the phase retardation of a light wave when transmitted through the observed cells, namely the quantitative phase signal (QPS), is sensitive to both cellular thickness and intracellular refractive index related to the cellular content, its accurate analysis allows to derive various cell parameters and monitor specific cell processes, which are very likely to identify new cell biomarkers. Specifically, quantitative phase-digital holographic microscopy (QP-DHM), thanks to its numerical flexibility facilitating 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.

  16. Statistical Issues in Testing Conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Profile Claims.

    PubMed

    Obuchowski, Nancy A; Buckler, Andrew; Kinahan, Paul; Chen-Mayer, Heather; Petrick, Nicholas; Barboriak, Daniel P; Bullen, Jennifer; Barnhart, Huiman; Sullivan, Daniel C

    2016-04-01

    A major initiative of the Quantitative Imaging Biomarker Alliance is to develop standards-based documents called "Profiles," which describe one or more technical performance claims for a given imaging modality. The term "actor" denotes any entity (device, software, or person) whose performance must meet certain specifications for the claim to be met. The objective of this paper is to present the statistical issues in testing actors' conformance with the specifications. In particular, we present the general rationale and interpretation of the claims, the minimum requirements for testing whether an actor achieves the performance requirements, the study designs used for testing conformity, and the statistical analysis plan. We use three examples to illustrate the process: apparent diffusion coefficient in solid tumors measured by MRI, change in Perc 15 as a biomarker for the progression of emphysema, and percent change in solid tumor volume by computed tomography as a biomarker for lung cancer progression. Copyright © 2016 The Association of University Radiologists. All rights reserved.

  17. Semi-Quantitative Imaging Biomarkers of Knee Osteoarthritis Progression: Data from the FNIH OA Biomarkers Consortium

    PubMed Central

    Collins, Jamie E.; Losina, Elena; Nevitt, Michael C.; Roemer, Frank W.; Guermazi, Ali; Lynch, John A.; Katz, Jeffrey N.; Kwoh, C. Kent; Kraus, Virginia B.; Hunter, David J.

    2017-01-01

    Objective To determine the association between changes in semi-quantitative knee MRI biomarkers over 24 months and radiographic and pain progression over 48 months in knees with mild to moderate osteoarthritis. Methods We undertook a nested case-control study as part of the Osteoarthritis Biomarkers Consortium Project. We built multivariable logistic regression models to examine the association between change over 24 months in semi-quantitative MR imaging markers and knee OA radiographic and pain progression. MRIs were read according to the MRI Osteoarthritis Knee Score (MOAKS) scoring system. We focused on changes in cartilage, osteophytes, meniscus, bone marrow lesions, Hoffa-synovitis, and synovitis-effusion. Results The most parsimonious model included changes in cartilage thickness and surface area, synovitis-effusion, Hoffa-synovitis, and meniscal morphology (C-statistic =0.740). Subjects with worsening cartilage thickness in 3+ subregions vs. no worsening had 2.8-fold (95% CI: 1.3 – 5.9) greater odds of being a case while subjects with worsening in cartilage surface area in 3+ subregions vs. no worsening had 2.4-fold (95% CI: 1.3 – 4.4) greater odds of being a case. Having worsening in any region in meniscal morphology was associated with a 2.2-fold (95%CI: 1.3 – 3.8) greater odds of being a case. Worsening synovitis-effusion (OR=2.7) and Hoffa-synovitis (OR=2.0) were also associated with greater odds of being a case. Conclusion Twenty-four-month change in cartilage thickness, cartilage surface area, synovitis-effusion, Hoffa-synovitis, and meniscal morphology were independently associated with OA progression, suggesting that they may serve as efficacy biomarkers in clinical trials of disease modifying interventions for knee OA. PMID:27111771

  18. TH-A-207B-00: Shear-Wave Imaging and a QIBA US Biomarker Update

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    NONE

    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 targetmore » 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

  19. TH-A-207B-02: QIBA Ultrasound Elasticity Imaging System Biomarker Qualification and User Testing of Systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Garra, B.

    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 targetmore » 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

  20. Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study

    NASA Astrophysics Data System (ADS)

    Qiu, Yuchen; Tan, Maxine; McMeekin, Scott; Thai, Theresa; Moore, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

    2015-03-01

    The purpose of this study is to identify and apply quantitative image biomarkers for early prediction of the tumor response to the chemotherapy among the ovarian cancer patients participated in the clinical trials of testing new drugs. In the experiment, we retrospectively selected 30 cases from the patients who participated in Phase I clinical trials of new drug or drug agents for ovarian cancer treatment. Each case is composed of two sets of CT images acquired pre- and post-treatment (4-6 weeks after starting treatment). A computer-aided detection (CAD) scheme was developed to extract and analyze the quantitative image features of the metastatic tumors previously tracked by the radiologists using the standard Response Evaluation Criteria in Solid Tumors (RECIST) guideline. The CAD scheme first segmented 3-D tumor volumes from the background using a hybrid tumor segmentation scheme. Then, for each segmented tumor, CAD computed three quantitative image features including the change of tumor volume, tumor CT number (density) and density variance. The feature changes were calculated between the matched tumors tracked on the CT images acquired pre- and post-treatments. Finally, CAD predicted patient's 6-month progression-free survival (PFS) using a decision-tree based classifier. The performance of the CAD scheme was compared with the RECIST category. The result shows that the CAD scheme achieved a prediction accuracy of 76.7% (23/30 cases) with a Kappa coefficient of 0.493, which is significantly higher than the performance of RECIST prediction with a prediction accuracy and Kappa coefficient of 60% (17/30) and 0.062, respectively. This study demonstrated the feasibility of analyzing quantitative image features to improve the early predicting accuracy of the tumor response to the new testing drugs or therapeutic methods for the ovarian cancer patients.

  1. Cartilage Repair Surgery: Outcome Evaluation by Using Noninvasive Cartilage Biomarkers Based on Quantitative MRI Techniques?

    PubMed Central

    Jungmann, Pia M.; Baum, Thomas; Bauer, Jan S.; Karampinos, Dimitrios C.; Link, Thomas M.; Li, Xiaojuan; Trattnig, Siegfried; Rummeny, Ernst J.; Woertler, Klaus; Welsch, Goetz H.

    2014-01-01

    Background. New quantitative magnetic resonance imaging (MRI) techniques are increasingly applied as outcome measures after cartilage repair. Objective. To review the current literature on the use of quantitative MRI biomarkers for evaluation of cartilage repair at the knee and ankle. Methods. Using PubMed literature research, studies on biochemical, quantitative MR imaging of cartilage repair were identified and reviewed. Results. Quantitative MR biomarkers detect early degeneration of articular cartilage, mainly represented by an increasing water content, collagen disruption, and proteoglycan loss. Recently, feasibility of biochemical MR imaging of cartilage repair tissue and surrounding cartilage was demonstrated. Ultrastructural properties of the tissue after different repair procedures resulted in differences in imaging characteristics. T2 mapping, T1rho mapping, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), and diffusion weighted imaging (DWI) are applicable on most clinical 1.5 T and 3 T MR scanners. Currently, a standard of reference is difficult to define and knowledge is limited concerning correlation of clinical and MR findings. The lack of histological correlations complicates the identification of the exact tissue composition. Conclusions. A multimodal approach combining several quantitative MRI techniques in addition to morphological and clinical evaluation might be promising. Further investigations are required to demonstrate the potential for outcome evaluation after cartilage repair. PMID:24877139

  2. Digital imaging biomarkers feed machine learning for melanoma screening.

    PubMed

    Gareau, Daniel S; Correa da Rosa, Joel; Yagerman, Sarah; Carucci, John A; Gulati, Nicholas; Hueto, Ferran; DeFazio, Jennifer L; Suárez-Fariñas, Mayte; Marghoob, Ashfaq; Krueger, James G

    2017-07-01

    We developed an automated approach for generating quantitative image analysis metrics (imaging biomarkers) that are then analysed with a set of 13 machine learning algorithms to generate an overall risk score that is called a Q-score. These methods were applied to a set of 120 "difficult" dermoscopy images of dysplastic nevi and melanomas that were subsequently excised/classified. This approach yielded 98% sensitivity and 36% specificity for melanoma detection, approaching sensitivity/specificity of expert lesion evaluation. Importantly, we found strong spectral dependence of many imaging biomarkers in blue or red colour channels, suggesting the need to optimize spectral evaluation of pigmented lesions. © 2016 The Authors. Experimental Dermatology Published by John Wiley & Sons Ltd.

  3. Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

    PubMed

    Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

    2014-01-01

    Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

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

    PubMed

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

    2014-10-01

    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 developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

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

    PubMed Central

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

    2014-01-01

    Abstract. 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 developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed. PMID:26157976

  6. Quantitative, spectrally-resolved intraoperative fluorescence imaging

    PubMed Central

    Valdés, Pablo A.; Leblond, Frederic; Jacobs, Valerie L.; Wilson, Brian C.; Paulsen, Keith D.; Roberts, David W.

    2012-01-01

    Intraoperative visual fluorescence imaging (vFI) has emerged as a promising aid to surgical guidance, but does not fully exploit the potential of the fluorescent agents that are currently available. Here, we introduce a quantitative fluorescence imaging (qFI) approach that converts spectrally-resolved data into images of absolute fluorophore concentration pixel-by-pixel across the surgical field of view (FOV). The resulting estimates are linear, accurate, and precise relative to true values, and spectral decomposition of multiple fluorophores is also achieved. Experiments with protoporphyrin IX in a glioma rodent model demonstrate in vivo quantitative and spectrally-resolved fluorescence imaging of infiltrating tumor margins for the first time. Moreover, we present images from human surgery which detect residual tumor not evident with state-of-the-art vFI. The wide-field qFI technique has broad implications for intraoperative surgical guidance because it provides near real-time quantitative assessment of multiple fluorescent biomarkers across the operative field. PMID:23152935

  7. Biomarkers and Surrogate Endpoints in Uveitis: The Impact of Quantitative Imaging.

    PubMed

    Denniston, Alastair K; Keane, Pearse A; Srivastava, Sunil K

    2017-05-01

    Uveitis is a major cause of sight loss across the world. The reliable assessment of intraocular inflammation in uveitis ('disease activity') is essential in order to score disease severity and response to treatment. In this review, we describe how 'quantitative imaging', the approach of using automated analysis and measurement algorithms across both standard and emerging imaging modalities, can develop objective instrument-based measures of disease activity. This is a narrative review based on searches of the current world literature using terms related to quantitative imaging techniques in uveitis, supplemented by clinical trial registry data, and expert knowledge of surrogate endpoints and outcome measures in ophthalmology. Current measures of disease activity are largely based on subjective clinical estimation, and are relatively insensitive, with poor discrimination and reliability. The development of quantitative imaging in uveitis is most established in the use of optical coherence tomographic (OCT) measurement of central macular thickness (CMT) to measure severity of macular edema (ME). The transformative effect of CMT in clinical assessment of patients with ME provides a paradigm for the development and impact of other forms of quantitative imaging. Quantitative imaging approaches are now being developed and validated for other key inflammatory parameters such as anterior chamber cells, vitreous haze, retinovascular leakage, and chorioretinal infiltrates. As new forms of quantitative imaging in uveitis are proposed, the uveitis community will need to evaluate these tools against the current subjective clinical estimates and reach a new consensus for how disease activity in uveitis should be measured. The development, validation, and adoption of sensitive and discriminatory measures of disease activity is an unmet need that has the potential to transform both drug development and routine clinical care for the patient with uveitis.

  8. DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research.

    PubMed

    Fedorov, Andriy; Clunie, David; Ulrich, Ethan; Bauer, Christian; Wahle, Andreas; Brown, Bartley; Onken, Michael; Riesmeier, Jörg; Pieper, Steve; Kikinis, Ron; Buatti, John; Beichel, Reinhard R

    2016-01-01

    Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM(®)) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions

  9. DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research

    PubMed Central

    Clunie, David; Ulrich, Ethan; Bauer, Christian; Wahle, Andreas; Brown, Bartley; Onken, Michael; Riesmeier, Jörg; Pieper, Steve; Kikinis, Ron; Buatti, John; Beichel, Reinhard R.

    2016-01-01

    Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM®) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions

  10. Novel CT-based objective imaging biomarkers of long term radiation-induced lung damage.

    PubMed

    Veiga, Catarina; Landau, David; Devaraj, Anand; Doel, Tom; White, Jared; Ngai, Yenting; Hawkes, David J; McClelland, Jamie R

    2018-06-14

    and Purpose: Recent improvements in lung cancer survival have spurred an interest in understanding and minimizing long term radiation-induced lung damage (RILD). However, there is still no objective criteria to quantify RILD leading to variable reporting across centres and trials. We propose a set of objective imaging biomarkers to quantify common radiological findings observed 12-months after lung cancer radiotherapy (RT). Baseline and 12-month CT scans of 27 patients from a phase I/II clinical trial of isotoxic chemoradiation were included in this study. To detect and measure the severity of RILD, twelve quantitative imaging biomarkers were developed. These describe basic CT findings including parenchymal change, volume reduction and pleural change. The imaging biomarkers were implemented as semi-automated image analysis pipelines and assessed against visual assessment of the occurrence of each change. The majority of the biomarkers were measurable in each patient. Their continuous nature allows objective scoring of severity for each patient. For each imaging biomarker the cohort was split into two groups according to the presence or absence of the biomarker by visual assessment, testing the hypothesis that the imaging biomarkers were different in these two groups. All features were statistically significant except for rotation of the main bronchus and diaphragmatic curvature. The majority of the biomarkers were not strongly correlated with each other suggesting that each of the biomarkers is measuring a separate element of RILD pathology. We developed objective CT-based imaging biomarkers that quantify the severity of radiological lung damage after RT. These biomarkers are representative of typical radiological findings of RILD. Copyright © 2018. Published by Elsevier Inc.

  11. Volumetric CT in lung cancer: an example for the qualification of imaging as a biomarker.

    PubMed

    Buckler, Andrew J; Mozley, P David; Schwartz, Lawrence; Petrick, Nicholas; McNitt-Gray, Michael; Fenimore, Charles; O'Donnell, Kevin; Hayes, Wendy; Kim, Hyun J; Clarke, Laurence; Sullivan, Daniel

    2010-01-01

    New ways to understand biology as well as increasing interest in personalized treatments requires new capabilities for the assessment of therapy response. The lack of consensus methods and qualification evidence needed for large-scale multicenter trials, and in turn the standardization that allows them, are widely acknowledged to be the limiting factor in the deployment of qualified imaging biomarkers. The Quantitative Imaging Biomarker Alliance is organized to establish a methodology whereby multiple stakeholders collaborate. It has charged the Volumetric Computed Tomography (CT) Technical Subcommittee with investigating the technical feasibility and clinical value of quantifying changes over time in either volume or other parameters as biomarkers. The group selected solid tumors of the chest in subjects with lung cancer as its first case in point. Success is defined as sufficiently rigorous improvements in CT-based outcome measures to allow individual patients in clinical settings to switch treatments sooner if they are no longer responding to their current regimens, and reduce the costs of evaluating investigational new drugs to treat lung cancer. The team has completed a systems engineering analysis, has begun a roadmap of experimental groundwork, documented profile claims and protocols, and documented a process for imaging biomarker qualification as a general paradigm for qualifying other imaging biomarkers as well. This report addresses a procedural template for the qualification of quantitative imaging biomarkers. This mechanism is cost-effective for stakeholders while simultaneously advancing the public health by promoting the use of measures that prove effective.

  12. Spectropathology-corroborated multimodal quantitative imaging biomarkers for neuroretinal degeneration in diabetic retinopathy

    PubMed Central

    Guha Mazumder, Arpan; Chatterjee, Swarnadip; Chatterjee, Saunak; Gonzalez, Juan Jose; Bag, Swarnendu; Ghosh, Sambuddha; Mukherjee, Anirban; Chatterjee, Jyotirmoy

    2017-01-01

    Introduction Image-based early detection for diabetic retinopathy (DR) needs value addition due to lack of well-defined disease-specific quantitative imaging biomarkers (QIBs) for neuroretinal degeneration and spectropathological information at the systemic level. Retinal neurodegeneration is an early event in the pathogenesis of DR. Therefore, development of an integrated assessment method for detecting neuroretinal degeneration using spectropathology and QIBs is necessary for the early diagnosis of DR. Methods The present work explored the efficacy of intensity and textural features extracted from optical coherence tomography (OCT) images after selecting a specific subset of features for the precise classification of retinal layers using variants of support vector machine (SVM). Fourier transform infrared (FTIR) spectroscopy and nuclear magnetic resonance (NMR) spectroscopy were also performed to confirm the spectropathological attributes of serum for further value addition to the OCT, fundoscopy, and fluorescein angiography (FA) findings. The serum metabolomic findings were also incorporated for characterizing retinal layer thickness alterations and vascular asymmetries. Results Results suggested that OCT features could differentiate the retinal lesions indicating retinal neurodegeneration with high sensitivity and specificity. OCT, fundoscopy, and FA provided geometrical as well as optical features. NMR revealed elevated levels of ribitol, glycerophosphocholine, and uridine diphosphate N-acetyl glucosamine, while the FTIR of serum samples confirmed the higher expressions of lipids and β-sheet-containing proteins responsible for neoangiogenesis, vascular fragility, vascular asymmetry, and subsequent neuroretinal degeneration in DR. Conclusion Our data indicated that disease-specific spectropathological alterations could be the major phenomena behind the vascular attenuations observed through fundoscopy and FA, as well as the variations in the intensity and

  13. Quantitative Medical Image Analysis for Clinical Development of Therapeutics

    NASA Astrophysics Data System (ADS)

    Analoui, Mostafa

    There has been significant progress in development of therapeutics for prevention and management of several disease areas in recent years, leading to increased average life expectancy, as well as of quality of life, globally. However, due to complexity of addressing a number of medical needs and financial burden of development of new class of therapeutics, there is a need for better tools for decision making and validation of efficacy and safety of new compounds. Numerous biological markers (biomarkers) have been proposed either as adjunct to current clinical endpoints or as surrogates. Imaging biomarkers are among rapidly increasing biomarkers, being examined to expedite effective and rational drug development. Clinical imaging often involves a complex set of multi-modality data sets that require rapid and objective analysis, independent of reviewer's bias and training. In this chapter, an overview of imaging biomarkers for drug development is offered, along with challenges that necessitate quantitative and objective image analysis. Examples of automated and semi-automated analysis approaches are provided, along with technical review of such methods. These examples include the use of 3D MRI for osteoarthritis, ultrasound vascular imaging, and dynamic contrast enhanced MRI for oncology. Additionally, a brief overview of regulatory requirements is discussed. In conclusion, this chapter highlights key challenges and future directions in this area.

  14. Analytical validation of quantitative immunohistochemical assays of tumor infiltrating lymphocyte biomarkers.

    PubMed

    Singh, U; Cui, Y; Dimaano, N; Mehta, S; Pruitt, S K; Yearley, J; Laterza, O F; Juco, J W; Dogdas, B

    2018-06-04

    Tumor infiltrating lymphocytes (TIL), especially T-cells, have both prognostic and therapeutic applications. The presence of CD8+ effector T-cells and the ratio of CD8+ cells to FOXP3+ regulatory T-cells have been used as biomarkers of disease prognosis to predict response to various immunotherapies. Blocking the interaction between inhibitory receptors on T-cells and their ligands with therapeutic antibodies including atezolizumab, nivolumab, pembrolizumab and tremelimumab increases the immune response against cancer cells and has shown significant improvement in clinical benefits and survival in several different tumor types. The improved clinical outcome is presumed to be associated with a higher tumor infiltration; therefore, it is thought that more accurate methods for measuring the amount of TIL could assist prognosis and predict treatment response. We have developed and validated quantitative immunohistochemistry (IHC) assays for CD3, CD8 and FOXP3 for immunophenotyping T-lymphocytes in tumor tissue. Various types of formalin fixed, paraffin embedded (FFPE) tumor tissues were immunolabeled with anti-CD3, anti-CD8 and anti-FOXP3 antibodies using an IHC autostainer. The tumor area of stained tissues, including the invasive margin of the tumor, was scored by a pathologist (visual scoring) and by computer-based quantitative image analysis. Two image analysis scores were obtained for the staining of each biomarker: the percent positive cells in the tumor area and positive cells/mm 2 tumor area. Comparison of visual vs. image analysis scoring methods using regression analysis showed high correlation and indicated that quantitative image analysis can be used to score the number of positive cells in IHC stained slides. To demonstrate that the IHC assays produce consistent results in normal daily testing, we evaluated the specificity, sensitivity and reproducibility of the IHC assays using both visual and image analysis scoring methods. We found that CD3, CD8 and

  15. Quantitative apparent diffusion coefficient as a noninvasive imaging biomarker for the differentiation of invasive breast cancer and ductal carcinoma in situ.

    PubMed

    Bickel, Hubert; Pinker-Domenig, Katja; Bogner, Wolfgang; Spick, Claudio; Bagó-Horváth, Zsuzsanna; Weber, Michael; Helbich, Thomas; Baltzer, Pascal

    2015-02-01

    The objective of this study was to evaluate whether apparent diffusion coefficient (ADC) obtained through diffusion-weighted imaging magnetic resonance imaging at 3 T can be used as an imaging biomarker to differentiate invasive breast cancer from noninvasive ductal carcinoma in situ (DCIS). One hundred seventy-six histopathologically verified primary malignant breast tumors were retrospectively evaluated in 170 patients. All patients had undergone a standardized 3-T magnetic resonance imaging protocol, containing a diffusion-weighted sequence with 2 b values and a series of dynamic contrast-enhanced T1-weighted sequences. Apparent diffusion coefficient was measured manually by a reader blinded to the histopathological results. The ADC values were correlated with histopathological results. Mean ADC values were compared between invasive cancers and DCIS as well as between different tumor grades. Receiver operating characteristics curves were used to calculate diagnostic performance. There were 155 invasive cancers and 21 noninvasive DCIS. Mean (SD) values differed significantly between the invasive cancers (0.9 [0.15] ×10 mm/s) and the DCIS (1.24 [0.23] ×10 mm/s, P < 0.001). Area under the receiver operating characteristics curve was 0.895 (95% confidence interval [CI], 0.840-0.936). A threshold of 1.01 ×10 mm/s or less allowed an identification of invasive cancers with a sensitivity of 78.06% (95% CI, 70.7%-84.3%) and a specificity of 90.5% (95% CI, 69.6%-98.8%). No significant ADC differences were found among different tumor grades (P > 0.05). Apparent diffusion coefficient could be used as an imaging biomarker for the diagnosis of breast cancer. It seems to be a valuable noninvasive quantitative biomarker to assess breast cancer invasiveness. Thus, ADC measurements provide the potential to reduce overdiagnosis and subsequent overtreatment.

  16. Enhancing image classification models with multi-modal biomarkers

    NASA Astrophysics Data System (ADS)

    Caban, Jesus J.; Liao, David; Yao, Jianhua; Mollura, Daniel J.; Gochuico, Bernadette; Yoo, Terry

    2011-03-01

    Currently, most computer-aided diagnosis (CAD) systems rely on image analysis and statistical models to diagnose, quantify, and monitor the progression of a particular disease. In general, CAD systems have proven to be effective at providing quantitative measurements and assisting physicians during the decision-making process. As the need for more flexible and effective CADs continues to grow, questions about how to enhance their accuracy have surged. In this paper, we show how statistical image models can be augmented with multi-modal physiological values to create more robust, stable, and accurate CAD systems. In particular, this paper demonstrates how highly correlated blood and EKG features can be treated as biomarkers and used to enhance image classification models designed to automatically score subjects with pulmonary fibrosis. In our results, a 3-5% improvement was observed when comparing the accuracy of CADs that use multi-modal biomarkers with those that only used image features. Our results show that lab values such as Erythrocyte Sedimentation Rate and Fibrinogen, as well as EKG measurements such as QRS and I:40, are statistically significant and can provide valuable insights about the severity of the pulmonary fibrosis disease.

  17. Quantitative multiplex detection of pathogen biomarkers

    DOEpatents

    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.

  18. Quantitative multiplex detection of pathogen biomarkers

    DOEpatents

    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.

  19. Serum Squamous Cell Carcinoma Antigen in Psoriasis: A Potential Quantitative Biomarker for Disease Severity.

    PubMed

    Sun, Ziwen; Shi, Xiaomin; Wang, Yun; Zhao, Yi

    2018-06-05

    An objective and quantitative method to evaluate psoriasis severity is important for practice and research in the precision care of psoriasis. We aimed to explore serum biomarkers quantitatively in association with disease severity and treatment response in psoriasis patients, with serum squamous cell carcinoma antigen (SCCA) evaluated in this pilot study. 15 psoriasis patients were treated with adalimumab. At different visits before and after treatment, quantitative body surface area (qBSA) was obtained from standardized digital body images of the patients, and the psoriasis area severity index (PASI) was also monitored. SCCA were detected by using microparticle enzyme immunoassay. The serum biomarkers were also tested in healthy volunteers as normal controls. Receiver-operating characteristic (ROC) curve analysis was used to explore the optimal cutoff point of SCCA to differentiate mild and moderate-to-severe psoriasis. The serum SCCA level in the psoriasis group was significantly higher (p < 0.05) than in the normal control group. After treatment, the serum SCCA levels were significantly decreased (p < 0.05). The SCCA level was well correlated with PASI and qBSA. In ROC analysis, when taking PASI = 10 or qBSA = 10% as the threshold, an optimal cutoff point of SCCA was found at 2.0 ng/mL with the highest Youden index. Serum SCCA might be a useful quantitative biomarker for psoriasis disease severity. © 2018 S. Karger AG, Basel.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bowen, S.

    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, headmore » 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.« less

  1. Fundamentals of quantitative dynamic contrast-enhanced MR imaging.

    PubMed

    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.

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

    PubMed

    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.

  3. Incorporating prognostic imaging biomarkers into clinical practice

    PubMed Central

    Miles, Kenneth A.

    2013-01-01

    Abstract A prognostic imaging biomarker can be defined as an imaging characteristic that is objectively measurable and provides information on the likely outcome of the cancer disease in an untreated individual and should be distinguished from predictive imaging biomarkers and imaging markers of response. A range of tumour characteristics of potential prognostic value can be measured using a variety imaging modalities. However, none has currently been adopted into routine clinical practice. This article considers key examples of emerging prognostic imaging biomarkers and proposes an evaluation framework that aims to demonstrate clinical efficacy and so support their introduction into the clinical arena. With appropriate validation within an established evaluation framework, prognostic imaging biomarkers have the potential to contribute to individualized cancer care, in some cases reducing the financial burden of expensive cancer treatments by facilitating their more rational use. PMID:24060808

  4. Magnetic resonance imaging retinal oximetry: a quantitative physiological biomarker for early diabetic retinopathy?

    PubMed

    Yang, Y; Zhu, X R; Xu, Q G; Metcalfe, H; Wang, Z C; Yang, J K

    2012-04-01

    To assess the efficacy of using magnetic resonance imaging measurements of retinal oxygenation response to detect early diabetic retinopathy in patients with Type 2 diabetes. Magnetic resonance imaging was conducted during 100% oxygen inhalation in patients with Type 2 diabetes with either no diabetic retinopathy (n = 12) or mild to moderate background diabetic retinopathy (n = 12), as well as in healthy control subjects (n = 12). Meanwhile, changes in retinal oxygenation response were measured. In the healthy control group, levels of retinal oxygenation response increased slowly during 100% oxygen inhalation. In contrast, they increased more quickly and attained homeostasis much earlier in the groups with background diabetic retinopathy (at the 20-min time point) and with no diabetic retinopathy (at the 25-min time point) than in the healthy control group (at the 42-min time point). Furthermore, levels of retinal oxygenation response in the group with background diabetic retinopathy increased more than that of the group with no diabetic retinopathy, which in turn increased more than that of the healthy control group. There are statistically significant differences between the group with background diabetic retinopathy and the healthy control group at 6-, 8-, 10-, 15-, 20- and 25-min time points (P < 0.05). According to the normal range of the healthy control group by setting fundus photography results as 'gold standard' in our research, the sensitivity, specificity, positive predictive value, negative predictive value and receiver operating characteristic area for reporting the early indications of utility of diabetic retinopathy were 83.33%, 58.33%, 50%, 87.5% and 0.774, respectively. The results indicate that magnetic resonance imaging is a potential screening method and probably a quantitative physiological biomarker to find early diabetic retinopathy in patients with Type 2 diabetes. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

  5. Clinical Utility of Quantitative Imaging

    PubMed Central

    Rosenkrantz, Andrew B; Mendiratta-Lala, Mishal; Bartholmai, Brian J.; Ganeshan, Dhakshinamoorthy; Abramson, Richard G.; Burton, Kirsteen R.; Yu, John-Paul J.; Scalzetti, Ernest M.; Yankeelov, Thomas E.; Subramaniam, Rathan M.; Lenchik, Leon

    2014-01-01

    Quantitative imaging (QI) is increasingly applied in modern radiology practice, assisting in the clinical assessment of many patients and providing a source of biomarkers for a spectrum of diseases. QI is commonly used to inform patient diagnosis or prognosis, determine the choice of therapy, or monitor therapy response. Because most radiologists will likely implement some QI tools to meet the patient care needs of their referring clinicians, it is important for all radiologists to become familiar with the strengths and limitations of QI. The Association of University Radiologists Radiology Research Alliance Quantitative Imaging Task Force has explored the clinical application of QI and summarizes its work in this review. We provide an overview of the clinical use of QI by discussing QI tools that are currently employed in clinical practice, clinical applications of these tools, approaches to reporting of QI, and challenges to implementing QI. It is hoped that these insights will help radiologists recognize the tangible benefits of QI to their patients, their referring clinicians, and their own radiology practice. PMID:25442800

  6. Quantitative imaging features: extension of the oncology medical image database

    NASA Astrophysics Data System (ADS)

    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.

  7. Development of imaging biomarkers and generation of big data.

    PubMed

    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.

  8. Test–retest repeatability of human speech biomarkers from static and real-time dynamic magnetic resonance imaging

    PubMed Central

    Töger, Johannes; Sorensen, Tanner; Somandepalli, Krishna; Toutios, Asterios; Lingala, Sajan Goud; Narayanan, Shrikanth; Nayak, Krishna

    2017-01-01

    Static anatomical and real-time dynamic magnetic resonance imaging (RT-MRI) of the upper airway is a valuable method for studying speech production in research and clinical settings. The test–retest repeatability of quantitative imaging biomarkers is an important parameter, since it limits the effect sizes and intragroup differences that can be studied. Therefore, this study aims to present a framework for determining the test–retest repeatability of quantitative speech biomarkers from static MRI and RT-MRI, and apply the framework to healthy volunteers. Subjects (n = 8, 4 females, 4 males) are imaged in two scans on the same day, including static images and dynamic RT-MRI of speech tasks. The inter-study agreement is quantified using intraclass correlation coefficient (ICC) and mean within-subject standard deviation (σe). Inter-study agreement is strong to very strong for static measures (ICC: min/median/max 0.71/0.89/0.98, σe: 0.90/2.20/6.72 mm), poor to strong for dynamic RT-MRI measures of articulator motion range (ICC: 0.26/0.75/0.90, σe: 1.6/2.5/3.6 mm), and poor to very strong for velocities (ICC: 0.21/0.56/0.93, σe: 2.2/4.4/16.7 cm/s). In conclusion, this study characterizes repeatability of static and dynamic MRI-derived speech biomarkers using state-of-the-art imaging. The introduced framework can be used to guide future development of speech biomarkers. Test–retest MRI data are provided free for research use. PMID:28599561

  9. Metabolic imaging biomarkers of postradiotherapy xerostomia.

    PubMed

    Cannon, Blake; Schwartz, David L; Dong, Lei

    2012-08-01

    Xerostomia is a major complication of head and neck radiotherapy (RT). Available xerostomia measures remain flawed. [(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. 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. Average whole-gland or voxel-by-voxel models incorporating parotid D(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). In this pilot series, loss of parotid FDG uptake was strongly associated with acute clinical post-RT parotid toxicity. D(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. Copyright © 2012 Elsevier Inc. All rights reserved.

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

    PubMed

    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.

  11. Low-frequency quantitative ultrasound imaging of cell death in vivo

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sadeghi-Naini, Ali; Falou, Omar; Czarnota, Gregory J.

    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 indicatedmore » 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

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

    PubMed

    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 < 0.0001) for epilepsy, while diffused pathology is associated with a lower risk. Early treatments with either isoflurane anaesthesia or losartan prevented early microvascular damage and late epilepsy. We suggest quantitative assessment of blood-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.

  13. Potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection

    NASA Astrophysics Data System (ADS)

    Kawata, Y.; Niki, N.; Ohmatsu, H.; Satake, M.; Kusumoto, M.; Tsuchida, T.; Aokage, K.; Eguchi, K.; Kaneko, M.; Moriyama, N.

    2014-03-01

    In this work, we investigate a potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection. The elucidation of the subcategorization of a pulmonary nodule type in CT images is an important preliminary step towards developing the nodule managements that are specific to each patient. We categorize lung cancers by analyzing volumetric distributions of CT values within lung cancers via a topic model such as latent Dirichlet allocation. Through applying our scheme to 3D CT images of nonsmall- cell lung cancer (maximum lesion size of 3 cm) , we demonstrate the potential usefulness of the topic model-based categorization of lung cancers as quantitative CT biomarkers.

  14. Statistical Issues in the Comparison of Quantitative Imaging Biomarker Algorithms using Pulmonary Nodule Volume as an Example

    PubMed Central

    2014-01-01

    Quantitative imaging biomarkers (QIBs) are being used increasingly in medicine to diagnose and monitor patients’ disease. The computer algorithms that measure QIBs have different technical performance characteristics. In this paper we illustrate the appropriate statistical methods for assessing and comparing the bias, precision, and agreement of computer algorithms. We use data from three studies of pulmonary nodules. The first study is a small phantom study used to illustrate metrics for assessing repeatability. The second study is a large phantom study allowing assessment of four algorithms’ bias and reproducibility for measuring tumor volume and the change in tumor volume. The third study is a small clinical study of patients whose tumors were measured on two occasions. This study allows a direct assessment of six algorithms’ performance for measuring tumor change. With these three examples we compare and contrast study designs and performance metrics, and we illustrate the advantages and limitations of various common statistical methods for QIB studies. PMID:24919828

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

    NASA Astrophysics Data System (ADS)

    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.

  16. Integration of co-localized glandular morphometry and protein biomarker expression in immunofluorescent images for prostate cancer prognosis

    NASA Astrophysics Data System (ADS)

    Scott, Richard; Khan, Faisal M.; Zeineh, Jack; Donovan, Michael; Fernandez, Gerardo

    2015-03-01

    Immunofluorescent (IF) image analysis of tissue pathology has proven to be extremely valuable and robust in developing prognostic assessments of disease, particularly in prostate cancer. There have been significant advances in the literature in quantitative biomarker expression as well as characterization of glandular architectures in discrete gland rings. However, while biomarker and glandular morphometric features have been combined as separate predictors in multivariate models, there is a lack of integrative features for biomarkers co-localized within specific morphological sub-types; for example the evaluation of androgen receptor (AR) expression within Gleason 3 glands only. In this work we propose a novel framework employing multiple techniques to generate integrated metrics of morphology and biomarker expression. We demonstrate the utility of the approaches in predicting clinical disease progression in images from 326 prostate biopsies and 373 prostatectomies. Our proposed integrative approaches yield significant improvements over existing IF image feature metrics. This work presents some of the first algorithms for generating innovative characteristics in tissue diagnostics that integrate co-localized morphometry and protein biomarker expression.

  17. Informatics methods to enable sharing of quantitative imaging research data.

    PubMed

    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.

  18. Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

    PubMed Central

    Saykin, Andrew J.; Shen, Li; Foroud, Tatiana M.; Potkin, Steven G.; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L.; Nho, Kwangsik; Huentelman, Matthew J.; Craig, David W.; Thompson, Paul M.; Stein, Jason L.; Moore, Jason H.; Farrer, Lindsay A.; Green, Robert C.; Bertram, Lars; Jack, Clifford R.; Weiner, Michael W.

    2010-01-01

    The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875

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

    Cancer.gov

    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.

  20. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network

    PubMed Central

    Fedorov, Andriy; Beichel, Reinhard; Kalpathy-Cramer, Jayashree; Finet, Julien; Fillion-Robin, Jean-Christophe; Pujol, Sonia; Bauer, Christian; Jennings, Dominique; Fennessy, Fiona; Sonka, Milan; Buatti, John; Aylward, Stephen; Miller, James V.; Pieper, Steve; Kikinis, Ron

    2012-01-01

    Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future

  1. Imaging biomarkers in multiple Sclerosis: From image analysis to population imaging.

    PubMed

    Barillot, Christian; Edan, Gilles; Commowick, Olivier

    2016-10-01

    The production of imaging data in medicine increases more rapidly than the capacity of computing models to extract information from it. The grand challenges of better understanding the brain, offering better care for neurological disorders, and stimulating new drug design will not be achieved without significant advances in computational neuroscience. The road to success is to develop a new, generic, computational methodology and to confront and validate this methodology on relevant diseases with adapted computational infrastructures. This new concept sustains the need to build new research paradigms to better understand the natural history of the pathology at the early phase; to better aggregate data that will provide the most complete representation of the pathology in order to better correlate imaging with other relevant features such as clinical, biological or genetic data. In this context, one of the major challenges of neuroimaging in clinical neurosciences is to detect quantitative signs of pathological evolution as early as possible to prevent disease progression, evaluate therapeutic protocols or even better understand and model the natural history of a given neurological pathology. Many diseases encompass brain alterations often not visible on conventional MRI sequences, especially in normal appearing brain tissues (NABT). MRI has often a low specificity for differentiating between possible pathological changes which could help in discriminating between the different pathological stages or grades. The objective of medical image analysis procedures is to define new quantitative neuroimaging biomarkers to track the evolution of the pathology at different levels. This paper illustrates this issue in one acute neuro-inflammatory pathology: Multiple Sclerosis (MS). It exhibits the current medical image analysis approaches and explains how this field of research will evolve in the next decade to integrate larger scale of information at the temporal, cellular

  2. Qualification of imaging biomarkers for oncology drug development.

    PubMed

    Waterton, John C; Pylkkanen, Liisa

    2012-03-01

    Although many imaging biomarkers have been described for cancer research, few are sufficiently robust, reliable and well-characterised to be used as routine tools in clinical cancer research. In particular, biomarkers which show that investigational therapies have reduced tumour cell proliferation, or induced necrotic or apoptotic cell death are not commonly used to support decision-making in drug development, even though such pharmacodynamic effects are common goals of many classes of investigational drugs. Moreover we lack well-qualified biomarkers of propensity to metastasise. The qualification and technical validation of imaging biomarkers poses unique challenges not always encountered when validating biospecimen biomarkers. These include standardisation of acquisition and analysis, imaging-pathology correlation, cross-sectional clinical-biomarker correlations and correlation with outcome. Such work is ideally suited to precompetitive research and public-private partnerships, and this has been recognised within the Innovative Medicines Initiative (IMI), a Joint Undertaking between the European Union and the European Federation of Pharmaceutical Industries and Associations, which has initiated projects in the areas of drug safety, drug efficacy, knowledge management and training. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. High throughput, parallel imaging and biomarker quantification of human spermatozoa by ImageStream flow cytometry.

    PubMed

    Buckman, Clayton; George, Thaddeus C; Friend, Sherree; Sutovsky, Miriam; Miranda-Vizuete, Antonio; Ozanon, Christophe; Morrissey, Phil; Sutovsky, Peter

    2009-12-01

    Spermatid specific thioredoxin-3 protein (SPTRX-3) accumulates in the superfluous cytoplasm of defective human spermatozoa. Novel ImageStream technology combining flow cytometry with cell imaging was used for parallel quantification and visualization of SPTRX-3 protein in defective spermatozoa of five men from infertile couples. The majority of the SPTRX-3 containing cells were overwhelmingly spermatozoa with a variety of morphological defects, detectable in the ImageStream recorded images. Quantitative parameters of relative SPTRX-3 induced fluorescence measured by ImageStream correlated closely with conventional flow cytometric measurements of the same sample set and reflected the results of clinical semen evaluation. Image Stream quantification of SPTRX-3 combines and surpasses the informative value of both conventional flow cytometry and light microscopic semen evaluation. The observed patterns of the retention of SPTRX-3 in the sperm samples from infertility patients support the view that SPTRX3 is a biomarker of male infertility.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jackson, E.

    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, andmore » 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

  5. Quantitative analysis of biological tissues using Fourier transform-second-harmonic generation imaging

    NASA Astrophysics Data System (ADS)

    Ambekar Ramachandra Rao, Raghu; Mehta, Monal R.; Toussaint, Kimani C., Jr.

    2010-02-01

    We demonstrate the use of Fourier transform-second-harmonic generation (FT-SHG) imaging of collagen fibers as a means of performing quantitative analysis of obtained images of selected spatial regions in porcine trachea, ear, and cornea. Two quantitative markers, preferred orientation and maximum spatial frequency are proposed for differentiating structural information between various spatial regions of interest in the specimens. The ear shows consistent maximum spatial frequency and orientation as also observed in its real-space image. However, there are observable changes in the orientation and minimum feature size of fibers in the trachea indicating a more random organization. Finally, the analysis is applied to a 3D image stack of the cornea. It is shown that the standard deviation of the orientation is sensitive to the randomness in fiber orientation. Regions with variations in the maximum spatial frequency, but with relatively constant orientation, suggest that maximum spatial frequency is useful as an independent quantitative marker. We emphasize that FT-SHG is a simple, yet powerful, tool for extracting information from images that is not obvious in real space. This technique can be used as a quantitative biomarker to assess the structure of collagen fibers that may change due to damage from disease or physical injury.

  6. Quantitative multiplex detection of biomarkers on a waveguide-based biosensor using quantum dots

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Xie, Hongzhi; Mukundan, Harshini; Martinez, Jennifer S

    2009-01-01

    The quantitative, simultaneous detection of multiple biomarkers with high sensitivity and specificity is critical for biomedical diagnostics, drug discovery and biomarker characterization [Wilson 2006, Tok 2006, Straub 2005, Joos 2002, Jani 2000]. Detection systems relying on optical signal transduction are, in general, advantageous because they are fast, portable, inexpensive, sensitive, and have the potential for multiplex detection of analytes of interest. However, conventional immunoassays for the detection of biomarkers, such as the Enzyme Linked Immunosorbant Assays (ELISAs) are semi-quantitative, time consuming and insensitive. ELISA assays are also limited by high non-specific binding, especially when used with complex biological samples suchmore » as serum and urine (REF). Organic fluorophores that are commonly used in such applications lack photostability and possess a narrow Stoke's shift that makes simultaneous detection of multiple fluorophores with a single excitation source difficult, thereby restricting their use in multiplex assays. The above limitations with traditional assay platforms have resulted in the increased use of nanotechnology-based tools and techniques in the fields of medical imaging [ref], targeted drug delivery [Caruthers 2007, Liu 2007], and sensing [ref]. One such area of increasing interest is the use of semiconductor quantum dots (QDs) for biomedical research and diagnostics [Gao and Cui 2004, Voura 2004, Michalet 2005, Chan 2002, Jaiswal 2004, Gao 2005, Medintz 2005, So 2006 2006, Wu 2003]. Compared to organic dyes, QDs provide several advantages for use in immunoassay platforms, including broad absorption bands with high extinction coefficients, narrow and symmetric emission bands with high quantum yields, high photostablility, and a large Stokes shift [Michalet 2005, Gu 2002]. These features prompted the use of QDs as probes in biodetection [Michalet 2005, Medintz 2005]. For example, Jaiswal et al. reported long term

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

    PubMed

    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.

  8. Magnetic Resonance Spectroscopy: An In Vivo Molecular Imaging Biomarker for Parkinson's Disease?

    PubMed Central

    Ciurleo, Rosella; Di Lorenzo, Giuseppe; Marino, Silvia

    2014-01-01

    Parkinson's disease (PD) is a neurodegenerative disorder caused by selective loss of dopaminergic neurons in the substantia nigra pars compacta which leads to dysfunction of cerebral pathways critical for the control of movements. The diagnosis of PD is based on motor symptoms, such as bradykinesia, akinesia, muscular rigidity, postural instability, and resting tremor, which are evident only after the degeneration of a significant number of dopaminergic neurons. Currently, a marker for early diagnosis of PD is still not available. Consequently, also the development of disease-modifying therapies is a challenge. Magnetic resonance spectroscopy is a quantitative imaging technique that allows in vivo measurement of certain neurometabolites and may produce biomarkers that reflect metabolic dysfunctions and irreversible neuronal damage. This review summarizes the abnormalities of cerebral metabolites found in MRS studies performed in patients with PD and other forms of parkinsonism. In addition, we discuss the potential role of MRS as in vivo molecular imaging biomarker for early diagnosis of PD and for monitoring the efficacy of therapeutic interventions. PMID:25302300

  9. 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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie

    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 162more » 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

  10. Challenges and Opportunities for Extracting Cardiovascular Risk Biomarkers from Imaging Data

    NASA Astrophysics Data System (ADS)

    Kakadiaris, I. A.; Mendizabal-Ruiz, E. G.; Kurkure, U.; Naghavi, M.

    Complications attributed to cardiovascular diseases (CDV) are the leading cause of death worldwide. In the United States, sudden heart attack remains the number one cause of death and accounts for the majority of the 280 billion burden of cardiovascular diseases. In spite of the advancements in cardiovascular imaging techniques, the rate of deaths due to unpredicted heart attack remains high. Thus, novel computational tools are of critical need, in order to mine quantitative parameters from the imaging data for early detection of persons with a high likelihood of developing a heart attack in the near future (vulnerable patients). In this paper, we present our progress in the research of computational methods for the extraction of cardiovascular risk biomarkers from cardiovascular imaging data. In particular, we focus on the methods developed for the analysis of intravascular ultrasound (IVUS) data.

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

    PubMed

    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.

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

    PubMed

    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

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

    PubMed Central

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

    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. PMID:28326926

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

    PubMed

    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.

  15. A standardized kit for automated quantitative assessment of candidate protein biomarkers in human plasma.

    PubMed

    Percy, Andrew J; Mohammed, Yassene; Yang, Juncong; Borchers, Christoph H

    2015-12-01

    An increasingly popular mass spectrometry-based quantitative approach for health-related research in the biomedical field involves the use of stable isotope-labeled standards (SIS) and multiple/selected reaction monitoring (MRM/SRM). To improve inter-laboratory precision and enable more widespread use of this 'absolute' quantitative technique in disease-biomarker assessment studies, methods must be standardized. Results/methodology: Using this MRM-with-SIS-peptide approach, we developed an automated method (encompassing sample preparation, processing and analysis) for quantifying 76 candidate protein markers (spanning >4 orders of magnitude in concentration) in neat human plasma. The assembled biomarker assessment kit - the 'BAK-76' - contains the essential materials (SIS mixes), methods (for acquisition and analysis), and tools (Qualis-SIS software) for performing biomarker discovery or verification studies in a rapid and standardized manner.

  16. Biomarkers of Cell Senescence Assessed by Imaging Cytometry

    PubMed Central

    Zhao, Hong; Darzynkiewicz, Zbigniew

    2012-01-01

    The characteristic features of senescent cells such as their “flattened” appearance, enlarged nuclei and low saturation density at the plateau phase of cell growth, can be conveniently measured by image-assisted d cytometry such as provided by the laser scanning cytometry (LSC). The “flattening” of senescent cells is reflected by the decline in local density of staining (intensity of maximal pixel) of DNA-associated fluorescence [4,6-diamidino-2- phenylindole (DAPI)] paralleled by an increase in nuclear size (area). Thus, the ratio of the maximal pixel of DAPI fluorescence per nucleus to the nuclear area provides a very sensitive morphometric biomarker of “depth” of senescence, which progressively declines during induction of senescence. Also recorded is cellular DNA content revealing cell cycle phase, as well as the saturation cell density at plateau phase of growth, which is dramatically decreased in cultures of senescent cells. Concurrent immunocytochemical analysis of expression of p21WAF1, p16INK4a or p27KIP1 cyclin kinase inhibitor provides additional markers of senescence. These biomarker indices can be expressed in quantitative terms (“senescence indices”) as a fraction of the same markers of the exponentially growing cells in control cultures. PMID:23296652

  17. A novel image-based quantitative method for the characterization of NETosis

    PubMed Central

    Zhao, Wenpu; Fogg, Darin K.; Kaplan, Mariana J.

    2015-01-01

    NETosis is a newly recognized mechanism of programmed neutrophil death. It is characterized by a stepwise progression of chromatin decondensation, membrane rupture, and release of bactericidal DNA-based structures called neutrophil extracellular traps (NETs). Conventional ‘suicidal’ NETosis has been described in pathogenic models of systemic autoimmune disorders. Recent in vivo studies suggest that a process of ‘vital’ NETosis also exists, in which chromatin is condensed and membrane integrity is preserved. Techniques to assess ‘suicidal’ or ‘vital’ NET formation in a specific, quantitative, rapid and semiautomated way have been lacking, hindering the characterization of this process. Here we have developed a new method to simultaneously assess both ‘suicidal’ and ‘vital’ NETosis, using high-speed multi-spectral imaging coupled to morphometric image analysis, to quantify spontaneous NET formation observed ex-vivo or stimulus-induced NET formation triggered in vitro. Use of imaging flow cytometry allows automated, quantitative and rapid analysis of subcellular morphology and texture, and introduces the potential for further investigation using NETosis as a biomarker in pre-clinical and clinical studies. PMID:26003624

  18. Assessment of quantitative cortical biomarkers in the developing brain of preterm infants

    NASA Astrophysics Data System (ADS)

    Moeskops, Pim; Benders, Manon J. N. L.; Pearlman, Paul C.; Kersbergen, Karina J.; Leemans, Alexander; Viergever, Max A.; Išgum, Ivana

    2013-02-01

    The cerebral cortex rapidly develops its folding during the second and third trimester of pregnancy. In preterm birth, this growth might be disrupted and influence neurodevelopment. The aim of this work is to extract quantitative biomarkers describing the cortex and evaluate them on a set of preterm infants without brain pathology. For this study, a set of 19 preterm - but otherwise healthy - infants scanned coronally with 3T MRI at the postmenstrual age of 30 weeks were selected. In ten patients (test set), the gray and white matter were manually annotated by an expert on the T2-weighted scans. Manual segmentations were used to extract cortical volume, surface area, thickness, and curvature using voxel-based methods. To compute these biomarkers per region in every patient, a template brain image has been generated by iterative registration and averaging of the scans of the remaining nine patients. This template has been manually divided in eight regions, and is transformed to every test image using elastic registration. In the results, gray and white matter volumes and cortical surface area appear symmetric between hemispheres, but small regional differences are visible. Cortical thickness seems slightly higher in the right parietal lobe than in other regions. The parietal lobes exhibit a higher global curvature, indicating more complex folding compared to other regions. The proposed approach can potentially - together with an automatic segmentation algorithm - be applied as a tool to assist in early diagnosis of abnormalities and prediction of the development of the cognitive abilities of these children.

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

    PubMed

    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

  20. Multiplexed MRM-based quantitation of candidate cancer biomarker proteins in undepleted and non-enriched human plasma.

    PubMed

    Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Borchers, Christoph H

    2013-07-01

    An emerging approach for multiplexed targeted proteomics involves bottom-up LC-MRM-MS, with stable isotope-labeled internal standard peptides, to accurately quantitate panels of putative disease biomarkers in biofluids. In this paper, we used this approach to quantitate 27 candidate cancer-biomarker proteins in human plasma that had not been treated by immunoaffinity depletion or enrichment techniques. These proteins have been reported as biomarkers for a variety of human cancers, from laryngeal to ovarian, with breast cancer having the highest correlation. We implemented measures to minimize the analytical variability, improve the quantitative accuracy, and increase the feasibility and applicability of this MRM-based method. We have demonstrated excellent retention time reproducibility (median interday CV: 0.08%) and signal stability (median interday CV: 4.5% for the analytical platform and 6.1% for the bottom-up workflow) for the 27 biomarker proteins (represented by 57 interference-free peptides). The linear dynamic range for the MRM assays spanned four orders-of-magnitude, with 25 assays covering a 10(3) -10(4) range in protein concentration. The lowest abundance quantifiable protein in our biomarker panel was insulin-like growth factor 1 (calculated concentration: 127 ng/mL). Overall, the analytical performance of this assay demonstrates high robustness and sensitivity, and provides the necessary throughput and multiplexing capabilities required to verify and validate cancer-associated protein biomarker panels in human plasma, prior to clinical use. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Functional Imaging Biomarkers: Potential to Guide an Individualised Approach to Radiotherapy.

    PubMed

    Prestwich, R J D; Vaidyanathan, S; Scarsbrook, A F

    2015-10-01

    The identification of robust prognostic and predictive biomarkers would transform the ability to implement an individualised approach to radiotherapy. In this regard, there has been a surge of interest in the use of functional imaging to assess key underlying biological processes within tumours and their response to therapy. Importantly, functional imaging biomarkers hold the potential to evaluate tumour heterogeneity/biology both spatially and temporally. An ever-increasing range of functional imaging techniques is now available primarily involving positron emission tomography and magnetic resonance imaging. Small-scale studies across multiple tumour types have consistently been able to correlate changes in functional imaging parameters during radiotherapy with disease outcomes. Considerable challenges remain before the implementation of functional imaging biomarkers into routine clinical practice, including the inherent temporal variability of biological processes within tumours, reproducibility of imaging, determination of optimal imaging technique/combinations, timing during treatment and design of appropriate validation studies. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  2. Qualitative and quantitative mass spectrometry imaging of drugs and metabolites in tissue at therapeutic levels.

    PubMed

    Sun, Na; Walch, Axel

    2013-08-01

    Mass spectrometry imaging (MSI) is a rapidly evolving technology that yields qualitative and quantitative distribution maps of small pharmaceutical-active molecules and their metabolites in tissue sections in situ. The simplicity, high sensitivity and ability to provide comprehensive spatial distribution maps of different classes of biomolecules make MSI a valuable tool to complement histopathology for diagnostics and biomarker discovery. In this review, qualitative and quantitative MSI of drugs and metabolites in tissue at therapeutic levels are discussed and the impact of this technique in drug discovery and clinical research is highlighted.

  3. Advances in Magnetic Resonance Imaging Contrast Agents for Biomarker Detection

    PubMed Central

    Sinharay, Sanhita; Pagel, Mark D.

    2016-01-01

    Recent advances in magnetic resonance imaging (MRI) contrast agents have provided new capabilities for biomarker detection through molecular imaging. MRI contrast agents based on the T2 exchange mechanism have more recently expanded the armamentarium of agents for molecular imaging. Compared with T1 and T2* agents, T2 exchange agents have a slower chemical exchange rate, which improves the ability to design these MRI contrast agents with greater specificity for detecting the intended biomarker. MRI contrast agents that are detected through chemical exchange saturation transfer (CEST) have even slower chemical exchange rates. Another emerging class of MRI contrast agents uses hyperpolarized 13C to detect the agent with outstanding sensitivity. These hyperpolarized 13C agents can be used to track metabolism and monitor characteristics of the tissue microenvironment. Together, these various MRI contrast agents provide excellent opportunities to develop molecular imaging for biomarker detection. PMID:27049630

  4. Ultratrace level determination and quantitative analysis of kidney injury biomarkers in patient samples attained by zinc oxide nanorods

    NASA Astrophysics Data System (ADS)

    Singh, Manpreet; Alabanza, Anginelle; Gonzalez, Lorelis E.; Wang, Weiwei; Reeves, W. Brian; Hahm, Jong-In

    2016-02-01

    Determining ultratrace amounts of protein biomarkers in patient samples in a straightforward and quantitative manner is extremely important for early disease diagnosis and treatment. Here, we successfully demonstrate the novel use of zinc oxide nanorods (ZnO NRs) in the ultrasensitive and quantitative detection of two acute kidney injury (AKI)-related protein biomarkers, tumor necrosis factor (TNF)-α and interleukin (IL)-8, directly from patient samples. We first validate the ZnO NRs-based IL-8 results via comparison with those obtained from using a conventional enzyme-linked immunosorbent method in samples from 38 individuals. We further assess the full detection capability of the ZnO NRs-based technique by quantifying TNF-α, whose levels in human urine are often below the detection limits of conventional methods. Using the ZnO NR platforms, we determine the TNF-α concentrations of all 46 patient samples tested, down to the fg per mL level. Subsequently, we screen for TNF-α levels in approximately 50 additional samples collected from different patient groups in order to demonstrate a potential use of the ZnO NRs-based assay in assessing cytokine levels useful for further clinical monitoring. Our research efforts demonstrate that ZnO NRs can be straightforwardly employed in the rapid, ultrasensitive, quantitative, and simultaneous detection of multiple AKI-related biomarkers directly in patient urine samples, providing an unparalleled detection capability beyond those of conventional analysis methods. Additional key advantages of the ZnO NRs-based approach include a fast detection speed, low-volume assay condition, multiplexing ability, and easy automation/integration capability to existing fluorescence instrumentation. Therefore, we anticipate that our ZnO NRs-based detection method will be highly beneficial for overcoming the frequent challenges in early biomarker development and treatment assessment, pertaining to the facile and ultrasensitive quantification

  5. Prevalence of Imaging Biomarkers to Guide the Planning of Acute Stroke Reperfusion Trials.

    PubMed

    Jiang, Bin; Ball, Robyn L; Michel, Patrik; Jovin, Tudor; Desai, Manisha; Eskandari, Ashraf; Naqvi, Zack; Wintermark, Max

    2017-06-01

    Imaging biomarkers are increasingly used as selection criteria for stroke clinical trials. The goal of our study was to determine the prevalence of commonly studied imaging biomarkers in different time windows after acute ischemic stroke onset to better facilitate the design of stroke clinical trials using such biomarkers for patient selection. This retrospective study included 612 patients admitted with a clinical suspicion of acute ischemic stroke with symptom onset no more than 24 hours before completing baseline imaging. Patients with subacute/chronic/remote infarcts and hemorrhage were excluded from this study. Imaging biomarkers were extracted from baseline imaging, which included a noncontrast head computed tomography (CT), perfusion CT, and CT angiography. The prevalence of dichotomized versions of each of the imaging biomarkers in several time windows (time since symptom onset) was assessed and statistically modeled to assess time dependence (not lack thereof). We created tables showing the prevalence of the imaging biomarkers pertaining to the core, the penumbra and the arterial occlusion for different time windows. All continuous imaging features vary over time. The dichotomized imaging features that vary significantly over time include: noncontrast head computed tomography Alberta Stroke Program Early CT (ASPECT) score and dense artery sign, perfusion CT infarct volume, and CT angiography collateral score and visible clot. The dichotomized imaging features that did not vary significantly over time include the thresholded perfusion CT penumbra volumes. As part of the feasibility analysis in stroke clinical trials, this analysis and the resulting tables can help investigators determine sample size and the number needed to screen. © 2017 American Heart Association, Inc.

  6. Detection of Prostate Cancer: Quantitative Multiparametric MR Imaging Models Developed Using Registered Correlative Histopathology.

    PubMed

    Metzger, Gregory J; Kalavagunta, Chaitanya; Spilseth, Benjamin; Bolan, Patrick J; Li, Xiufeng; Hutter, Diane; Nam, Jung W; Johnson, Andrew D; Henriksen, Jonathan C; Moench, Laura; Konety, Badrinath; Warlick, Christopher A; Schmechel, Stephen C; Koopmeiners, Joseph S

    2016-06-01

    Purpose To develop multiparametric magnetic resonance (MR) imaging models to generate a quantitative, user-independent, voxel-wise composite biomarker score (CBS) for detection of prostate cancer by using coregistered correlative histopathologic results, and to compare performance of CBS-based detection with that of single quantitative MR imaging parameters. Materials and Methods Institutional review board approval and informed consent were obtained. Patients with a diagnosis of prostate cancer underwent multiparametric MR imaging before surgery for treatment. All MR imaging voxels in the prostate were classified as cancer or noncancer on the basis of coregistered histopathologic data. Predictive models were developed by using more than one quantitative MR imaging parameter to generate CBS maps. Model development and evaluation of quantitative MR imaging parameters and CBS were performed separately for the peripheral zone and the whole gland. Model accuracy was evaluated by using the area under the receiver operating characteristic curve (AUC), and confidence intervals were calculated with the bootstrap procedure. The improvement in classification accuracy was evaluated by comparing the AUC for the multiparametric model and the single best-performing quantitative MR imaging parameter at the individual level and in aggregate. Results Quantitative T2, apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), reflux rate constant (kep), and area under the gadolinium concentration curve at 90 seconds (AUGC90) were significantly different between cancer and noncancer voxels (P < .001), with ADC showing the best accuracy (peripheral zone AUC, 0.82; whole gland AUC, 0.74). Four-parameter models demonstrated the best performance in both the peripheral zone (AUC, 0.85; P = .010 vs ADC alone) and whole gland (AUC, 0.77; P = .043 vs ADC alone). Individual-level analysis showed statistically significant improvement in AUC in 82% (23 of 28) and 71% (24 of 34

  7. Comparative study of two protocols for quantitative image-analysis of serotonin transporter clustering in lymphocytes, a putative biomarker of therapeutic efficacy in major depression.

    PubMed

    Romay-Tallon, Raquel; Rivera-Baltanas, Tania; Allen, Josh; Olivares, Jose M; Kalynchuk, Lisa E; Caruncho, Hector J

    2017-01-01

    The pattern of serotonin transporter clustering on the plasma membrane of lymphocytes extracted from human whole blood samples has been identified as a putative biomarker of therapeutic efficacy in major depression. Here we evaluated the possibility of performing a similar analysis using blood smears obtained from rats, and from control human subjects and depression patients. We hypothesized that we could optimize a protocol to make the analysis of serotonin protein clustering in blood smears comparable to the analysis of serotonin protein clustering using isolated lymphocytes. Our data indicate that blood smears require a longer fixation time and longer times of incubation with primary and secondary antibodies. In addition, one needs to optimize the image analysis settings for the analysis of smears. When these steps are followed, the quantitative analysis of both the number and size of serotonin transporter clusters on the plasma membrane of lymphocytes is similar using both blood smears and isolated lymphocytes. The development of this novel protocol will greatly facilitate the collection of appropriate samples by eliminating the necessity and cost of specialized personnel for drawing blood samples, and by being a less invasive procedure. Therefore, this protocol will help us advance the validation of membrane protein clustering in lymphocytes as a biomarker of therapeutic efficacy in major depression, and bring it closer to its clinical application.

  8. Quantitative imaging methods in osteoporosis.

    PubMed

    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.

  9. Adjacent slice prostate cancer prediction to inform MALDI imaging biomarker analysis

    NASA Astrophysics Data System (ADS)

    Chuang, Shao-Hui; Sun, Xiaoyan; Cazares, Lisa; Nyalwidhe, Julius; Troyer, Dean; Semmes, O. John; Li, Jiang; McKenzie, Frederic D.

    2010-03-01

    Prostate cancer is the second most common type of cancer among men in US [1]. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. Proteomic biomarkers can improve upon these methods. MALDI molecular spectra imaging is used to visualize protein/peptide concentrations across biopsy samples to search for biomarker candidates. Unfortunately, traditional processing methods require histopathological examination on one slice of a biopsy sample while the adjacent slice is subjected to the tissue destroying desorption and ionization processes of MALDI. The highest confidence tumor regions gained from the histopathological analysis are then mapped to the MALDI spectra data to estimate the regions for biomarker identification from the MALDI imaging. This paper describes a process to provide a significantly better estimate of the cancer tumor to be mapped onto the MALDI imaging spectra coordinates using the high confidence region to predict the true area of the tumor on the adjacent MALDI imaged slice.

  10. Epitope mapping and targeted quantitation of the cardiac biomarker troponin by SID-MRM mass spectrometry.

    PubMed

    Zhao, Cheng; Trudeau, Beth; Xie, Helen; Prostko, John; Fishpaugh, Jeffrey; Ramsay, Carol

    2014-06-01

    The absolute quantitation of the targeted protein using MS provides a promising method to evaluate/verify biomarkers used in clinical diagnostics. In this study, a cardiac biomarker, troponin I (TnI), was used as a model protein for method development. The epitope peptide of TnI was characterized by epitope excision followed with LC/MS/MS method and acted as the surrogate peptide for the targeted protein quantitation. The MRM-based MS assay using a stable internal standard that improved the selectivity, specificity, and sensitivity of the protein quantitation. Also, plasma albumin depletion and affinity enrichment of TnI by anti-TnI mAb-coated microparticles reduced the sample complexity, enhanced the dynamic range, and further improved the detecting sensitivity of the targeted protein in the biological matrix. Therefore, quantitation of TnI, a low abundant protein in human plasma, has demonstrated the applicability of the targeted protein quantitation strategy through its epitope peptide determined by epitope mapping method. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Quantitative fluorescence in intracranial tumor: implications for ALA-induced PpIX as an intraoperative biomarker

    PubMed Central

    Valdés, Pablo A.; Leblond, Frederic; Kim, Anthony; Harris, Brent T.; Wilson, Brian C.; Fan, Xiaoyao; Tosteson, Tor D.; Hartov, Alex; Ji, Songbai; Erkmen, Kadir; Simmons, Nathan E.; Paulsen, Keith D.; Roberts, David W.

    2011-01-01

    Object Accurate discrimination between tumor and normal tissue is crucial for optimal tumor resection. Qualitative fluorescence of protoporphyrin IX (PpIX), synthesized endogenously following δ-aminolevulinic acid (ALA) administration, has been used for this purpose in high-grade glioma (HGG). The authors show that diagnostically significant but visually imperceptible concentrations of PpIX can be quantitatively measured in vivo and used to discriminate normal from neoplastic brain tissue across a range of tumor histologies. Methods The authors studied 14 patients with diagnoses of low-grade glioma (LGG), HGG, meningioma, and metastasis under an institutional review board–approved protocol for fluorescence-guided resection. The primary aim of the study was to compare the diagnostic capabilities of a highly sensitive, spectrally resolved quantitative fluorescence approach to conventional fluorescence imaging for detection of neoplastic tissue in vivo. Results A significant difference in the quantitative measurements of PpIX concentration occurred in all tumor groups compared with normal brain tissue. Receiver operating characteristic (ROC) curve analysis of PpIX concentration as a diagnostic variable for detection of neoplastic tissue yielded a classification efficiency of 87% (AUC = 0.95, specificity = 92%, sensitivity = 84%) compared with 66% (AUC = 0.73, specificity = 100%, sensitivity = 47%) for conventional fluorescence imaging (p < 0.0001). More than 81% (57 of 70) of the quantitative fluorescence measurements that were below the threshold of the surgeon's visual perception were classified correctly in an analysis of all tumors. Conclusions These findings are clinically profound because they demonstrate that ALA-induced PpIX is a targeting biomarker for a variety of intracranial tumors beyond HGGs. This study is the first to measure quantitative ALA-induced PpIX concentrations in vivo, and the results have broad implications for guidance during resection of

  12. Automated analysis of immunohistochemistry images identifies candidate location biomarkers for cancers.

    PubMed

    Kumar, Aparna; Rao, Arvind; Bhavani, Santosh; Newberg, Justin Y; Murphy, Robert F

    2014-12-23

    Molecular biomarkers are changes measured in biological samples that reflect disease states. Such markers can help clinicians identify types of cancer or stages of progression, and they can guide in tailoring specific therapies. Many efforts to identify biomarkers consider genes that mutate between normal and cancerous tissues or changes in protein or RNA expression levels. Here we define location biomarkers, proteins that undergo changes in subcellular location that are indicative of disease. To discover such biomarkers, we have developed an automated pipeline to compare the subcellular location of proteins between two sets of immunohistochemistry images. We used the pipeline to compare images of healthy and tumor tissue from the Human Protein Atlas, ranking hundreds of proteins in breast, liver, prostate, and bladder based on how much their location was estimated to have changed. The performance of the system was evaluated by determining whether proteins previously known to change location in tumors were ranked highly. We present a number of candidate location biomarkers for each tissue, and identify biochemical pathways that are enriched in proteins that change location. The analysis technology is anticipated to be useful not only for discovering new location biomarkers but also for enabling automated analysis of biomarker distributions as an aid to determining diagnosis.

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

    PubMed

    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

  14. Integrating Soluble Biomarkers and Imaging Technologies in the Identification of Vulnerable Atherosclerotic Patients

    PubMed Central

    Páramo, José A.; Rodríguez JA, José A.; Orbe, Josune

    2006-01-01

    The clinical utility of a biomarker depends on its ability to identify high-risk individuals to optimally manage the patient. A new biomarker would be of clinical value if it is accurate and reliable, provides good sensitivity and specificity, and is available for widespread application. Data are accumulating on the potential clinical utility of integrating imaging technologies and circulating biomarkers for the identification of vulnerable (high-risk) cardiovascular patients. A multi-biomarker strategy consisting of markers of inflammation, hemostasis and thrombosis, proteolysis and oxidative stress, combined with new imaging modalities (optical coherence tomography, virtual histology plus IVUS, PET) can increase our ability to identify such thombosis-prone patients. In an ideal scenario, cardiovascular biomarkers and imaging combined will provide a better diagnostic tool to identify high-risk individuals and also more efficient methods for effective therapies to reduce such cardiovascular risk. However, additional studies are required in order to show that this approach can contribute to improved diagnostic and therapeutic of atherosclerotic disease. PMID:19690647

  15. Integrating soluble biomarkers and imaging technologies in the identification of vulnerable atherosclerotic patients.

    PubMed

    Páramo, José A; Rodríguez Ja, José A; Orbe, Josune

    2007-02-07

    The clinical utility of a biomarker depends on its ability to identify high-risk individuals to optimally manage the patient. A new biomarker would be of clinical value if it is accurate and reliable, provides good sensitivity and specificity, and is available for widespread application. Data are accumulating on the potential clinical utility of integrating imaging technologies and circulating biomarkers for the identification of vulnerable (high-risk) cardiovascular patients. A multi-biomarker strategy consisting of markers of inflammation, hemostasis and thrombosis, proteolysis and oxidative stress, combined with new imaging modalities (optical coherence tomography, virtual histology plus IVUS, PET) can increase our ability to identify such thombosis-prone patients. In an ideal scenario, cardiovascular biomarkers and imaging combined will provide a better diagnostic tool to identify high-risk individuals and also more efficient methods for effective therapies to reduce such cardiovascular risk. However, additional studies are required in order to show that this approach can contribute to improved diagnostic and therapeutic of atherosclerotic disease.

  16. Updating the OMERACT Filter: Implications for imaging and soluble biomarkers

    PubMed Central

    D’Agostino, Maria-Antonietta; Boers, Maarten; Kirwan, John; van der Heijde, Desirée; Østergaard, Mikkel; Schett, Georg; Landewé, Robert B.M.; Maksymowych, Walter P.; Naredo, Esperanza; Dougados, Maxime; Iagnocco, Annamaria; Bingham, Clifton O.; Brooks, Peter; Beaton, Dorcas; Gandjbakhch, Frederique; Gossec, Laure; Guillemin, Francis; Hewlett, Sarah; Kloppenburg, Margreet; March, Lyn; Mease, Philip J; Moller, Ingrid; Simon, Lee S; Singh, Jasvinder A; Strand, Vibeke; Wakefield, Richard J; Wells, George; Tugwell, Peter; Conaghan, Philip G

    2014-01-01

    Objective The OMERACT Filter provides a framework for the validation of outcome measures for use in rheumatology clinical research. However, imaging and biochemical measures may face additional validation challenges due to their technical nature. The Imaging and Soluble Biomarker Session at OMERACT 11 aimed to provide a guide for the iterative development of an imaging or biochemical measurement instrument so it can be used in therapeutic assessment. Methods A hierarchical structure was proposed, reflecting 3 dimensions needed for validating an imaging or biochemical measurement instrument: outcome domain(s), study setting and performance of the instrument. Movement along the axes in any dimension reflects increasing validation. For a given test instrument, the 3-axis structure assesses the extent to which the instrument is a validated measure for the chosen domain, whether it assesses a patient or disease centred-variable, and whether its technical performance is adequate in the context of its application. Some currently used imaging and soluble biomarkers for rheumatoid arthritis, spondyloarthritis and knee osteoarthritis were then evaluated using the original OMERACT filter and the newly proposed structure. Break-out groups critically reviewed the extent to which the candidate biomarkers complied with the proposed step-wise approach, as a way of examining the utility of the proposed 3 dimensional structure. Results Although there was a broad acceptance of the value of the proposed structure in general, some areas for improvement were suggested including clarification of criteria for achieving a certain level of validation and how to deal with extension of the structure to areas beyond clinical trials. Conclusion General support was obtained for a proposed tri-axis structure to assess validation of imaging and soluble biomarkers; nevertheless, additional work is required to better evaluate its place within the OMERACT Filter 2.0. PMID:24584916

  17. Updating the OMERACT filter: implications for imaging and soluble biomarkers.

    PubMed

    D'Agostino, Maria-Antonietta; Boers, Maarten; Kirwan, John; van der Heijde, Désirée; Østergaard, Mikkel; Schett, Georg; Landewé, Robert B; Maksymowych, Walter P; Naredo, Esperanza; Dougados, Maxime; Iagnocco, Annamaria; Bingham, Clifton O; Brooks, Peter M; Beaton, Dorcas E; Gandjbakhch, Frederique; Gossec, Laure; Guillemin, Francis; Hewlett, Sarah E; Kloppenburg, Margreet; March, Lyn; Mease, Philip J; Moller, Ingrid; Simon, Lee S; Singh, Jasvinder A; Strand, Vibeke; Wakefield, Richard J; Wells, George A; Tugwell, Peter; Conaghan, Philip G

    2014-05-01

    The Outcome Measures in Rheumatology (OMERACT) Filter provides a framework for the validation of outcome measures for use in rheumatology clinical research. However, imaging and biochemical measures may face additional validation challenges because of their technical nature. The Imaging and Soluble Biomarker Session at OMERACT 11 aimed to provide a guide for the iterative development of an imaging or biochemical measurement instrument so it can be used in therapeutic assessment. A hierarchical structure was proposed, reflecting 3 dimensions needed for validating an imaging or biochemical measurement instrument: outcome domain(s), study setting, and performance of the instrument. Movement along the axes in any dimension reflects increasing validation. For a given test instrument, the 3-axis structure assesses the extent to which the instrument is a validated measure for the chosen domain, whether it assesses a patient-centered or disease-centered variable, and whether its technical performance is adequate in the context of its application. Some currently used imaging and soluble biomarkers for rheumatoid arthritis, spondyloarthritis, and knee osteoarthritis were then evaluated using the original OMERACT Filter and the newly proposed structure. Breakout groups critically reviewed the extent to which the candidate biomarkers complied with the proposed stepwise approach, as a way of examining the utility of the proposed 3-dimensional structure. Although there was a broad acceptance of the value of the proposed structure in general, some areas for improvement were suggested including clarification of criteria for achieving a certain level of validation and how to deal with extension of the structure to areas beyond clinical trials. General support was obtained for a proposed tri-axis structure to assess validation of imaging and soluble biomarkers; nevertheless, additional work is required to better evaluate its place within the OMERACT Filter 2.0.

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

    PubMed

    Oberg, Kjell; Krenning, Eric; Sundin, Anders; Bodei, Lisa; Kidd, Mark; Tesselaar, Margot; Ambrosini, Valentina; Baum, Richard P; Kulke, Matthew; Pavel, Marianne; Cwikla, Jaroslaw; Drozdov, Ignat; Falconi, Massimo; Fazio, Nicola; Frilling, Andrea; Jensen, Robert; Koopmans, Klaus; Korse, Tiny; Kwekkeboom, Dik; Maecke, Helmut; Paganelli, Giovanni; Salazar, Ramon; Severi, Stefano; Strosberg, Jonathan; Prasad, Vikas; Scarpa, Aldo; Grossman, Ashley; Walenkamp, Annemeik; Cives, Mauro; Virgolini, Irene; Kjaer, Andreas; Modlin, Irvin M

    2016-09-01

    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. © 2016 The authors.

  19. The Role of High-resolution Peripheral Quantitative Computed Tomography as a Biomarker for Joint Damage in Inflammatory Arthritis.

    PubMed

    Tam, Lai-Shan

    2016-10-01

    Since 2011, members of the SPECTRA Collaboration (Study grouP for xtrEme-Computed Tomography in Rheumatoid Arthritis) have investigated the validity, reliability, and responsiveness of high-resolution peripheral quantitative computed tomography (HR-pQCT) as a biomarker for joint damage in inflammatory arthritis. Presented in this series of articles are a systematic review of HR-pQCT-related findings to date, a review of selected images of cortical and subchondral trabecular bone of metacarpophalangeal (MCP) joints, results of a consensus process to standardize the definition of erosions and their quantification, as well as an examination of the effect of joint flexion on width and volume assessment of the joint space.

  20. Quantitation of spatially-localized proteins in tissue samples using MALDI-MRM imaging.

    PubMed

    Clemis, Elizabeth J; Smith, Derek S; Camenzind, Alexander G; Danell, Ryan M; Parker, Carol E; Borchers, Christoph H

    2012-04-17

    MALDI imaging allows the creation of a "molecular image" of a tissue slice. This image is reconstructed from the ion abundances in spectra obtained while rastering the laser over the tissue. These images can then be correlated with tissue histology to detect potential biomarkers of, for example, aberrant cell types. MALDI, however, is known to have problems with ion suppression, making it difficult to correlate measured ion abundance with concentration. It would be advantageous to have a method which could provide more accurate protein concentration measurements, particularly for screening applications or for precise comparisons between samples. In this paper, we report the development of a novel MALDI imaging method for the localization and accurate quantitation of proteins in tissues. This method involves optimization of in situ tryptic digestion, followed by reproducible and uniform deposition of an isotopically labeled standard peptide from a target protein onto the tissue, using an aerosol-generating device. Data is acquired by MALDI multiple reaction monitoring (MRM) mass spectrometry (MS), and accurate peptide quantitation is determined from the ratio of MRM transitions for the endogenous unlabeled proteolytic peptides to the corresponding transitions from the applied isotopically labeled standard peptides. In a parallel experiment, the quantity of the labeled peptide applied to the tissue was determined using a standard curve generated from MALDI time-of-flight (TOF) MS data. This external calibration curve was then used to determine the quantity of endogenous peptide in a given area. All standard curves generate by this method had coefficients of determination greater than 0.97. These proof-of-concept experiments using MALDI MRM-based imaging show the feasibility for the precise and accurate quantitation of tissue protein concentrations over 2 orders of magnitude, while maintaining the spatial localization information for the proteins.

  1. Mechanism and non-mechanism based imaging biomarkers for assessing biological response to treatment in non-small cell lung cancer.

    PubMed

    Weller, A; O'Brien, M E R; Ahmed, M; Popat, S; Bhosle, J; McDonald, F; Yap, T A; Du, Y; Vlahos, I; deSouza, N M

    2016-05-01

    Therapeutic options in locally advanced non-small cell lung cancer (NSCLC) have expanded in the past decade to include a palate of targeted interventions such as high dose targeted thermal ablations, radiotherapy and growing platform of antibody and small molecule therapies and immunotherapies. Although these therapies have varied mechanisms of action, they often induce changes in tumour architecture and microenvironment such that response is not always accompanied by early reduction in tumour mass, and evaluation by criteria other than size is needed to report more effectively on response. Functional imaging techniques, which probe the tumour and its microenvironment through novel positron emission tomography and magnetic resonance imaging techniques, offer more detailed insights into and quantitation of tumour response than is available on anatomical imaging alone. Use of these biomarkers, or other rational combinations as readouts of pathological response in NSCLC have potential to provide more accurate predictors of treatment outcomes. In this article, the robustness of the more commonly available positron emission tomography and magnetic resonance imaging biomarker indices is examined and the evidence for their application in NSCLC is reviewed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Advances in multiplexed MRM-based protein biomarker quantitation toward clinical utility.

    PubMed

    Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Hardie, Darryl B; Borchers, Christoph H

    2014-05-01

    Accurate and rapid protein quantitation is essential for screening biomarkers for disease stratification and monitoring, and to validate the hundreds of putative markers in human biofluids, including blood plasma. An analytical method that utilizes stable isotope-labeled standard (SIS) peptides and selected/multiple reaction monitoring-mass spectrometry (SRM/MRM-MS) has emerged as a promising technique for determining protein concentrations. This targeted approach has analytical merit, but its true potential (in terms of sensitivity and multiplexing) has yet to be realized. Described herein is a method that extends the multiplexing ability of the MRM method to enable the quantitation 142 high-to-moderate abundance proteins (from 31mg/mL to 44ng/mL) in undepleted and non-enriched human plasma in a single run. The proteins have been reported to be associated to a wide variety of non-communicable diseases (NCDs), from cardiovascular disease (CVD) to diabetes. The concentrations of these proteins in human plasma are inferred from interference-free peptides functioning as molecular surrogates (2 peptides per protein, on average). A revised data analysis strategy, involving the linear regression equation of normal control plasma, has been instituted to enable the facile application to patient samples, as demonstrated in separate nutrigenomics and CVD studies. The exceptional robustness of the LC/MS platform and the quantitative method, as well as its high throughput, makes the assay suitable for application to patient samples for the verification of a condensed or complete protein panel. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

  3. Biomarkers and Imaging Findings of Anderson–Fabry Disease—What We Know Now

    PubMed Central

    Beirão, Idalina; Cabrita, Ana; Torres, Márcia; Silva, Fernando; Aguiar, Patrício; Laranjeira, Francisco; Gomes, Ana Marta

    2017-01-01

    Anderson–Fabry disease (AFD) is an X-linked lysosomal storage disorder, caused by deficiency or absence of the alpha-galactosidase A activity, with a consequent glycosphingolipid accumulation. Biomarkers and imaging findings may be useful for diagnosis, identification of an organ involvement, therapy monitoring and prognosis. The aim of this article is to review the current available literature on biomarkers and imaging findings of AFD patients. An extensive bibliographic review from PubMed, Medline and Clinical Key databases was performed by a group of experts from nephrology, neurology, genetics, cardiology and internal medicine, aiming for consensus. Lyso-GB3 is a valuable biomarker to establish the diagnosis. Proteinuria and creatinine are the most valuable to detect renal damage. Troponin I and high-sensitivity assays for cardiac troponin T can identify patients with cardiac lesions, but new techniques of cardiac imaging are essential to detect incipient damage. Specific cerebrovascular imaging findings are present in AFD patients. Techniques as metabolomics and proteomics have been developed in order to find an AFD fingerprint. Lyso-GB3 is important for evaluating the pathogenic mutations and monitoring the response to treatment. Many biomarkers can detect renal, cardiac and cerebrovascular involvement, but none of these have proved to be important to monitoring the response to treatment. Imaging features are preferred in order to find cardiac and cerebrovascular compromise in AFD patients. PMID:28933368

  4. Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells

    DOE PAGES

    Yurkovich, James T.; Yang, Laurence; Palsson, Bernhard O.; ...

    2017-03-06

    Deep-coverage metabolomic profiling has revealed a well-defined development of metabolic decay in human red blood cells (RBCs) under cold storage conditions. A set of extracellular biomarkers has been recently identified that reliably defines the qualitative state of the metabolic network throughout this metabolic decay process. Here, we extend the utility of these biomarkers by using them to quantitatively predict the concentrations of other metabolites in the red blood cell. We are able to accurately predict the concentration profile of 84 of the 91 (92%) measured metabolites ( p < 0.05) in RBC metabolism using only measurements of these five biomarkers.more » The median of prediction errors (symmetric mean absolute percent error) across all metabolites was 13%. Furthermore, the ability to predict numerous metabolite concentrations from a simple set of biomarkers offers the potential for the development of a powerful workflow that could be used to evaluate the metabolic state of a biological system using a minimal set of measurements.« less

  5. Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yurkovich, James T.; Yang, Laurence; Palsson, Bernhard O.

    Deep-coverage metabolomic profiling has revealed a well-defined development of metabolic decay in human red blood cells (RBCs) under cold storage conditions. A set of extracellular biomarkers has been recently identified that reliably defines the qualitative state of the metabolic network throughout this metabolic decay process. Here, we extend the utility of these biomarkers by using them to quantitatively predict the concentrations of other metabolites in the red blood cell. We are able to accurately predict the concentration profile of 84 of the 91 (92%) measured metabolites ( p < 0.05) in RBC metabolism using only measurements of these five biomarkers.more » The median of prediction errors (symmetric mean absolute percent error) across all metabolites was 13%. Furthermore, the ability to predict numerous metabolite concentrations from a simple set of biomarkers offers the potential for the development of a powerful workflow that could be used to evaluate the metabolic state of a biological system using a minimal set of measurements.« less

  6. How Imaging Can Impact Clinical Trial Design: Molecular Imaging as a Biomarker for Targeted Cancer Therapy.

    PubMed

    Mankoff, David A; Farwell, Michael D; Clark, Amy S; Pryma, Daniel A

    2015-01-01

    The ability to measure biochemical and molecular processes to guide cancer treatment represents a potentially powerful tool for trials of targeted cancer therapy. These assays have traditionally been performed by analysis of tissue samples. However, more recently, functional and molecular imaging has been developed that is capable of in vivo assays of cancer biochemistry and molecular biology and is highly complementary to tissue-based assays. Cancer imaging biomarkers can play a key role in increasing the efficacy and efficiency of therapeutic clinical trials and also provide insight into the biologic mechanisms that bring about a therapeutic response. Future progress will depend on close collaboration between imaging scientists and cancer physicians and on public and commercial sponsors, to take full advantage of what imaging has to offer for clinical trials of targeted cancer therapy. This review will provide examples of how molecular imaging can inform targeted cancer clinical trials and clinical decision making by (1) measuring regional expression of the therapeutic target, (2) assessing early (pharmacodynamic) response to treatment, and (3) predicting therapeutic outcome. The review includes a discussion of basic principles of molecular imaging biomarkers in cancer, with an emphasis on those methods that have been tested in patients. We then review clinical trials designed to evaluate imaging tests as integrated markers embedded in a therapeutic clinical trial with the goal of validating the imaging tests as integral markers that can aid patient selection and direct response-adapted treatment strategies. Examples of recently completed multicenter trials using imaging biomarkers are highlighted.

  7. Quantitative biomarkers of colonic dysplasia based on intrinsic second-harmonic generation signal

    NASA Astrophysics Data System (ADS)

    Zhuo, Shuangmu; Zhu, Xiaoqin; Wu, Guizhu; Chen, Jianxin; Xie, Shusen

    2011-12-01

    Most colorectal cancers arise from dysplastic lesions, such as adenomatous polyps, and these lesions are difficult to be detected by the current endoscopic screening approaches. Here, we present the use of an intrinsic second-harmonic generation (SHG) signal as a novel means to differentiate between normal and dysplastic human colonic tissues. We find that the SHG signal can quantitatively identify collagen change associated with colonic dysplasia that is indiscernible by conventional pathologic techniques. By comparing normal with dysplastic mucosa, there were significant differences in collagen density and collagen fiber direction, providing substantial potential to become quantitative intrinsic biomarkers for in vivo clinical diagnosis of colonic dysplasia.

  8. Consortium for Imaging and Biomarkers (CIB) Created: Eight Grants Awarded | Division of Cancer Prevention

    Cancer.gov

    The NCI Division of Cancer Prevention awarded eight grants to create the Consortium for Imaging and Biomarkers (CIB) on August 3, 2015. | 8 lead investigators combining imaging methods for the visualization of lesions with biomarkers to improve the accuracy of screening, early cancer detection, and the diagnosis of early stage cancers.

  9. Protocol for Biomarker Ratio Imaging Microscopy with Specific Application to Ductal Carcinoma In situ of the Breast

    PubMed Central

    Clark, Andrea J.; Petty, Howard R.

    2016-01-01

    This protocol describes the methods and steps involved in performing biomarker ratio imaging microscopy (BRIM) using formalin fixed paraffin-embedded (FFPE) samples of human breast tissue. The technique is based on the acquisition of two fluorescence images of the same microscopic field using two biomarkers and immunohistochemical tools. The biomarkers are selected such that one biomarker correlates with breast cancer aggressiveness while the second biomarker anti-correlates with aggressiveness. When the former image is divided by the latter image, a computed ratio image is formed that reflects the aggressiveness of tumor cells while increasing contrast and eliminating path-length and other artifacts from the image. For example, the aggressiveness of epithelial cells may be assessed by computing ratio images of N-cadherin and E-cadherin images or CD44 and CD24 images, which specifically reflect the mesenchymal or stem cell nature of the constituent cells, respectively. This methodology is illustrated for tissue samples of ductal carcinoma in situ (DCIS) and invasive breast cancer. This tool should be useful in tissue studies of experimental cancer as well as the management of cancer patients. PMID:27857940

  10. The use of immunohistochemistry for biomarker assessment--can it compete with other technologies?

    PubMed

    Dunstan, Robert W; Wharton, Keith A; Quigley, Catherine; Lowe, Amanda

    2011-10-01

    A morphology-based assay such as immunohistochemistry (IHC) should be a highly effective means to define the expression of a target molecule of interest, especially if the target is a protein. However, over the past decade, IHC as a platform for biomarkers has been challenged by more quantitative molecular assays with reference standards but that lack morphologic context. For IHC to be considered a "top-tier" biomarker assay, it must provide truly quantitative data on par with non-morphologic assays, which means it needs to be run with reference standards. However, creating such standards for IHC will require optimizing all aspects of tissue collection, fixation, section thickness, morphologic criteria for assessment, staining processes, digitization of images, and image analysis. This will also require anatomic pathology to evolve from a discipline that is descriptive to one that is quantitative. A major step in this transformation will be replacing traditional ocular microscopes with computer monitors and whole slide images, for without digitization, there can be no accurate quantitation; without quantitation, there can be no standardization; and without standardization, the value of morphology-based IHC assays will not be realized.

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

    NASA Astrophysics Data System (ADS)

    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.

  12. Bone metabolism in oxalosis: a single-center study using new imaging techniques and biomarkers.

    PubMed

    Bacchetta, Justine; Fargue, Sonia; Boutroy, Stéphanie; Basmaison, Odile; Vilayphiou, Nicolas; Plotton, Ingrid; Guebre-Egziabher, Fitsum; Dohin, Bruno; Kohler, Rémi; Cochat, Pierre

    2010-06-01

    The deposition of calcium oxalate crystals in the kidney and bone is a hallmark of primary hyperoxaluria type 1 (PH1). We report here an evaluation of the bone status of 12 PH1 children based on bone biomarkers [parathyroid hormone, vitamin D, fibroblast growth factor 23 (FGF23)] and radiological assessments (skeletal age, three-dimensional high-resolution peripheral quantitative computed tomography, HR-pQCT) carried out within the framework of a cross-sectional single-center study. The controls consisted of healthy and children with chronic kidney disease already enrolled in local bone and mineral metabolism studies. The mean age (+ or - standard deviation) age of the patients was 99 (+ or - 63) months. Six children suffered from fracture. Bone maturation was accelerated in five patients, four of whom were <5 years. The combination of new imaging techniques and biomarkers highlighted new and unexplained features of PH1: advanced skeletal age in young PH1 patients, increased FGF23 levels and decreased total volumetric bone mineral density with bone microarchitecture alteration.

  13. T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model.

    PubMed

    Whittaker, Heather T; Zhu, Shenghua; Di Curzio, Domenico L; Buist, Richard; Li, Xin-Min; Noy, Suzanna; Wiseman, Frances K; Thiessen, Jonathan D; Martin, Melanie

    2018-07-01

    Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T 1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T 1 -weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD. Copyright © 2018. Published by Elsevier Inc.

  14. Biomarker-guided translation of brain imaging into disease pathway models

    PubMed Central

    Younesi, Erfan; Hofmann-Apitius, Martin

    2013-01-01

    The advent of state-of-the-art brain imaging technologies in recent years and the ability of such technologies to provide high-resolution information at both structural and functional levels has spawned large efforts to introduce novel non-invasive imaging biomarkers for early prediction and diagnosis of brain disorders; however, their utility in both clinic and drug development at their best resolution remains limited to visualizing and monitoring disease progression. Given the fact that efficient translation of valuable information embedded in brain scans into clinical application is of paramount scientific and public health importance, a strategy is needed to bridge the current gap between imaging and molecular biology, particularly in neurodegenerative diseases. As an attempt to address this issue, we present a novel computational method to link readouts of imaging biomarkers to their underlying molecular pathways with the aim of guiding clinical diagnosis, prognosis and even target identification in drug discovery for Alzheimer's disease. PMID:24287435

  15. Imaging biomarker roadmap for cancer studies

    PubMed Central

    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, John 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; Sullivan, Daniel C.; Taylor, Stuart A.; Tofts, Paul S.; Tozer, Gillian M.; van Herk, Marcel; Walker-Samuel, Simon; Wason, James; Williams, Kaye J.; Workman, Paul; Yankeelov, Thomas E.; Brindle, Kevin M.; McShane, Lisa M.; Jackson, Alan; Waterton, John C.

    2017-01-01

    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 drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing ‘translational gaps’ through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored ‘roadmap’. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use. PMID:27725679

  16. Genomic biomarkers for molecular imaging: predicting the future.

    PubMed

    Thakur, Mathew L

    2009-07-01

    Over the past few decades, great strides have been made in anatomical imaging of disease that has led to their diagnosis with minimal invasion. Despite these advances, diseases such as cancer continue to take one human life every minute in the United States. Complimentary approaches that pertain directly to the genesis of the disease might contribute to its early diagnosis and subsequent management. In cancer, an array of molecular abnormalities leading to the modulations in expression of key proteins important in the cellular signaling pathways and cell proliferation has been identified. These specific disease fingerprints, biomarkers, are overexpressed on malignant cell surfaces or within the cytoplasm, and they provide unique targets that are promising for improving cancer diagnosis and therapy. We and others have designed, synthesized, and evaluated some novel probes specific for those oncogenes and oncogene product biomarkers for PET and SPECT molecular imaging of certain types of cancers. This article briefly describes this approach and gives specific examples that depict the ability of molecular imaging to detect occult lesions not detectable by current scintigraphic approaches. The article also outlines a few examples predicting other possible applications of targeting such specific probes not yet used.

  17. Toward Quantitative Small Animal Pinhole SPECT: Assessment of Quantitation Accuracy Prior to Image Compensations

    PubMed Central

    Chen, Chia-Lin; Wang, Yuchuan; Lee, Jason J. S.; Tsui, Benjamin M. W.

    2011-01-01

    Purpose We assessed the quantitation accuracy of small animal pinhole single photon emission computed tomography (SPECT) under the current preclinical settings, where image compensations are not routinely applied. Procedures The effects of several common image-degrading factors and imaging parameters on quantitation accuracy were evaluated using Monte-Carlo simulation methods. Typical preclinical imaging configurations were modeled, and quantitative analyses were performed based on image reconstructions without compensating for attenuation, scatter, and limited system resolution. Results Using mouse-sized phantom studies as examples, attenuation effects alone degraded quantitation accuracy by up to −18% (Tc-99m or In-111) or −41% (I-125). The inclusion of scatter effects changed the above numbers to −12% (Tc-99m or In-111) and −21% (I-125), respectively, indicating the significance of scatter in quantitative I-125 imaging. Region-of-interest (ROI) definitions have greater impacts on regional quantitation accuracy for small sphere sources as compared to attenuation and scatter effects. For the same ROI, SPECT acquisitions using pinhole apertures of different sizes could significantly affect the outcome, whereas the use of different radii-of-rotation yielded negligible differences in quantitation accuracy for the imaging configurations simulated. Conclusions We have systematically quantified the influence of several factors affecting the quantitation accuracy of small animal pinhole SPECT. In order to consistently achieve accurate quantitation within 5% of the truth, comprehensive image compensation methods are needed. PMID:19048346

  18. Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique

    PubMed Central

    Xu, Jingwen; Zhang, Shijun; Jiang, Haiqiang; Wang, Nan; Lin, Haiqing

    2017-01-01

    Tengfu Jiangya Tablet (TJT) is a well accepted antihypertension drug in China and its major active components were Uncaria total alkaloids and Semen Raphani soluble alkaloid. To further explore treatment effects mechanism of TJT on essential hypertension, a serum proteomic study was performed. Potential biomarkers were quantified in serum of hypertension individuals before and after taking TJT with isobaric tags for relative and absolute quantitation (iTRAQ) coupled two-dimensional liquid chromatography followed electrospray ionization-tandem mass spectrometry (2D LC-MS/MS) proteomics technique. Among 391 identified proteins with high confidence, 70 proteins were differentially expressed (fold variation criteria, >1.2 or <0.83) between two groups (39 upregulated and 31 downregulated). Combining with Gene Ontology annotation, KEGG pathway analysis, and literature retrieval, 5 proteins were chosen as key target biomarkers during TJT therapeutic process. And the alteration profiles of these 5 proteins were verified by ELISA and Western Blot. Proteins Kininogen 1 and Keratin 1 are members of Kallikrein system, while Myeloperoxidase, Serum Amyloid protein A, and Retinol binding protein 4 had been reported closely related to vascular endothelial injury. Our study discovered 5 target biomarkers of the compound Chinese medicine TJT. Secondly, this research initially revealed the antihypertension therapeutic mechanism of this drug from a brand-new aspect. PMID:28408942

  19. Quantitative fluorescence microscopy and image deconvolution.

    PubMed

    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

  20. Quantitative phase imaging of arthropods

    PubMed Central

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

    2015-01-01

    Abstract. 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. PMID:26334858

  1. Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.

    PubMed

    Chen, Jin-Qiu; Wakefield, Lalage M; Goldstein, David J

    2015-06-06

    There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

  2. Imaging Biomarker Dynamics in an Intracranial Murine Glioma Study of Radiation and Antiangiogenic Therapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chung, Caroline, E-mail: caroline.chung@rmp.uhn.on.ca; Jalali, Shahrzad; Foltz, Warren

    2013-03-01

    Purpose: There is a growing need for noninvasive biomarkers to guide individualized spatiotemporal delivery of radiation therapy (RT) and antiangiogenic (AA) therapy for brain tumors. This study explored early biomarkers of response to RT and the AA agent sunitinib (SU), in a murine intracranial glioma model, using serial magnetic resonance imaging (MRI). Methods and Materials: Mice with MRI-visible tumors were stratified by tumor size into 4 therapy arms: control, RT, SU, and SU plus RT (SURT). Single-fraction conformal RT was delivered using MRI and on-line cone beam computed tomography (CT) guidance. Serial MR images (T2-weighted, diffusion, dynamic contrast-enhanced and gadolinium-enhancedmore » T1-weighted scans) were acquired biweekly to evaluate tumor volume, apparent diffusion coefficient (ADC), and tumor perfusion and permeability responses (K{sub trans}, K{sub ep}). Results: Mice in all treatment arms survived longer than those in control, with a median survival of 35 days for SURT (P<.0001) and 30 days for RT (P=.009) and SU (P=.01) mice vs 26 days for control mice. At Day 3, ADC rise was greater with RT than without (P=.002). Sunitinib treatment reduced tumor perfusion/permeability values with mean K{sub trans} reduction of 27.6% for SU (P=.04) and 26.3% for SURT (P=.04) mice and mean K{sub ep} reduction of 38.1% for SU (P=.01) and 27.3% for SURT (P=.02) mice. The magnitude of individual mouse ADC responses at Days 3 and 7 correlated with subsequent tumor growth rate R values of −0.878 (P=.002) and −0.80 (P=.01), respectively. Conclusions: Early quantitative changes in diffusion and perfusion MRI measures reflect treatment responses soon after starting therapy and thereby raise the potential for these imaging biomarkers to guide adaptive and potentially individualized therapy approaches in the future.« less

  3. 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.

    PubMed

    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 < 0.05). Differences in iodine concentrations between healthy pancreatic tissue and carcinoma were statistically significant for DECT acquisitions corresponding to trigger delays of 15-21 s (p < 0.05). An acquisition window between 15 and 21 s after exceeding bolus tracking threshold shows promising results for acquisition of DECT iodine maps as an 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

  4. Alzheimer's Disease Normative Cerebrospinal Fluid Biomarkers Validated in PET Amyloid-β Characterized Subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study.

    PubMed

    Li, Qiao-Xin; Villemagne, Victor L; Doecke, James D; Rembach, Alan; Sarros, Shannon; Varghese, Shiji; McGlade, Amelia; Laughton, Katrina M; Pertile, Kelly K; Fowler, Christopher J; Rumble, Rebecca L; Trounson, Brett O; Taddei, Kevin; Rainey-Smith, Stephanie R; Laws, Simon M; Robertson, Joanne S; Evered, Lisbeth A; Silbert, Brendan; Ellis, Kathryn A; Rowe, Christopher C; Macaulay, S Lance; Darby, David; Martins, Ralph N; Ames, David; Masters, Colin L; Collins, Steven

    2015-01-01

    The cerebrospinal fluid (CSF) amyloid-β (Aβ)(1-42), total-tau (T-tau), and phosphorylated-tau (P-tau181P) profile has been established as a valuable biomarker for Alzheimer's disease (AD). The current study aimed to determine CSF biomarker cut-points using positron emission tomography (PET) Aβ imaging screened subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, as well as correlate CSF analyte cut-points across a range of PET Aβ amyloid ligands. Aβ pathology was determined by PET imaging, utilizing ¹¹C-Pittsburgh Compound B, ¹⁸F-flutemetamol, or ¹⁸F-florbetapir, in 157 AIBL participants who also underwent CSF collection. Using an INNOTEST assay, cut-points were established (Aβ(1-42) >544 ng/L, T-tau <407 ng/L, and P-tau181P <78 ng/L) employing a rank based method to define a "positive" CSF in the sub-cohort of amyloid-PET negative healthy participants (n = 97), and compared with the presence of PET demonstrated AD pathology. CSF Aβ(1-42) was the strongest individual biomarker, detecting cognitively impaired PET positive mild cognitive impairment (MCI)/AD with 85% sensitivity and 91% specificity. The ratio of P-tau181P or T-tau to Aβ(1-42) provided greater accuracy, predicting MCI/AD with Aβ pathology with ≥92% sensitivity and specificity. Cross-validated accuracy, using all three biomarkers or the ratio of P-tau or T-tau to Aβ(1-42) to predict MCI/AD, reached ≥92% sensitivity and specificity. CSF Aβ(1-42) levels and analyte combination ratios demonstrated very high correlation with PET Aβ imaging. Our study offers additional support for CSF biomarkers in the early and accurate detection of AD pathology, including enrichment of patient cohorts for treatment trials even at the pre-symptomatic stage.

  5. Design of a novel class of protein-based magnetic resonance imaging contrast agents for the molecular imaging of cancer biomarkers

    PubMed Central

    Xue, Shenghui; Qiao, Jingjuan; Pu, Fan; Cameron, Mathew; Yang, Jenny J.

    2014-01-01

    Magnetic resonance imaging (MRI) of disease biomarkers, especially cancer biomarkers, could potentially improve our understanding of the disease and drug activity during preclinical and clinical drug treatment and patient stratification. MRI contrast agents with high relaxivity and targeting capability to tumor biomarkers are highly required. Extensive work has been done to develop MRI contrast agents. However, only a few limited literatures report that protein residues can function as ligands to bind Gd3+ with high binding affinity, selectivity, and relaxivity. In this paper, we focus on reporting our current progress on designing a novel class of protein-based Gd3+ MRI contrast agents (ProCAs) equipped with several desirable capabilities for in vivo application of MRI of tumor biomarkers. We will first discuss our strategy for improving the relaxivity by a novel protein-based design. We then discuss the effect of increased relaxivity of ProCAs on improving the detection limits for MRI contrast agent, especially for in vivo application. We will further report our efforts to improve in vivo imaging capability and our achievement in molecular imaging of cancer biomarkers with potential preclinical and clinical applications. PMID:23335551

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chen, S.

    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 targetmore » 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

  7. Quantitative assessment of the relationship between biomarker content and biomass in marine phytoplankton in responses to temperature and nutrient supply ratio changes

    NASA Astrophysics Data System (ADS)

    Ding, Y.; Chen, X.; Bi, R.; Zhang, L. H.; Li, L.; Zhao, M.

    2016-12-01

    Alkenones and sterols are useful biomarkers to construct past productivity and community structure changes in aquatic environments. Until now, the quantitative relationship between biomarker content and biomass in marine phytoplankton remains understudied, which hinders the quantitative reconstruction of ocean changes. In this study, we carried out laboratory culture experiments to determine the quantitative relationship between biomarker content and biomass under three temperatures (15°, 20° and 25°) and three N:P supply ratios (N:P=10:1, 24:1 and 63:1 mol mol-1) for three common phytoplankton groups, diatoms (Phaeodactylum tricornutum Bohlin, Skeletonema costatum, Chaetoceros muelleri), dinoflagellates (Karenia mikimotoi, Prorocentrum donghaiense, Prorocentrum minimum), and coccolithophores (Emiliania huxleyi). Alkenones were only detected in E. huxleyiand dinosterol was only detected in dinoflagellates, confirming that they are the biomarkers for these two groups of phytoplankton, respectively. Brassicasterol was detected in all three groups of phytoplankton, but its content was higher in diatoms, suggesting that it is still a useful biomarker for diatoms. Cell-normalized alkenone content (pg/cell) increases with increasing growth temperature by up to 30%; while the effect of nutrients on alkenone content is minimum. On the other hand, cell-normalized dinosterol content is not temperature dependent, but it is strongly affected by nutrient ratio changes. The effects of temperature and nutrients on cell-normalized brassicasterol content are phytoplankton dependent. For diatoms, the temperature effect is minimum while the nutrient effect is significant but also varies with temperatures. Our results have strong implications for understanding how different phytoplankton respond to global changes, and for more quantitative reconstruction of past productivity and community structure changes using these biomarkers.

  8. 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.

    PubMed

    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.

  9. Quantitative Imaging in Cancer Clinical Trials

    PubMed Central

    Yankeelov, Thomas E.; Mankoff, David A.; Schwartz, Lawrence H.; Lieberman, Frank S.; Buatti, John M.; Mountz, James M.; Erickson, Bradley J.; Fennessy, Fiona M.M.; Huang, Wei; Kalpathy-Cramer, Jayashree; Wahl, Richard L.; Linden, Hannah M.; Kinahan, Paul; Zhao, Binsheng; Hylton, Nola M.; Gillies, Robert J.; Clarke, Laurence; Nordstrom, Robert; Rubin, Daniel L.

    2015-01-01

    As anti-cancer therapies designed to target specific molecular pathways have been developed, it has become critical to develop methods to assess the response induced by such agents. While traditional, anatomic CT and MRI exams are useful in many settings, there is increasing evidence that these methods cannot answer the fundamental biological and physiological questions essential for assessment and, eventually, prediction of treatment response in the clinical trial setting, especially in the critical period soon after treatment is initiated. To optimally apply advances in quantitative imaging methods to trials of targeted cancer therapy, new infrastructure improvements are needed that incorporate these emerging techniques into the settings where they are most likely to have impact. In this review, we first elucidate the needs for therapeutic response assessment in the era of molecularly targeted therapy and describe how quantitative imaging can most effectively provide scientifically and clinically relevant data. We then describe the tools and methods required to apply quantitative imaging and provide concrete examples of work making these advances practically available for routine application in clinical trials. We conclude by proposing strategies to surmount barriers to wider incorporation of these quantitative imaging methods into clinical trials and, eventually, clinical practice. Our goal is to encourage and guide the oncology community to deploy standardized quantitative imaging techniques in clinical trials to further personalize care for cancer patients, and to provide a more efficient path for the development of improved targeted therapies. PMID:26773162

  10. Validation of CBCT for the computation of textural biomarkers

    NASA Astrophysics Data System (ADS)

    Paniagua, Beatriz; Ruellas, Antonio C.; Benavides, Erika; Marron, Steve; Wolford, Larry; Cevidanes, Lucia

    2015-03-01

    Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr- CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr- CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA.

  11. Validation of CBCT for the computation of textural biomarkers

    PubMed Central

    Paniagua, Beatriz; Ruellas, Antonio Carlos; Benavides, Erika; Marron, Steve; Woldford, Larry; Cevidanes, Lucia

    2015-01-01

    Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr-CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr-CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA. PMID:26085710

  12. Validation of CBCT for the computation of textural biomarkers.

    PubMed

    Paniagua, Beatriz; Ruellas, Antonio Carlos; Benavides, Erika; Marron, Steve; Woldford, Larry; Cevidanes, Lucia

    2015-03-17

    Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr-CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr-CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lin, C; Bradshaw, T; Perk, T

    2015-06-15

    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 {sup 18}F-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{sup 3} were identified and automatically segmented using a SUV>15 threshold. From eachmore » 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{sup 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

  14. Image Based Biomarker of Breast Cancer Risk: Analysis of Risk Disparity among Minority Populations

    DTIC Science & Technology

    2013-03-01

    TITLE: Image Based Biomarker of Breast Cancer Risk: Analysis of Risk Disparity among Minority Populations PRINCIPAL INVESTIGATOR: Fengshan Liu...SUBTITLE 5a. CONTRACT NUMBER Image Based Biomarker of Breast Cancer Risk: Analysis of Risk Disparity among Minority Populations 5b. GRANT NUMBER...identifying the prevalence of women with incomplete visualization of the breast . We developed a code to estimate the breast cancer risks using the

  15. Dissociable brain biomarkers of fluid intelligence.

    PubMed

    Paul, Erick J; Larsen, Ryan J; Nikolaidis, Aki; Ward, Nathan; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Barbey, Aron K

    2016-08-15

    Cognitive neuroscience has long sought to understand the biological foundations of human intelligence. Decades of research have revealed that general intelligence is correlated with two brain-based biomarkers: the concentration of the brain biochemical N-acetyl aspartate (NAA) measured by proton magnetic resonance spectroscopy (MRS) and total brain volume measured using structural MR imaging (MRI). However, the relative contribution of these biomarkers in predicting performance on core facets of human intelligence remains to be well characterized. In the present study, we sought to elucidate the role of NAA and brain volume in predicting fluid intelligence (Gf). Three canonical tests of Gf (BOMAT, Number Series, and Letter Sets) and three working memory tasks (Reading, Rotation, and Symmetry span tasks) were administered to a large sample of healthy adults (n=211). We conducted exploratory factor analysis to investigate the factor structure underlying Gf independent from working memory and observed two Gf components (verbal/spatial and quantitative reasoning) and one working memory component. Our findings revealed a dissociation between two brain biomarkers of Gf (controlling for age and sex): NAA concentration correlated with verbal/spatial reasoning, whereas brain volume correlated with quantitative reasoning and working memory. A follow-up analysis revealed that this pattern of findings is observed for males and females when analyzed separately. Our results provide novel evidence that distinct brain biomarkers are associated with specific facets of human intelligence, demonstrating that NAA and brain volume are independent predictors of verbal/spatial and quantitative facets of Gf. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Automated Tracking of Quantitative Assessments of Tumor Burden in Clinical Trials1

    PubMed Central

    Rubin, Daniel L; Willrett, Debra; O'Connor, Martin J; Hage, Cleber; Kurtz, Camille; Moreira, Dilvan A

    2014-01-01

    There are two key challenges hindering effective use of quantitative assessment of imaging in cancer response assessment: 1) Radiologists usually describe the cancer lesions in imaging studies subjectively and sometimes ambiguously, and 2) it is difficult to repurpose imaging data, because lesion measurements are not recorded in a format that permits machine interpretation and interoperability. We have developed a freely available software platform on the basis of open standards, the electronic Physician Annotation Device (ePAD), to tackle these challenges in two ways. First, ePAD facilitates the radiologist in carrying out cancer lesion measurements as part of routine clinical trial image interpretation workflow. Second, ePAD records all image measurements and annotations in a data format that permits repurposing image data for analyses of alternative imaging biomarkers of treatment response. To determine the impact of ePAD on radiologist efficiency in quantitative assessment of imaging studies, a radiologist evaluated computed tomography (CT) imaging studies from 20 subjects having one baseline and three consecutive follow-up imaging studies with and without ePAD. The radiologist made measurements of target lesions in each imaging study using Response Evaluation Criteria in Solid Tumors 1.1 criteria, initially with the aid of ePAD, and then after a 30-day washout period, the exams were reread without ePAD. The mean total time required to review the images and summarize measurements of target lesions was 15% (P < .039) shorter using ePAD than without using this tool. In addition, it was possible to rapidly reanalyze the images to explore lesion cross-sectional area as an alternative imaging biomarker to linear measure. We conclude that ePAD appears promising to potentially improve reader efficiency for quantitative assessment of CT examinations, and it may enable discovery of future novel image-based biomarkers of cancer treatment response. PMID:24772204

  17. High-speed quantitative phase imaging using time-stretch spectral shearing contrast (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Bosworth, Bryan; Foster, Mark A.

    2017-02-01

    Photonic time-stretch microscopy (TSM) provides an ideal platform for high-throughput imaging flow cytometry, affording extremely high shutter speeds and frame rates with high sensitivity. In order to resolve weakly scattering cells in biofluid and solve the issue of signal-to-noise in cell labeling specificity of biomarkers in imaging flow cytometry, several quantitative phase (QP) techniques have recently been adapted to TSM. However, these techniques have relied primarily on sensitive free-space optical configurations to generate full electric field measurements. The present work draws from the field of ultrashort pulse characterization to leverage the coherence of the ultrashort optical pulses integral to all TSM systems in order to do self-referenced single-shot quantitative phase imaging in a TSM system. Self-referencing is achieved via spectral shearing interferometry in an exceptionally stable and straightforward Sagnac loop incorporating an electro-optic phase modulator and polarization-maintaining fiber that produce sheared and unsheared copies of the pulse train with an inter-pulse delay determined by polarization mode dispersion. The spectral interferogram then yields a squared amplitude and a phase derivative image that can be integrated for conventional phase. We apply this spectral shearing contrast microscope to acquire QP images on a high-speed flow microscope at 90-MHz line rates with <400 pixels per line. We also consider the extension of this technique to compressed sensing (CS) acquisition by intensity modulating the interference spectra with pseudorandom binary waveforms to reconstruct the images from a highly sub-Nyquist number of random inner products, providing a path to even higher operating rates and reduced data storage requirements.

  18. Amyloid imaging and CSF biomarkers in predicting cognitive impairment up to 7.5 years later

    PubMed Central

    Fagan, Anne M.; Grant, Elizabeth A.; Hassenstab, Jason; Moulder, Krista L.; Maue Dreyfus, Denise; Sutphen, Courtney L.; Benzinger, Tammie L.S.; Mintun, Mark A.; Holtzman, David M.; Morris, John C.

    2013-01-01

    Objectives: We compared the ability of molecular biomarkers for Alzheimer disease (AD), including amyloid imaging and CSF biomarkers (Aβ42, tau, ptau181, tau/Aβ42, ptau181/Aβ42), to predict time to incident cognitive impairment among cognitively normal adults aged 45 to 88 years and followed for up to 7.5 years. Methods: Longitudinal data from Knight Alzheimer's Disease Research Center participants (N = 201) followed for a mean of 3.70 years (SD = 1.46 years) were used. Participants with amyloid imaging and CSF collection within 1 year of a clinical assessment indicating normal cognition were eligible. Cox proportional hazards models tested whether the individual biomarkers were related to time to incident cognitive impairment. “Expanded” models were developed using the biomarkers and participant demographic variables. The predictive values of the models were compared. Results: Abnormal levels of all biomarkers were associated with faster time to cognitive impairment, and some participants with abnormal biomarker levels remained cognitively normal for up to 6.6 years. No differences in predictive value were found between the individual biomarkers (p > 0.074), nor did we find differences between the expanded biomarker models (p > 0.312). Each expanded model better predicted incident cognitive impairment than the model containing the biomarker alone (p < 0.005). Conclusions: Our results indicate that all AD biomarkers studied here predicted incident cognitive impairment, and support the hypothesis that biomarkers signal underlying AD pathology at least several years before the appearance of dementia symptoms. PMID:23576620

  19. Protocol for Standardizing High-to-Moderate Abundance Protein Biomarker Assessments Through an MRM-with-Standard-Peptides Quantitative Approach.

    PubMed

    Percy, Andrew J; Yang, Juncong; Chambers, Andrew G; Mohammed, Yassene; Miliotis, Tasso; Borchers, Christoph H

    2016-01-01

    Quantitative mass spectrometry (MS)-based approaches are emerging as a core technology for addressing health-related queries in systems biology and in the biomedical and clinical fields. In several 'omics disciplines (proteomics included), an approach centered on selected or multiple reaction monitoring (SRM or MRM)-MS with stable isotope-labeled standards (SIS), at the protein or peptide level, has emerged as the most precise technique for quantifying and screening putative analytes in biological samples. To enable the widespread use of MRM-based protein quantitation for disease biomarker assessment studies and its ultimate acceptance for clinical analysis, the technique must be standardized to facilitate precise and accurate protein quantitation. To that end, we have developed a number of kits for assessing method/platform performance, as well as for screening proposed candidate protein biomarkers in various human biofluids. Collectively, these kits utilize a bottom-up LC-MS methodology with SIS peptides as internal standards and quantify proteins using regression analysis of standard curves. This chapter details the methodology used to quantify 192 plasma proteins of high-to-moderate abundance (covers a 6 order of magnitude range from 31 mg/mL for albumin to 18 ng/mL for peroxidredoxin-2), and a 21-protein subset thereof. We also describe the application of this method to patient samples for biomarker discovery and verification studies. Additionally, we introduce our recently developed Qualis-SIS software, which is used to expedite the analysis and assessment of protein quantitation data in control and patient samples.

  20. Evaluation of imaging biomarkers for identification of single cancer cells in blood

    NASA Astrophysics Data System (ADS)

    Odaka, Masao; Kim, Hyonchol; Girault, Mathias; Hattori, Akihiro; Terazono, Hideyuki; Matsuura, Kenji; Yasuda, Kenji

    2015-06-01

    A method of discriminating single cancer cells from whole blood cells based on their morphological visual characteristics (i.e., “imaging biomarker”) was examined. Cells in healthy rat blood, a cancer cell line (MAT-LyLu), and cells in cancer-cell-implanted rat blood were chosen as models, and their bright-field (BF, whole-cell morphology) and fluorescence (FL, nucleus morphology) images were taken by an on-chip multi-imaging flow cytometry system and compared. Eight imaging biomarker indices, i.e., cellular area in a BF image, nucleus area in an FL image, area ratio of a whole cell and its nucleus, distance of the mass center between a whole cell and nucleus, cellular and nucleus perimeter, and perimeter ratios were calculated and analyzed using the BF and FL images taken. Results show that cancer cells can be clearly distinguished from healthy blood cells using correlation diagrams for cellular and nucleus areas as two different categories. Moreover, a portion of cancer cells showed a low nucleus perimeter ratio less than 0.9 because of the irregular nucleus morphologies of cancer cells. These results indicate that the measurements of imaging biomarkers are practically applicable to identifying cancer cells in blood.

  1. Multimodal Imaging in Rat Model Recapitulates Alzheimer's Disease Biomarkers Abnormalities.

    PubMed

    Parent, Maxime J; Zimmer, Eduardo R; Shin, Monica; Kang, Min Su; Fonov, Vladimir S; Mathieu, Axel; Aliaga, Antonio; Kostikov, Alexey; Do Carmo, Sonia; Dea, Doris; Poirier, Judes; Soucy, Jean-Paul; Gauthier, Serge; Cuello, A Claudio; Rosa-Neto, Pedro

    2017-12-13

    Imaging biomarkers are frequently proposed as endpoints for clinical trials targeting brain amyloidosis in Alzheimer's disease (AD); however, the specific impact of amyloid-β (Aβ) aggregation on biomarker abnormalities remains elusive in AD. Using the McGill-R-Thy1-APP transgenic rat as a model of selective Aβ pathology, we characterized the longitudinal progression of abnormalities in biomarkers commonly used in AD research. Middle-aged (9-11 months) transgenic animals (both male and female) displayed mild spatial memory impairments and disrupted cingulate network connectivity measured by resting-state fMRI, even in the absence of hypometabolism (measured with PET [ 18 F]FDG) or detectable fibrillary amyloidosis (measured with PET [ 18 F]NAV4694). At more advanced ages (16-19 months), cognitive deficits progressed in conjunction with resting connectivity abnormalities; furthermore, hypometabolism, Aβ plaque accumulation, reduction of CSF Aβ 1-42 concentrations, and hippocampal atrophy (structural MRI) were detectable at this stage. The present results emphasize the early impact of Aβ on brain connectivity and support a framework in which persistent Aβ aggregation itself is sufficient to impose memory circuits dysfunction, which propagates to adjacent brain networks at later stages. SIGNIFICANCE STATEMENT The present study proposes a "back translation" of the Alzheimer pathological cascade concept from human to animals. We used the same set of Alzheimer imaging biomarkers typically used in large human cohorts and assessed their progression over time in a transgenic rat model, which allows for a finer spatial resolution not attainable with mice. Using this translational platform, we demonstrated that amyloid-β pathology recapitulates an Alzheimer-like profile of biomarker abnormalities even in the absence of other hallmarks of the disease such as neurofibrillary tangles and widespread neuronal losses. Copyright © 2017 Parent et al.

  2. Multimodal Imaging in Rat Model Recapitulates Alzheimer's Disease Biomarkers Abnormalities

    PubMed Central

    Parent, Maxime J.; Kang, Min Su; Mathieu, Axel; Aliaga, Antonio; Do Carmo, Sonia; Dea, Doris; Gauthier, Serge; Cuello, A. Claudio

    2017-01-01

    Imaging biomarkers are frequently proposed as endpoints for clinical trials targeting brain amyloidosis in Alzheimer's disease (AD); however, the specific impact of amyloid-β (Aβ) aggregation on biomarker abnormalities remains elusive in AD. Using the McGill-R-Thy1-APP transgenic rat as a model of selective Aβ pathology, we characterized the longitudinal progression of abnormalities in biomarkers commonly used in AD research. Middle-aged (9–11 months) transgenic animals (both male and female) displayed mild spatial memory impairments and disrupted cingulate network connectivity measured by resting-state fMRI, even in the absence of hypometabolism (measured with PET [18F]FDG) or detectable fibrillary amyloidosis (measured with PET [18F]NAV4694). At more advanced ages (16–19 months), cognitive deficits progressed in conjunction with resting connectivity abnormalities; furthermore, hypometabolism, Aβ plaque accumulation, reduction of CSF Aβ1-42 concentrations, and hippocampal atrophy (structural MRI) were detectable at this stage. The present results emphasize the early impact of Aβ on brain connectivity and support a framework in which persistent Aβ aggregation itself is sufficient to impose memory circuits dysfunction, which propagates to adjacent brain networks at later stages. SIGNIFICANCE STATEMENT The present study proposes a “back translation” of the Alzheimer pathological cascade concept from human to animals. We used the same set of Alzheimer imaging biomarkers typically used in large human cohorts and assessed their progression over time in a transgenic rat model, which allows for a finer spatial resolution not attainable with mice. Using this translational platform, we demonstrated that amyloid-β pathology recapitulates an Alzheimer-like profile of biomarker abnormalities even in the absence of other hallmarks of the disease such as neurofibrillary tangles and widespread neuronal losses. PMID:29097597

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

    PubMed

    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.

  4. CNTRICS Imaging Biomarkers Final Task Selection: Long-Term Memory and Reinforcement Learning

    PubMed Central

    Ragland, John D.; Cohen, Neal J.; Cools, Roshan; Frank, Michael J.; Hannula, Deborah E.; Ranganath, Charan

    2012-01-01

    Functional imaging paradigms hold great promise as biomarkers for schizophrenia research as they can detect altered neural activity associated with the cognitive and emotional processing deficits that are so disabling to this patient population. In an attempt to identify the most promising functional imaging biomarkers for research on long-term memory (LTM), the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) initiative selected “item encoding and retrieval,” “relational encoding and retrieval,” and “reinforcement learning” as key LTM constructs to guide the nomination process. This manuscript reports on the outcome of the third CNTRICS biomarkers meeting in which nominated paradigms in each of these domains were discussed by a review panel to arrive at a consensus on which of the nominated paradigms could be recommended for immediate translational development. After briefly describing this decision process, information is presented from the nominating authors describing the 4 functional imaging paradigms that were selected for immediate development. In addition to describing the tasks, information is provided on cognitive and neural construct validity, sensitivity to behavioral or pharmacological manipulations, availability of animal models, psychometric characteristics, effects of schizophrenia, and avenues for future development. PMID:22102094

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

    PubMed Central

    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.

    2016-01-01

    Objective: To examine neurodegenerative imaging biomarkers in Alzheimer disease (AD) dementia from middle to old age. Methods: Persons with AD dementia and elevated brain β-amyloid with Pittsburgh compound B (PiB)-PET imaging underwent [18F]-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. Results: 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. Conclusions: 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. PMID:27421543

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Quantitative metagenomics reveals unique gut microbiome biomarkers in ankylosing spondylitis.

    PubMed

    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.

  9. Top-Down Quantitative Proteomics Identified Phosphorylation of Cardiac Troponin I as a Candidate Biomarker for Chronic Heart Failure

    PubMed Central

    Zhang, Jiang; Guy, Moltu J.; Norman, Holly S.; Chen, Yi-Chen; Xu, Qingge; Dong, Xintong; Guner, Huseyin; Wang, Sijian; Kohmoto, Takushi; Young, Ken H.; Moss, Richard L.; Ge, Ying

    2011-01-01

    The rapid increase in the prevalence of chronic heart failure (CHF) worldwide underscores an urgent need to identify biomarkers for the early detection of CHF. Post-translational modifications (PTMs) are associated with many critical signaling events during disease progression and thus offer a plethora of candidate biomarkers. We have employed top-down quantitative proteomics methodology for comprehensive assessment of PTMs in whole proteins extracted from normal and diseased tissues. We have systematically analyzed thirty-six clinical human heart tissue samples and identified phosphorylation of cardiac troponin I (cTnI) as a candidate biomarker for CHF. The relative percentages of the total phosphorylated cTnI forms over the entire cTnI populations (%Ptotal) were 56.4±3.5%, 36.9±1.6%, 6.1±2.4%, and 1.0±0.6% for postmortem hearts with normal cardiac function (n=7), early-stage of mild hypertrophy (n=5), severe hypertrophy/dilation (n=4), and end-stage CHF (n=6), respectively. In fresh transplant samples, the %Ptotal of cTnI from non-failing donor (n=4), and end-stage failing hearts (n=10) were 49.5±5.9% and 18.8±2.9%, respectively. Top-down MS with electron capture dissociation unequivocally localized the altered phosphorylation sites to Ser22/23 and determined the order of phosphorylation/dephosphorylation. This study represents the first clinical application of top-down MS-based quantitative proteomics for biomarker discovery from tissues, highlighting the potential of PTM as disease biomarkers. PMID:21751783

  10. Application of multispectral imaging in quantitative immunohistochemistry study of breast cancer: a comparative study.

    PubMed

    Liu, Wen-Lou; Wang, Lin-Wei; Chen, Jia-Mei; Yuan, Jing-Ping; Xiang, Qing-Ming; Yang, Gui-Fang; Qu, Ai-Ping; Liu, Juan; Li, Yan

    2016-04-01

    Multispectral imaging (MSI) based on imaging and spectroscopy, as relatively novel to the field of histopathology, has been used in biomedical multidisciplinary researches. We analyzed and compared the utility of multispectral (MS) versus conventional red-green-blue (RGB) images for immunohistochemistry (IHC) staining to explore the advantages of MSI in clinical-pathological diagnosis. The MS images acquired of IHC-stained membranous marker human epidermal growth factor receptor 2 (HER2), cytoplasmic marker cytokeratin5/6 (CK5/6), and nuclear marker estrogen receptor (ER) have higher resolution, stronger contrast, and more accurate segmentation than the RGB images. The total signal optical density (OD) values for each biomarker were higher in MS images than in RGB images (all P < 0.05). Moreover, receiver operator characteristic (ROC) analysis revealed that a greater area under the curve (AUC), higher sensitivity, and specificity in evaluation of HER2 gene were achieved by MS images (AUC = 0.91, 89.1 %, 83.2 %) than RGB images (AUC = 0.87, 84.5, and 81.8 %). There was no significant difference between quantitative results of RGB images and clinico-pathological characteristics (P > 0.05). However, by quantifying MS images, the total signal OD values of HER2 positive expression were correlated with lymph node status and histological grades (P = 0.02 and 0.04). Additionally, the consistency test results indicated the inter-observer agreement was more robust in MS images for HER2 (inter-class correlation coefficient (ICC) = 0.95, r s = 0.94), CK5/6 (ICC = 0.90, r s = 0.88), and ER (ICC = 0.94, r s = 0.94) (all P < 0.001) than that in RGB images for HER2 (ICC = 0.91, r s = 0.89), CK5/6 (ICC = 0.85, r s = 0.84), and ER (ICC = 0.90, r s = 0.89) (all P < 0.001). Our results suggest that the application of MS images in quantitative IHC analysis could obtain higher accuracy, reliability, and more

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

    PubMed

    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

  12. Consensus Paper: Radiological Biomarkers of Cerebellar Diseases

    PubMed Central

    Baldarçara, Leonardo; Currie, Stuart; Hadjivassiliou, M.; Hoggard, Nigel; Jack, Allison; Jackowski, Andrea P.; Mascalchi, Mario; Parazzini, Cecilia; Reetz, Kathrin; Righini, Andrea; Schulz, Jörg B.; Vella, Alessandra; Webb, Sara Jane; Habas, Christophe

    2016-01-01

    Hereditary and sporadic cerebellar ataxias represent a vast and still growing group of diseases whose diagnosis and differentiation cannot only rely on clinical evaluation. Brain imaging including magnetic resonance (MR) and nuclear medicine techniques allows for characterization of structural and functional abnormalities underlying symptomatic ataxias. These methods thus constitute a potential source of radiological biomarkers, which could be used to identify these diseases and differentiate subgroups of them, and to assess their severity and their evolution. Such biomarkers mainly comprise qualitative and quantitative data obtained from MR including proton spectroscopy, diffusion imaging, tractography, voxel-based morphometry, functional imaging during task execution or in a resting state, and from SPETC and PET with several radiotracers. In the current article, we aim to illustrate briefly some applications of these neuroimaging tools to evaluation of cerebellar disorders such as inherited cerebellar ataxia, fetal developmental malformations, and immune-mediated cerebellar diseases and of neurodegenerative or early-developing diseases, such as dementia and autism in which cerebellar involvement is an emerging feature. Although these radiological biomarkers appear promising and helpful to better understand ataxia-related anatomical and physiological impairments, to date, very few of them have turned out to be specific for a given ataxia with atrophy of the cerebellar system being the main and the most usual alteration being observed. Consequently, much remains to be done to establish sensitivity, specificity, and reproducibility of available MR and nuclear medicine features as diagnostic, progression and surrogate biomarkers in clinical routine. PMID:25382714

  13. Quantitative analysis of single-molecule superresolution images

    PubMed Central

    Coltharp, Carla; Yang, Xinxing; Xiao, Jie

    2014-01-01

    This review highlights the quantitative capabilities of single-molecule localization-based superresolution imaging methods. In addition to revealing fine structural details, the molecule coordinate lists generated by these methods provide the critical ability to quantify the number, clustering, and colocalization of molecules with 10 – 50 nm resolution. Here we describe typical workflows and precautions for quantitative analysis of single-molecule superresolution images. These guidelines include potential pitfalls and essential control experiments, allowing critical assessment and interpretation of superresolution images. PMID:25179006

  14. How to integrate quantitative information into imaging reports for oncologic patients.

    PubMed

    Martí-Bonmatí, L; Ruiz-Martínez, E; Ten, A; Alberich-Bayarri, A

    2018-05-01

    Nowadays, the images and information generated in imaging tests, as well as the reports that are issued, are digital and represent a reliable source of data. Reports can be classified according to their content and to the type of information they include into three main types: organized (free text in natural language), predefined (with templates and guidelines elaborated with previously determined natural language like that used in BI-RADS and PI-RADS), or structured (with drop-down menus displaying questions with various possible answers that have been agreed on with the rest of the multidisciplinary team, which use standardized lexicons and are structured in the form of a database with data that can be traced and exploited with statistical tools and data mining). The structured report, compatible with Management of Radiology Report Templates (MRRT), makes it possible to incorporate quantitative information related with the digital analysis of the data from the acquired images to accurately and precisely describe the properties and behavior of tissues by means of radiomics (characteristics and parameters). In conclusion, structured digital information (images, text, measurements, radiomic features, and imaging biomarkers) should be integrated into computerized reports so that they can be indexed in large repositories. Radiologic databanks are fundamental for exploiting health information, phenotyping lesions and diseases, and extracting conclusions in personalized medicine. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

  15. Consortium for Imaging and Biomarkers (CIB) | Division of Cancer Prevention

    Cancer.gov

    Overdiagnosis and false positives present significant clinical problems in the prevention, detection and treatment of | 8 lead investigators combining imaging methods for the visualization of lesions with biomarkers to improve the accuracy of screening, early cancer detection, and the diagnosis of early stage cancers.

  16. Molecular imaging biomarkers of resistance to radiation therapy for spontaneous nasal tumors in canines.

    PubMed

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

    2015-03-15

    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. 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). 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 pretreatment to midtreatment (P=.041

  17. A quantitative reconstruction software suite for SPECT imaging

    NASA Astrophysics Data System (ADS)

    Namías, Mauro; Jeraj, Robert

    2017-11-01

    Quantitative Single Photon Emission Tomography (SPECT) imaging allows for measurement of activity concentrations of a given radiotracer in vivo. Although SPECT has usually been perceived as non-quantitative by the medical community, the introduction of accurate CT based attenuation correction and scatter correction from hybrid SPECT/CT scanners has enabled SPECT systems to be as quantitative as Positron Emission Tomography (PET) systems. We implemented a software suite to reconstruct quantitative SPECT images from hybrid or dedicated SPECT systems with a separate CT scanner. Attenuation, scatter and collimator response corrections were included in an Ordered Subset Expectation Maximization (OSEM) algorithm. A novel scatter fraction estimation technique was introduced. The SPECT/CT system was calibrated with a cylindrical phantom and quantitative accuracy was assessed with an anthropomorphic phantom and a NEMA/IEC image quality phantom. Accurate activity measurements were achieved at an organ level. This software suite helps increasing quantitative accuracy of SPECT scanners.

  18. Multimodal quantitative phase and fluorescence imaging of cell apoptosis

    NASA Astrophysics Data System (ADS)

    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.

  19. Quantitative SIMS Imaging of Agar-Based Microbial Communities.

    PubMed

    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.

  20. Machine Learning methods for Quantitative Radiomic Biomarkers.

    PubMed

    Parmar, Chintan; Grossmann, Patrick; Bussink, Johan; Lambin, Philippe; Aerts, Hugo J W L

    2015-08-17

    Radiomics extracts and mines large number of medical imaging features quantifying tumor phenotypic characteristics. Highly accurate and reliable machine-learning approaches can drive the success of radiomic applications in clinical care. In this radiomic study, fourteen feature selection methods and twelve classification methods were examined in terms of their performance and stability for predicting overall survival. A total of 440 radiomic features were extracted from pre-treatment computed tomography (CT) images of 464 lung cancer patients. To ensure the unbiased evaluation of different machine-learning methods, publicly available implementations along with reported parameter configurations were used. Furthermore, we used two independent radiomic cohorts for training (n = 310 patients) and validation (n = 154 patients). We identified that Wilcoxon test based feature selection method WLCX (stability = 0.84 ± 0.05, AUC = 0.65 ± 0.02) and a classification method random forest RF (RSD = 3.52%, AUC = 0.66 ± 0.03) had highest prognostic performance with high stability against data perturbation. Our variability analysis indicated that the choice of classification method is the most dominant source of performance variation (34.21% of total variance). Identification of optimal machine-learning methods for radiomic applications is a crucial step towards stable and clinically relevant radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor-phenotypic characteristics in clinical practice.

  1. Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

    PubMed

    Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

    2017-11-01

    Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

  2. Laser-emission imaging of nuclear biomarkers for high-contrast cancer screening and immunodiagnosis

    PubMed Central

    Chen, Yu-Cheng; Tan, Xiaotian; Sun, Qihan; Chen, Qiushu; Wang, Wenjie; Fan, Xudong

    2017-01-01

    Detection of nuclear biomarkers such as nucleic acids and nuclear proteins is critical for early-stage cancer diagnosis and prognosis. Conventional methods relying on morphological assessment of cell nuclei in histopathology slides may be subjective, whereas colorimetric immunohistochemical and fluorescence-based imaging are limited by strong light absorption, broad-emission bands and low contrast. Here, we describe the development and use of a scanning laser-emission-based microscope that maps lasing emissions from nuclear biomarkers in human tissues. 41 tissue samples from 35 patients labelled with site-specific and biomarker-specific antibody-conjugated dyes were sandwiched in a Fabry-Pérot microcavity while an excitation laser beam built a laser-emission image. We observed multiple sub-cellular lasing emissions from cancer cell nuclei, with a threshold of tens of μJ/mm2, sub-micron resolution (<700 nm), and a lasing band in the few-nanometre range. Different lasing thresholds of nuclei in cancer and normal tissues enabled the identification and multiplexed detection of nuclear proteomic biomarkers, with a high sensitivity for early-stage cancer diagnosis. Laser-emission-based cancer screening and immunodiagnosis might find use in precision medicine and facilitate research in cell biology. PMID:29204310

  3. Confidence estimation for quantitative photoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Gröhl, Janek; Kirchner, Thomas; Maier-Hein, Lena

    2018-02-01

    Quantification of photoacoustic (PA) images is one of the major challenges currently being addressed in PA research. Tissue properties can be quantified by correcting the recorded PA signal with an estimation of the corresponding fluence. Fluence estimation itself, however, is an ill-posed inverse problem which usually needs simplifying assumptions to be solved with state-of-the-art methods. These simplifications, as well as noise and artifacts in PA images reduce the accuracy of quantitative PA imaging (PAI). This reduction in accuracy is often localized to image regions where the assumptions do not hold true. This impedes the reconstruction of functional parameters when averaging over entire regions of interest (ROI). Averaging over a subset of voxels with a high accuracy would lead to an improved estimation of such parameters. To achieve this, we propose a novel approach to the local estimation of confidence in quantitative reconstructions of PA images. It makes use of conditional probability densities to estimate confidence intervals alongside the actual quantification. It encapsulates an estimation of the errors introduced by fluence estimation as well as signal noise. We validate the approach using Monte Carlo generated data in combination with a recently introduced machine learning-based approach to quantitative PAI. Our experiments show at least a two-fold improvement in quantification accuracy when evaluating on voxels with high confidence instead of thresholding signal intensity.

  4. [Quantitative data analysis for live imaging of bone.

    PubMed

    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.

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

    PubMed

    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

    associated with increased risk of breast cancer for both operators (OR = 4.0, 95% confidence interval (CI) 1.6-10.1, and 2.4, 95% CI 1.2-4.7). Quantitative 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.

  6. A paradigm shift in imaging biomarkers in neovascular age-related macular degeneration.

    PubMed

    Schmidt-Erfurth, Ursula; Waldstein, Sebastian M

    2016-01-01

    Neovascular age-related macular degeneration (AMD) has undergone substantial break-throughs in diagnostic as well as therapeutic respect, with optical coherence tomography (OCT) allowing to identify disease morphology in great detail, and intravitreal anti-vascular endothelial growth factor therapy providing unprecedented benefit. However, these two paths have yet not been combined in an optimal way, real-world outcomes are inferior to expectations, and disease management is largely inefficient in the real-world setting. This dilemma can be solved by identification of valid biomarkers relevant for visual function, disease activity and prognosis, which can provide solid guidance for therapeutic management on an individual level as well as on the population base. Qualitative and quantitative morphological features obtained by advanced OCT provide novel insight into exudative and degenerative stages of neovascular AMD. However, conclusions from structure/function correlations evolve differently from previous paradigms. While central retinal thickness was used as biomarker for guiding retreatment management in clinical trials and practice, fluid localization in different compartments offers superior prognostic value: Intraretinal cystoid fluid has a negative impact on visual acuity and is considered as degenerative when persisting through the initial therapeutic interval. Subretinal fluid is associated with superior visual benefit and a lower rate of progression towards geographic atrophy. Detachment of the retinal pigment epithelium was identified as most pathognomonic biomarker, often irresponsive to therapy and responsible for visual decline during a pro-re-nata regimen. Alterations of neurosensory tissue are usually associated with irreversible loss of functional elements and a negative prognosis. Novel OCT technologies offer crucial insight into corresponding changes at the level of the photoreceptor--retinal pigment epithelial--choriocapillary unit, identifying

  7. Systemic, Local, and Imaging Biomarkers of Brain Injury: More Needed, and Better Use of Those Already Established?

    PubMed Central

    Carpenter, Keri L. H.; Czosnyka, Marek; Jalloh, Ibrahim; Newcombe, Virginia F. J.; Helmy, Adel; Shannon, Richard J.; Budohoski, Karol P.; Kolias, Angelos G.; Kirkpatrick, Peter J.; Carpenter, Thomas Adrian; Menon, David K.; Hutchinson, Peter J.

    2015-01-01

    Much progress has been made over the past two decades in the treatment of severe acute brain injury, including traumatic brain injury and subarachnoid hemorrhage, 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 utilized in diagnosis and monitoring of response to treatment. They are thus crucial to the development of therapies and may be utilized 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 state of knowledge

  8. Quantitative image fusion in infrared radiometry

    NASA Astrophysics Data System (ADS)

    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.

  9. Vessel wall characterization using quantitative MRI: what's in a number?

    PubMed

    Coolen, Bram F; Calcagno, Claudia; van Ooij, Pim; Fayad, Zahi A; Strijkers, Gustav J; Nederveen, Aart J

    2018-02-01

    The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.

  10. UK audit of quantitative thyroid uptake imaging.

    PubMed

    Taylor, Jonathan C; Murray, Anthony W; Hall, David O; Barnfield, Mark C; O'Shaugnessy, Emma R; Carson, Kathryn J; Cullis, James; Towey, David J; Kenny, Bob

    2017-07-01

    A national audit of quantitative thyroid uptake imaging was conducted by the Nuclear Medicine Software Quality Group of the Institute of Physics and Engineering in Medicine in 2014/2015. The aims of the audit were to measure and assess the variability in thyroid uptake results across the UK and to compare local protocols with British Nuclear Medicine Society (BNMS) guidelines. Participants were invited through a combination of emails on a public mailbase and targeted invitations from regional co-ordinators. All participants were given a set of images from which to calculate quantitative measures and a spreadsheet for capturing results. The image data consisted of two sets of 10 anterior thyroid images, half of which were acquired after administration of Tc-pertechnetate and the other half after administration of I-iodide. Images of the administration syringes or thyroid phantoms were also included. In total, 54 participants responded to the audit. The median number of scans conducted per year was 50. A majority of centres had at least one noncompliance in comparison with BNMS guidelines. Of most concern was the widespread lack of injection-site imaging. Quantitative results showed that both intersite and intrasite variability were low for the Tc dataset. The coefficient of quartile deviation was between 0.03 and 0.13 for measurements of overall percentage uptake. Although the number of returns for the I dataset was smaller, the level of variability between participants was greater (the coefficient of quartile deviation was between 0.17 and 0.25). A UK-wide audit showed that thyroid uptake imaging is still a common test in the UK. It was found that most centres do not adhere to all aspects of the BNMS practice guidelines but that quantitative results are reasonably consistent for Tc-based scans.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bosca, R; The University of Texas MD Anderson Cancer Center, Houston, TX; Mahajan, A

    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 weremore » 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 (PR« less

  12. 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.

    PubMed

    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.

  13. FLIM-FRET image analysis of tryptophan in prostate cancer cells

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  15. Qualitative and quantitative interpretation of SEM image using digital image processing.

    PubMed

    Saladra, Dawid; Kopernik, Magdalena

    2016-10-01

    The aim of the this study is improvement of qualitative and quantitative analysis of scanning electron microscope micrographs by development of computer program, which enables automatic crack analysis of scanning electron microscopy (SEM) micrographs. Micromechanical tests of pneumatic ventricular assist devices result in a large number of micrographs. Therefore, the analysis must be automatic. Tests for athrombogenic titanium nitride/gold coatings deposited on polymeric substrates (Bionate II) are performed. These tests include microshear, microtension and fatigue analysis. Anisotropic surface defects observed in the SEM micrographs require support for qualitative and quantitative interpretation. Improvement of qualitative analysis of scanning electron microscope images was achieved by a set of computational tools that includes binarization, simplified expanding, expanding, simple image statistic thresholding, the filters Laplacian 1, and Laplacian 2, Otsu and reverse binarization. Several modifications of the known image processing techniques and combinations of the selected image processing techniques were applied. The introduced quantitative analysis of digital scanning electron microscope images enables computation of stereological parameters such as area, crack angle, crack length, and total crack length per unit area. This study also compares the functionality of the developed computer program of digital image processing with existing applications. The described pre- and postprocessing may be helpful in scanning electron microscopy and transmission electron microscopy surface investigations. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

  16. Quantitative Imaging with a Mobile Phone Microscope

    PubMed Central

    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

  17. Quantitative Hyperspectral Reflectance Imaging

    PubMed Central

    Klein, Marvin E.; Aalderink, Bernard J.; Padoan, Roberto; de Bruin, Gerrit; Steemers, Ted A.G.

    2008-01-01

    Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms. PMID:27873831

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

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed

    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

  20. Alzheimer Disease: New Concepts on Its Neurobiology and the Clinical Role Imaging Will Play

    PubMed Central

    2012-01-01

    Alzheimer disease (AD) is one of, if not the most, feared diseases associated with aging. The prevalence of AD increases exponentially with age after 60 years. Increasing life expectancy coupled with the absence of any approved disease-modifying therapies at present position AD as a dominant public health problem. Major advances have occurred in the development of disease biomarkers for AD in the past 2 decades. At present, the most well-developed AD biomarkers are the cerebrospinal fluid analytes amyloid-β 42 and tau and the brain imaging measures amyloid positron emission tomography (PET), fluorodeoxyglucose PET, and magnetic resonance imaging. CSF and imaging biomarkers are incorporated into revised diagnostic guidelines for AD, which have recently been updated for the first time since their original formulation in 1984. Results of recent studies suggest the possibility of an ordered evolution of AD biomarker abnormalities that can be used to stage the typical 20–30-year course of the disease. When compared with biomarkers in other areas of medicine, however, the absence of standardized quantitative metrics for AD imaging biomarkers constitutes a major deficiency. Failure to move toward a standardized system of quantitative metrics has substantially limited potential diagnostic usefulness of imaging in AD. This presents an important opportunity that, if widely embraced, could greatly expand the application of imaging to improve clinical diagnosis and the quality and efficiency of clinical trials. © RSNA, 2012 PMID:22517954

  1. Generalized PSF modeling for optimized quantitation in PET imaging.

    PubMed

    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

  2. Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation.

    PubMed

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

    2017-04-01

    With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.

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

    NASA Astrophysics Data System (ADS)

    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.

  4. Quantitative Image Restoration in Bright Field Optical Microscopy.

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Phase calibration target for quantitative phase imaging with ptychography.

    PubMed

    Godden, T M; Muñiz-Piniella, A; Claverley, J D; Yacoot, A; Humphry, M J

    2016-04-04

    Quantitative phase imaging (QPI) utilizes refractive index and thickness variations that lead to optical phase shifts. This gives contrast to images of transparent objects. In quantitative biology, phase images are used to accurately segment cells and calculate properties such as dry mass, volume and proliferation rate. The fidelity of the measured phase shifts is of critical importance in this field. However to date, there has been no standardized method for characterizing the performance of phase imaging systems. Consequently, there is an increasing need for protocols to test the performance of phase imaging systems using well-defined phase calibration and resolution targets. In this work, we present a candidate for a standardized phase resolution target, and measurement protocol for the determination of the transfer of spatial frequencies, and sensitivity of a phase imaging system. The target has been carefully designed to contain well-defined depth variations over a broadband range of spatial frequencies. In order to demonstrate the utility of the target, we measure quantitative phase images on a ptychographic microscope, and compare the measured optical phase shifts with Atomic Force Microscopy (AFM) topography maps and surface profile measurements from coherence scanning interferometry. The results show that ptychography has fully quantitative nanometer sensitivity in optical path differences over a broadband range of spatial frequencies for feature sizes ranging from micrometers to hundreds of micrometers.

  7. Non-interferometric quantitative phase imaging of yeast cells

    NASA Astrophysics Data System (ADS)

    Poola, Praveen K.; Pandiyan, Vimal Prabhu; John, Renu

    2015-12-01

    Real-time imaging of live cells is quite difficult without the addition of external contrast agents. Various methods for quantitative phase imaging of living cells have been proposed like digital holographic microscopy and diffraction phase microscopy. In this paper, we report theoretical and experimental results of quantitative phase imaging of live yeast cells with nanometric precision using transport of intensity equations (TIE). We demonstrate nanometric depth sensitivity in imaging live yeast cells using this technique. This technique being noninterferometric, does not need any coherent light sources and images can be captured through a regular bright-field microscope. This real-time imaging technique would deliver the depth or 3-D volume information of cells and is highly promising in real-time digital pathology applications, screening of pathogens and staging of diseases like malaria as it does not need any preprocessing of samples.

  8. The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science

    PubMed Central

    2014-01-01

    In the post-genomic era, it has become evident that genetic changes alone are not sufficient to understand most disease processes including pancreatic cancer. Genome sequencing has revealed a complex set of genetic alterations in pancreatic cancer such as point mutations, chromosomal losses, gene amplifications and telomere shortening that drive cancerous growth through specific signaling pathways. Proteome-based approaches are important complements to genomic data and provide crucial information of the target driver molecules and their post-translational modifications. By applying quantitative mass spectrometry, this is an alternative way to identify biomarkers for early diagnosis and personalized medicine. We review the current quantitative mass spectrometric technologies and analyses that have been developed and applied in the last decade in the context of pancreatic cancer. Examples of candidate biomarkers that have been identified from these pancreas studies include among others, asporin, CD9, CXC chemokine ligand 7, fibronectin 1, galectin-1, gelsolin, intercellular adhesion molecule 1, insulin-like growth factor binding protein 2, metalloproteinase inhibitor 1, stromal cell derived factor 4, and transforming growth factor beta-induced protein. Many of these proteins are involved in various steps in pancreatic tumor progression including cell proliferation, adhesion, migration, invasion, metastasis, immune response and angiogenesis. These new protein candidates may provide essential information for the development of protein diagnostics and targeted therapies. We further argue that new strategies must be advanced and established for the integration of proteomic, transcriptomic and genomic data, in order to enhance biomarker translation. Large scale studies with meta data processing will pave the way for novel and unexpected correlations within pancreatic cancer, that will benefit the patient, with targeted treatment. PMID:24708694

  9. Can diffusion-weighted imaging serve as a biomarker of fibrosis in pancreatic adenocarcinoma?

    PubMed

    Hecht, Elizabeth M; Liu, Michael Z; Prince, Martin R; Jambawalikar, Sachin; Remotti, Helen E; Weisberg, Stuart W; Garmon, Donald; Lopez-Pintado, Sara; Woo, Yanghee; Kluger, Michael D; Chabot, John A

    2017-08-01

    To assess the relationship between diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM)-derived quantitative parameters (apparent diffusion coefficient [ADC], perfusion fraction [f], D slow , diffusion coefficient [D], and D fast , pseudodiffusion coefficient [D*]) and histopathology in pancreatic adenocarcinoma (PAC). Subjects with suspected surgically resectable PAC were prospectively enrolled in this Health Insurance Portability and Accountability Act (HIPAA)-compliant, Institutional Review Board-approved study. Imaging was performed at 1.5T with a respiratory-triggered echo planar DWI sequence using 10 b values. Two readers drew regions of interest (ROIs) over the tumor and adjacent nontumoral tissue. Monoexponential and biexponential fits were used to derive ADC 2b , ADC all , f, D, and D*, which were compared to quantitative histopathology of fibrosis, mean vascular density, and cellularity. Two biexponential IVIM models were investigated and compared: 1) nonlinear least-square fitting based on the Levenberg-Marquardt algorithm, and 2) linear fit using a fixed D* (20 mm 2 /s). Statistical analysis included Student's t-test, Pearson correlation (P < 0.05 was considered significant), intraclass correlation, and coefficients of variance. Twenty subjects with PAC were included in the final cohort. Negative correlation between D and fibrosis (Reader 2: r = -0.57 P = 0.01; pooled P = -0.46, P = 0.04) was observed with a trend toward positive correlation between f and fibrosis (r = 0.44, P = 0.05). ADC 2b was significantly lower in PAC with dense fibrosis than with loose fibrosis ADC 2b (P = 0.03). Inter- and intrareader agreement was excellent for ADC, D, and f. In PAC, D negatively correlates with fibrosis, with a trend toward positive correlation with f suggesting both perfusion and diffusion effects contribute to stromal desmoplasia. ADC 2b is significantly lower in tumors with dense fibrosis and may serve as a

  10. Imaging biomarkers in liver fibrosis.

    PubMed

    Berzigotti, A; França, M; Martí-Aguado, D; Martí-Bonmatí, L

    There is a need for early identification of patients with chronic liver diseases due to their increasing prevalence and morbidity-mortality. The degree of liver fibrosis determines the prognosis and therapeutic options in this population. Liver biopsy represents the reference standard for fibrosis staging. However, given its limitations and complications, different non-invasive methods have been developed recently for the in vivo quantification of fibrosis. Due to their precision and reliability, biomarkers' measurements derived from Ultrasound and Magnetic Resonance stand out. This article reviews the different acquisition techniques and image processing methods currently used in the evaluation of liver fibrosis, focusing on their diagnostic performance, applicability and clinical value. In order to properly interpret their results in the appropriate clinical context, it seems necessary to understand the techniques and their quality parameters, the standardization and validation of the measurement units and the quality control of the methodological problems. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

  11. Quantitative Imaging in Cancer Evolution and Ecology

    PubMed Central

    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

  12. Advancing Precision Nuclear Medicine and Molecular Imaging for Lymphoma.

    PubMed

    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.

  13. Prospects and challenges of quantitative phase imaging in tumor cell biology

    NASA Astrophysics Data System (ADS)

    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.

  14. Calibration of Wide-Field Deconvolution Microscopy for Quantitative Fluorescence Imaging

    PubMed Central

    Lee, Ji-Sook; Wee, Tse-Luen (Erika); Brown, Claire M.

    2014-01-01

    Deconvolution enhances contrast in fluorescence microscopy images, especially in low-contrast, high-background wide-field microscope images, improving characterization of features within the sample. Deconvolution can also be combined with other imaging modalities, such as confocal microscopy, and most software programs seek to improve resolution as well as contrast. Quantitative image analyses require instrument calibration and with deconvolution, necessitate that this process itself preserves the relative quantitative relationships between fluorescence intensities. To ensure that the quantitative nature of the data remains unaltered, deconvolution algorithms need to be tested thoroughly. This study investigated whether the deconvolution algorithms in AutoQuant X3 preserve relative quantitative intensity data. InSpeck Green calibration microspheres were prepared for imaging, z-stacks were collected using a wide-field microscope, and the images were deconvolved using the iterative deconvolution algorithms with default settings. Afterwards, the mean intensities and volumes of microspheres in the original and the deconvolved images were measured. Deconvolved data sets showed higher average microsphere intensities and smaller volumes than the original wide-field data sets. In original and deconvolved data sets, intensity means showed linear relationships with the relative microsphere intensities given by the manufacturer. Importantly, upon normalization, the trend lines were found to have similar slopes. In original and deconvolved images, the volumes of the microspheres were quite uniform for all relative microsphere intensities. We were able to show that AutoQuant X3 deconvolution software data are quantitative. In general, the protocol presented can be used to calibrate any fluorescence microscope or image processing and analysis procedure. PMID:24688321

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

    PubMed

    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.

  16. Quantitative multimodality imaging in cancer research and therapy.

    PubMed

    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.

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

    PubMed

    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.

  18. Quantitative image processing in fluid mechanics

    NASA Technical Reports Server (NTRS)

    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.

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

    PubMed

    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.

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

    PubMed Central

    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

    2017-01-01

    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. PMID:24872353

  1. Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

    PubMed

    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.

  2. Infrared thermography quantitative image processing

    NASA Astrophysics Data System (ADS)

    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.

  3. Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation

    PubMed Central

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

    2017-01-01

    Abstract. With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset. PMID:28612037

  4. Cancer Biomarkers | Division of Cancer Prevention

    Cancer.gov

    [[{"fid":"175","view_mode":"default","fields":{"format":"default","field_file_image_alt_text[und][0][value]":"Cancer Biomarkers Research Group Homepage Logo","field_file_image_title_text[und][0][value]":"Cancer Biomarkers Research Group Homepage Logo","field_folder[und]":"15"},"type":"media","attributes":{"alt":"Cancer Biomarkers Research Group Homepage Logo","title":"Cancer

  5. Quantitative Phase Imaging in a Volume Holographic Microscope

    NASA Astrophysics Data System (ADS)

    Waller, Laura; Luo, Yuan; Barbastathis, George

    2010-04-01

    We demonstrate a method for quantitative phase imaging in a Volume Holographic Microscope (VHM) from a single exposure, describe the properties of the system and show experimental results. The VHM system uses a multiplexed volume hologram (VH) to laterally separate images from different focal planes. This 3D intensity information is then used to solve the transport of intensity (TIE) equation and recover phase quantitatively. We discuss the modifications to the technique that were made in order to give accurate results.

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

    PubMed Central

    Zhang, Jiong; Bekkers, Erik; Abbasi-Sureshjani, Samaneh

    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. PMID:27703803

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

    PubMed

    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.

  8. Principles of Quantitative MR Imaging with Illustrated Review of Applicable Modular Pulse Diagrams.

    PubMed

    Mills, Andrew F; Sakai, Osamu; Anderson, Stephan W; Jara, Hernan

    2017-01-01

    Continued improvements in diagnostic accuracy using magnetic resonance (MR) imaging will require development of methods for tissue analysis that complement traditional qualitative MR imaging studies. Quantitative MR imaging is based on measurement and interpretation of tissue-specific parameters independent of experimental design, compared with qualitative MR imaging, which relies on interpretation of tissue contrast that results from experimental pulse sequence parameters. Quantitative MR imaging represents a natural next step in the evolution of MR imaging practice, since quantitative MR imaging data can be acquired using currently available qualitative imaging pulse sequences without modifications to imaging equipment. The article presents a review of the basic physical concepts used in MR imaging and how quantitative MR imaging is distinct from qualitative MR imaging. Subsequently, the article reviews the hierarchical organization of major applicable pulse sequences used in this article, with the sequences organized into conventional, hybrid, and multispectral sequences capable of calculating the main tissue parameters of T1, T2, and proton density. While this new concept offers the potential for improved diagnostic accuracy and workflow, awareness of this extension to qualitative imaging is generally low. This article reviews the basic physical concepts in MR imaging, describes commonly measured tissue parameters in quantitative MR imaging, and presents the major available pulse sequences used for quantitative MR imaging, with a focus on the hierarchical organization of these sequences. © RSNA, 2017.

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

    NASA Astrophysics Data System (ADS)

    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.

  10. Quantitative photoacoustic elasticity and viscosity imaging for cirrhosis detection

    NASA Astrophysics Data System (ADS)

    Wang, Qian; Shi, Yujiao; Yang, Fen; Yang, Sihua

    2018-05-01

    Elasticity and viscosity assessments are essential for understanding and characterizing the physiological and pathological states of tissue. In this work, by establishing a photoacoustic (PA) shear wave model, an approach for quantitative PA elasticity imaging based on measurement of the rise time of the thermoelastic displacement was developed. Thus, using an existing PA viscoelasticity imaging method that features a phase delay measurement, quantitative PA elasticity imaging and viscosity imaging can be obtained in a simultaneous manner. The method was tested and validated by imaging viscoelastic agar phantoms prepared at different agar concentrations, and the imaging data were in good agreement with rheometry results. Ex vivo experiments on liver pathological models demonstrated the capability for cirrhosis detection, and the results were consistent with the corresponding histological results. This method expands the scope of conventional PA imaging and has potential to become an important alternative imaging modality.

  11. Quantitative comparison of 3D third harmonic generation and fluorescence microscopy images.

    PubMed

    Zhang, Zhiqing; Kuzmin, Nikolay V; Groot, Marie Louise; de Munck, Jan C

    2018-01-01

    Third harmonic generation (THG) microscopy is a label-free imaging technique that shows great potential for rapid pathology of brain tissue during brain tumor surgery. However, the interpretation of THG brain images should be quantitatively linked to images of more standard imaging techniques, which so far has been done qualitatively only. We establish here such a quantitative link between THG images of mouse brain tissue and all-nuclei-highlighted fluorescence images, acquired simultaneously from the same tissue area. For quantitative comparison of a substantial pair of images, we present here a segmentation workflow that is applicable for both THG and fluorescence images, with a precision of 91.3 % and 95.8 % achieved respectively. We find that the correspondence between the main features of the two imaging modalities amounts to 88.9 %, providing quantitative evidence of the interpretation of dark holes as brain cells. Moreover, 80 % bright objects in THG images overlap with nuclei highlighted in the fluorescence images, and they are 2 times smaller than the dark holes, showing that cells of different morphologies can be recognized in THG images. We expect that the described quantitative comparison is applicable to other types of brain tissue and with more specific staining experiments for cell type identification. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Cardiovascular and pulmonary dynamics by quantitative imaging

    NASA Technical Reports Server (NTRS)

    Wood, E. H.

    1976-01-01

    The accuracy and range of studies on cardiovascular and pulmonary functions can be greatly facilitated if the motions of the underlying organ systems throughout individual cycles can be directly visualized and readily measured with minimum or preferably no effect on these motions. Achievement of this objective requires development of techniques for quantitative noninvasive or minimally invasive dynamic and stop-action imaging of the organ systems. A review of advances in dynamic quantitative imaging of moving organs reveals that the revolutionary value of cross-sectional and three-dimensional images produced by various types of radiant energy such as X-rays and gamma rays, positrons, electrons, protons, light, and ultrasound for clinical diagnostic and biomedical research applications is just beginning to be realized. The fabrication of a clinically useful cross-section reconstruction device with sensing capabilities for both anatomical structural composition and chemical composition may be possible and awaits future development.

  13. Quantitative magnetic resonance imaging in traumatic brain injury.

    PubMed

    Bigler, E D

    2001-04-01

    Quantitative neuroimaging has now become a well-established method for analyzing magnetic resonance imaging in traumatic brain injury (TBI). A general review of studies that have examined quantitative changes following TBI is presented. The consensus of quantitative neuroimaging studies is that most brain structures demonstrate changes in volume or surface area after injury. The patterns of atrophy are consistent with the generalized nature of brain injury and diffuse axonal injury. Various clinical caveats are provided including how quantitative neuroimaging findings can be used clinically and in predicting rehabilitation outcome. The future of quantitative neuroimaging also is discussed.

  14. Diagnosis of breast cancer biopsies using quantitative phase imaging

    NASA Astrophysics Data System (ADS)

    Majeed, Hassaan; Kandel, Mikhail E.; Han, Kevin; Luo, Zelun; Macias, Virgilia; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

    2015-03-01

    The standard practice in the histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope. The pathologist looks at certain morphological features, visible under the stain, to diagnose whether a tumor is benign or malignant. This determination is made based on qualitative inspection making it subject to investigator bias. Furthermore, since this method requires a microscopic examination by the pathologist it suffers from low throughput. A quantitative, label-free and high throughput method for detection of these morphological features from images of tissue biopsies is, hence, highly desirable as it would assist the pathologist in making a quicker and more accurate diagnosis of cancers. We present here preliminary results showing the potential of using quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated optical path length maps of unstained breast tissue biopsies using Spatial Light Interference Microscopy (SLIM). As a first step towards diagnosis based on quantitative phase imaging, we carried out a qualitative evaluation of the imaging resolution and contrast of our label-free phase images. These images were shown to two pathologists who marked the tumors present in tissue as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on H&E stained tissue images and the number of agreements were counted. In our experiment, the agreement between SLIM and H&E based diagnosis was measured to be 88%. Our preliminary results demonstrate the potential and promise of SLIM for a push in the future towards quantitative, label-free and high throughput diagnosis.

  15. Biomarkers in sarcoidosis.

    PubMed

    Chopra, Amit; Kalkanis, Alexandros; Judson, Marc A

    2016-11-01

    Numerous biomarkers have been evaluated for the diagnosis, assessment of disease activity, prognosis, and response to treatment in sarcoidosis. In this report, we discuss the clinical and research utility of several biomarkers used to evaluate sarcoidosis. Areas covered: The sarcoidosis biomarkers discussed include serologic tests, imaging studies, identification of inflammatory cells and genetic analyses. Literature was obtained from medical databases including PubMed and Web of Science. Expert commentary: Most of the biomarkers examined in sarcoidosis are not adequately specific or sensitive to be used in isolation to make clinical decisions. However, several sarcoidosis biomarkers have an important role in the clinical management of sarcoidosis when they are coupled with clinical data including the results of other biomarkers.

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

    PubMed

    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 < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise 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.

  17. The Effects of Exercise on Cardiovascular Biomarkers: New Insights, Recent Data, and Applications.

    PubMed

    Che, Lin; Li, Dong

    2017-01-01

    The benefit of regular exercise or physical activity with appropriate intensity on improving cardiopulmonary function and endurance has long been accepted with less controversy. The challenge remains, however, quantitatively evaluate the effect of exercise on cardiovascular health due in part to the amount and intensity of exercise varies widely plus lack of effective, robust and efficient biomarker evaluation systems. Better evaluating the overall function of biomarker and validate biomarkers utility in cardiovascular health should improve the evidence regarding the benefit or the effect of exercise or physical activity on cardiovascular health, in turn increasing the efficiency of the biomarker on individuals with mild to moderate cardiovascular risk. In this review, beyond traditional cytokines, chemokines and inflammatory factors, we systemic reviewed the latest novel biomarkers in metabolomics, genomics, proteomics, and molecular imaging mainly focus on heart health, as well as cardiovascular diseases such as atherosclerosis and ischemic heart disease. Furthermore, we highlight the state-of-the-art biomarker developing techniques and its application in the field of heart health. Finally, we discuss the clinical relevance of physical activity and exercise on key biomarkers in molecular basis and practical considerations.

  18. Quantitative magnetic resonance micro-imaging methods for pharmaceutical research.

    PubMed

    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.

  19. Nanoparticle Enhancement Cascade for Sensitive Multiplex Measurements of Biomarkers in Complex Fluids with Surface Plasmon Resonance Imaging.

    PubMed

    Hendriks, Jan; Stojanovic, Ivan; Schasfoort, Richard B M; Saris, Daniël B F; Karperien, Marcel

    2018-06-05

    There is a large unmet need for reliable biomarker measurement systems for clinical application. Such systems should meet challenging requirements for large scale use, including a large dynamic detection range, multiplexing capacity, and both high specificity and sensitivity. More importantly, these requirements need to apply to complex biological samples, which require extensive quality control. In this paper, we present the development of an enhancement detection cascade for surface plasmon resonance imaging (SPRi). The cascade applies an antibody sandwich assay, followed by neutravidin and a gold nanoparticle enhancement for quantitative biomarker measurements in small volumes of complex fluids. We present a feasibility study both in simple buffers and in spiked equine synovial fluid with four cytokines, IL-1β, IL-6, IFN-γ, and TNF-α. Our enhancement cascade leads to an antibody dependent improvement in sensitivity up to 40 000 times, resulting in a limit of detection as low as 50 fg/mL and a dynamic detection range of more than 7 logs. Additionally, measurements at these low concentrations are highly reliable with intra- and interassay CVs between 2% and 20%. We subsequently showed this assay is suitable for multiplex measurements with good specificity and limited cross-reactivity. Moreover, we demonstrated robust detection of IL-6 and IL-1β in spiked undiluted equine synovial fluid with small variation compared to buffer controls. In addition, the availability of real time measurements provides extensive quality control opportunities, essential for clinical applications. Therefore, we consider this method is suitable for broad application in SPRi for multiplex biomarker detection in both research and clinical settings.

  20. 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.

    PubMed

    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

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

    NASA Astrophysics Data System (ADS)

    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.

  2. High-Throughput Quantitation of Proline Betaine in Foods and Suitability as a Valid Biomarker for Citrus Consumption.

    PubMed

    Lang, Roman; Lang, Tatjana; Bader, Matthias; Beusch, Anja; Schlagbauer, Verena; Hofmann, Thomas

    2017-03-01

    Proline betaine has been proposed as a candidate dietary biomarker for citrus intake. To validate its suitability as a dietary biomarker and to gain insight into the range of this per-methylated amino acid in foods and beverages, a quick and accurate stable isotope dilution assay was developed for quantitative high-throughput HILIC-MS/MS screening of proline betaine in foods and urine after solvent-mediated matrix precipitation. Quantitative analysis of a variety of foods confirmed substantial amounts of proline betaine in citrus juices (140-1100 mg/L) and revealed high abundance in tubers of the vegetable Stachys affinis, also known as Chinese artichocke (∼700 mg/kg). Seafood including clams, shrimp, and lobster contained limited amounts (1-95 mg/kg), whereas only traces were detected in fish, cuttlefish, fresh meat, dairy products, fresh vegetable (<3 mg/kg), coffee, tea, beer, and wine (<7 mg/L). The human excretion profiles of proline betaine in urine were comparable when common portions of orange juice or fried Stachys tubers were consumed. Neither mussels nor beer provided enough proline betaine to detect significant differences between morning urine samples collected before and after consumption. As Stachys is a rather rare vegetable and not part of peoples' daily diet, the data reported here will help to monitor the subject's compliance in future nutritional human studies on citrus products or the exclusion of citrus products in the wash-out phase of an intervention study. Moreover, proline betaine measurement can contribute to the establishment of a toolbox of valid dietary biomarkers reflecting wider aspects of diet to assess metabolic profiles as measures of dietary exposure and indicators of dietary patterns, dietary changes, or effectiveness of dietary interventions.

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

    PubMed

    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.

  4. Quantitative single-molecule imaging by confocal laser scanning microscopy.

    PubMed

    Vukojevic, Vladana; Heidkamp, Marcus; Ming, Yu; Johansson, Björn; Terenius, Lars; Rigler, Rudolf

    2008-11-25

    A new approach to quantitative single-molecule imaging by confocal laser scanning microscopy (CLSM) is presented. It relies on fluorescence intensity distribution to analyze the molecular occurrence statistics captured by digital imaging and enables direct determination of the number of fluorescent molecules and their diffusion rates without resorting to temporal or spatial autocorrelation analyses. Digital images of fluorescent molecules were recorded by using fast scanning and avalanche photodiode detectors. In this way the signal-to-background ratio was significantly improved, enabling direct quantitative imaging by CLSM. The potential of the proposed approach is demonstrated by using standard solutions of fluorescent dyes, fluorescently labeled DNA molecules, quantum dots, and the Enhanced Green Fluorescent Protein in solution and in live cells. The method was verified by using fluorescence correlation spectroscopy. The relevance for biological applications, in particular, for live cell imaging, is discussed.

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

    PubMed

    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.

  6. A new method to evaluate image quality of CBCT images quantitatively without observers

    PubMed Central

    Shimizu, Mayumi; Okamura, Kazutoshi; Yoshida, Shoko; Weerawanich, Warangkana; Tokumori, Kenji; Jasa, Gainer R; Yoshiura, Kazunori

    2017-01-01

    Objectives: To develop an observer-free method for quantitatively evaluating the image quality of CBCT images by applying just-noticeable difference (JND). Methods: We used two test objects: (1) a Teflon (polytetrafluoroethylene) plate phantom attached to a dry human mandible; and (2) a block phantom consisting of a Teflon step phantom and an aluminium step phantom. These phantoms had holes with different depths. They were immersed in water and scanned with a CB MercuRay (Hitachi Medical Corporation, Tokyo, Japan) at tube voltages of 120 kV, 100 kV, 80 kV and 60 kV. Superimposed images of the phantoms with holes were used for evaluation. The number of detectable holes was used as an index of image quality. In detecting holes quantitatively, the threshold grey value (ΔG), which differentiated holes from the background, was calculated using a specific threshold (the JND), and we extracted the holes with grey values above ΔG. The indices obtained by this quantitative method (the extracted hole values) were compared with the observer evaluations (the observed hole values). In addition, the contrast-to-noise ratio (CNR) of the shallowest detectable holes and the deepest undetectable holes were measured to evaluate the contribution of CNR to detectability. Results: The results of this evaluation method corresponded almost exactly with the evaluations made by observers. The extracted hole values reflected the influence of different tube voltages. All extracted holes had an area with a CNR of ≥1.5. Conclusions: This quantitative method of evaluating CBCT image quality may be more useful and less time-consuming than evaluation by observation. PMID:28045343

  7. Precise quantitation of 136 urinary proteins by LC/MRM-MS using stable isotope labeled peptides as internal standards for biomarker discovery and/or verification studies.

    PubMed

    Percy, Andrew J; Yang, Juncong; Hardie, Darryl B; Chambers, Andrew G; Tamura-Wells, Jessica; Borchers, Christoph H

    2015-06-15

    Spurred on by the growing demand for panels of validated disease biomarkers, increasing efforts have focused on advancing qualitative and quantitative tools for more highly multiplexed and sensitive analyses of a multitude of analytes in various human biofluids. In quantitative proteomics, evolving strategies involve the use of the targeted multiple reaction monitoring (MRM) mode of mass spectrometry (MS) with stable isotope-labeled standards (SIS) used for internal normalization. Using that preferred approach with non-invasive urine samples, we have systematically advanced and rigorously assessed the methodology toward the precise quantitation of the largest, multiplexed panel of candidate protein biomarkers in human urine to date. The concentrations of the 136 proteins span >5 orders of magnitude (from 8.6 μg/mL to 25 pg/mL), with average CVs of 8.6% over process triplicate. Detailed here is our quantitative method, the analysis strategy, a feasibility application to prostate cancer samples, and a discussion of the utility of this method in translational studies. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Biomarkers for Radiation Pneumonitis Using Noninvasive Molecular Imaging.

    PubMed

    Medhora, Meetha; Haworth, Steven; Liu, Yu; Narayanan, Jayashree; Gao, Feng; Zhao, Ming; Audi, Said; Jacobs, Elizabeth R; Fish, Brian L; Clough, Anne V

    2016-08-01

    Our goal is to develop minimally invasive biomarkers for predicting radiation-induced lung injury before symptoms develop. Currently, there are no biomarkers that can predict radiation pneumonitis. Radiation damage to the whole lung is a serious risk in nuclear accidents or in radiologic terrorism. Our previous studies have shown that a single dose of 15 Gy of x-rays to the thorax causes severe pneumonitis in rats by 6-8 wk. We have also developed a mitigator for radiation pneumonitis and fibrosis that can be started as late as 5 wk after radiation. We used 2 functional SPECT probes in vivo in irradiated rat lungs. Regional pulmonary perfusion was measured by injection of (99m)Tc-macroaggregated albumin. Perfused volume was determined by comparing the volume of distribution of (99m)Tc-macroaggregated albumin to the anatomic lung volume obtained by small-animal CT. A second probe, (99m)Tc-labeled Duramycin, which binds to apoptotic cells, was used to measure pulmonary cell death in the same rat model. The perfused volume of lung was decreased by about 25% at 1, 2, and 3 wk after receipt of 15 Gy, and (99m)Tc-Duramycin uptake was more than doubled at 2 and 3 wk. There was no change in body weight, breathing rate, or lung histology between irradiated and nonirradiated rats at these times. Pulmonary vascular resistance and vascular permeability measured in isolated perfused lungs ex vivo increased at 2 wk after 15 Gy of irradiation. Our results suggest that SPECT biomarkers have the potential to predict radiation injury to the lungs before substantial functional or histologic damage is observed. Early prediction of radiation pneumonitis in time to initiate mitigation will benefit those exposed to radiation in the context of therapy, accidents, or terrorism. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

  9. Quantitative Ultrasound Imaging Using Acoustic Backscatter Coefficients.

    NASA Astrophysics Data System (ADS)

    Boote, Evan Jeffery

    Current clinical ultrasound scanners render images which have brightness levels related to the degree of backscattered energy from the tissue being imaged. These images offer the interpreter a qualitative impression of the scattering characteristics of the tissue being examined, but due to the complex factors which affect the amplitude and character of the echoed acoustic energy, it is difficult to make quantitative assessments of scattering nature of the tissue, and thus, difficult to make precise diagnosis when subtle disease effects are present. In this dissertation, a method of data reduction for determining acoustic backscatter coefficients is adapted for use in forming quantitative ultrasound images of this parameter. In these images, the brightness level of an individual pixel corresponds to the backscatter coefficient determined for the spatial position represented by that pixel. The data reduction method utilized rigorously accounts for extraneous factors which affect the scattered echo waveform and has been demonstrated to accurately determine backscatter coefficients under a wide range of conditions. The algorithms and procedures used to form backscatter coefficient images are described. These were tested using tissue-mimicking phantoms which have regions of varying scattering levels. Another phantom has a fat-mimicking layer for testing these techniques under more clinically relevant conditions. Backscatter coefficient images were also formed of in vitro human liver tissue. A clinical ultrasound scanner has been adapted for use as a backscatter coefficient imaging platform. The digital interface between the scanner and the computer used for data reduction are described. Initial tests, using phantoms are presented. A study of backscatter coefficient imaging of in vivo liver was performed using several normal, healthy human subjects.

  10. Evaluating biomarkers for prognostic enrichment of clinical trials.

    PubMed

    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.

  11. Optical Ptychographic Microscope for Quantitative Bio-Mechanical Imaging

    NASA Astrophysics Data System (ADS)

    Anthony, Nicholas; Cadenazzi, Guido; Nugent, Keith; Abbey, Brian

    The role that mechanical forces play in biological processes such as cell movement and death is becoming of significant interest to further develop our understanding of the inner workings of cells. The most common method used to obtain stress information is photoelasticity which maps a samples birefringence, or its direction dependent refractive indices, using polarized light. However this method only provides qualitative data and for stress information to be useful quantitative data is required. Ptychography is a method for quantitatively determining the phase of a samples complex transmission function. The technique relies upon the collection of multiple overlapping coherent diffraction patterns from laterally displaced points on the sample. The overlap of measurement points provides complementary information that significantly aids in the reconstruction of the complex wavefield exiting the sample and allows for quantitative imaging of weakly interacting specimens. Here we describe recent advances at La Trobe University Melbourne on achieving quantitative birefringence mapping using polarized light ptychography with applications in cell mechanics. Australian Synchrotron, ARC Centre of Excellence for Advanced Molecular Imaging.

  12. The Potential Role of Sensory Testing, Skin Biopsy, and Functional Brain Imaging as Biomarkers in Chronic Pain Clinical Trials: IMMPACT Considerations.

    PubMed

    Smith, Shannon M; Dworkin, Robert H; Turk, Dennis C; Baron, Ralf; Polydefkis, Michael; Tracey, Irene; Borsook, David; Edwards, Robert R; Harris, Richard E; Wager, Tor D; Arendt-Nielsen, Lars; Burke, Laurie B; Carr, Daniel B; Chappell, Amy; Farrar, John T; Freeman, Roy; Gilron, Ian; Goli, Veeraindar; Haeussler, Juergen; Jensen, Troels; Katz, Nathaniel P; Kent, Jeffrey; Kopecky, Ernest A; Lee, David A; Maixner, William; Markman, John D; McArthur, Justin C; McDermott, Michael P; Parvathenani, Lav; Raja, Srinivasa N; Rappaport, Bob A; Rice, Andrew S C; Rowbotham, Michael C; Tobias, Jeffrey K; Wasan, Ajay D; Witter, James

    2017-07-01

    Valid and reliable biomarkers can play an important role in clinical trials as indicators of biological or pathogenic processes or as a signal of treatment response. Currently, there are no biomarkers for pain qualified by the U.S. Food and Drug Administration or the European Medicines Agency for use in clinical trials. This article summarizes an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials meeting in which 3 potential biomarkers were discussed for use in the development of analgesic treatments: 1) sensory testing, 2) skin punch biopsy, and 3) brain imaging. The empirical evidence supporting the use of these tests is described within the context of the 4 categories of biomarkers: 1) diagnostic, 2) prognostic, 3) predictive, and 4) pharmacodynamic. Although sensory testing, skin punch biopsy, and brain imaging are promising tools for pain in clinical trials, additional evidence is needed to further support and standardize these tests for use as biomarkers in pain clinical trials. The applicability of sensory testing, skin biopsy, and brain imaging as diagnostic, prognostic, predictive, and pharmacodynamic biomarkers for use in analgesic treatment trials is considered. Evidence in support of their use and outlining problems is presented, as well as a call for further standardization and demonstrations of validity and reliability. Copyright © 2017 American Pain Society. All rights reserved.

  13. Quantitative analysis of cardiovascular MR images.

    PubMed

    van der Geest, R J; de Roos, A; van der Wall, E E; Reiber, J H

    1997-06-01

    The diagnosis of cardiovascular disease requires the precise assessment of both morphology and function. Nearly all aspects of cardiovascular function and flow can be quantified nowadays with fast magnetic resonance (MR) imaging techniques. Conventional and breath-hold cine MR imaging allow the precise and highly reproducible assessment of global and regional left ventricular function. During the same examination, velocity encoded cine (VEC) MR imaging provides measurements of blood flow in the heart and great vessels. Quantitative image analysis often still relies on manual tracing of contours in the images. Reliable automated or semi-automated image analysis software would be very helpful to overcome the limitations associated with the manual and tedious processing of the images. Recent progress in MR imaging of the coronary arteries and myocardial perfusion imaging with contrast media, along with the further development of faster imaging sequences, suggest that MR imaging could evolve into a single technique ('one stop shop') for the evaluation of many aspects of heart disease. As a result, it is very likely that the need for automated image segmentation and analysis software algorithms will further increase. In this paper the developments directed towards the automated image analysis and semi-automated contour detection for cardiovascular MR imaging are presented.

  14. Automatic segmentation of lumbar vertebrae in CT images

    NASA Astrophysics Data System (ADS)

    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.

  15. [Biomarkers and imaging for diagnosis and stratification of rheumatoid arthritis and spondylarthritis in the BMBF consortium ArthroMark].

    PubMed

    Häupl, T; Skapenko, A; Hoppe, B; Skriner, K; Burkhardt, H; Poddubnyy, D; Ohrndorf, S; Sewerin, P; Mansmann, U; Stuhlmüller, B; Schulze-Koops, H; Burmester, G-R

    2018-05-01

    Rheumatic diseases are among the most common chronic inflammatory disorders. Besides severe pain and progressive destruction of the joints, rheumatoid arthritis (RA), spondyloarthritides (SpA) and psoriatic arthritis (PsA) impair working ability, reduce quality of life and if treated insufficiently may enhance mortality. With the introduction of biologics to treat these diseases, the demand for biomarkers of early diagnosis and therapeutic stratification has been growing continuously. The main goal of the consortium ArthroMark is to identify new biomarkers and to apply modern imaging technologies for diagnosis, follow-up assessment and stratification of patients with RA, SpA and PsA. With the development of new biomarkers for these diseases, the ArthroMark project contributes to research in chronic diseases of the musculoskeletal system. The cooperation between different national centers will utilize site-specific resources, such as biobanks and clinical studies for sharing and gainful networking of individual core areas in biomarker analysis. Joint data management and harmonization of data assessment as well as best practice characterization of patients with new imaging technologies will optimize quality of marker validation.

  16. Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network.

    PubMed

    Newitt, David C; Malyarenko, Dariya; Chenevert, Thomas L; Quarles, C Chad; Bell, Laura; Fedorov, Andriy; Fennessy, Fiona; Jacobs, Michael A; Solaiyappan, Meiyappan; Hectors, Stefanie; Taouli, Bachir; Muzi, Mark; Kinahan, Paul E; Schmainda, Kathleen M; Prah, Melissa A; Taber, Erin N; Kroenke, Christopher; Huang, Wei; Arlinghaus, Lori R; Yankeelov, Thomas E; Cao, Yue; Aryal, Madhava; Yen, Yi-Fen; Kalpathy-Cramer, Jayashree; Shukla-Dave, Amita; Fung, Maggie; Liang, Jiachao; Boss, Michael; Hylton, Nola

    2018-01-01

    Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and in vivo breast studies were evaluated for two ([Formula: see text]) and four ([Formula: see text]) [Formula: see text]-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo [Formula: see text], with relative biases [Formula: see text] ([Formula: see text]) and [Formula: see text] (phantom [Formula: see text]) but with higher deviations in ADC at the lowest phantom ADC values. In vivo [Formula: see text] concordance was good, with typical biases of [Formula: see text] to 3% but higher for online maps. Multiple b -value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for [Formula: see text] in vivo data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.

  17. Dual function microscope for quantitative DIC and birefringence imaging

    NASA Astrophysics Data System (ADS)

    Li, Chengshuai; Zhu, Yizheng

    2016-03-01

    A spectral multiplexing interferometry (SXI) method is presented for integrated birefringence and phase gradient measurement on label-free biological specimens. With SXI, the retardation and orientation of sample birefringence are simultaneously encoded onto two separate spectral carrier waves, generated by a crystal retarder oriented at a specific angle. Thus sufficient information for birefringence determination can be obtained from a single interference spectrum, eliminating the need for multiple acquisitions with mechanical rotation or electrical modulation. In addition, with the insertion of a Nomarski prism, the setup can then acquire quantitative differential interference contrast images. Red blood cells infected by malaria parasites are imaged for birefringence retardation as well as phase gradient. The results demonstrate that the SXI approach can achieve both quantitative phase imaging and birefringence imaging with a single, high-sensitivity system.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Harmon, S; Perk, T; Lin, C

    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 articulatedmore » 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

  19. Circulating RNAs as new biomarkers for detecting pancreatic cancer

    PubMed Central

    Kishikawa, Takahiro; Otsuka, Motoyuki; Ohno, Motoko; Yoshikawa, Takeshi; Takata, Akemi; Koike, Kazuhiko

    2015-01-01

    Pancreatic cancer remains difficult to treat and has a high mortality rate. It is difficult to diagnose early, mainly due to the lack of screening imaging modalities and specific biomarkers. Consequently, it is important to develop biomarkers that enable the detection of early stage tumors. Emerging evidence is accumulating that tumor cells release substantial amounts of RNA into the bloodstream that strongly resist RNases in the blood and are present at sufficient levels for quantitative analyses. These circulating RNAs are upregulated in the serum and plasma of cancer patients, including those with pancreatic cancer, compared with healthy controls. The majority of RNA biomarker studies have assessed circulating microRNAs (miRs), which are often tissue-specific. There are few reports of the tumor-specific upregulation of other types of small non-coding RNAs (ncRNAs), such as small nucleolar RNAs and Piwi-interacting RNAs. Long ncRNAs (lncRNAs), such as HOTAIR and MALAT1, in the serum/plasma of pancreatic cancer patients have also been reported as diagnostic and prognostic markers. Among tissue-derived RNAs, some miRs show increased expression even in pre-cancerous tissues, and their expression profiles may allow for the discrimination between a chronic inflammatory state and carcinoma. Additionally, some miRs and lncRNAs have been reported with significant alterations in expression according to disease progression, and they may thus represent potential candidate diagnostic or prognostic biomarkers that may be used to evaluate patients once detection methods in peripheral blood are well established. Furthermore, recent innovations in high-throughput sequencing techniques have enabled the discovery of unannotated tumor-associated ncRNAs and tumor-specific alternative splicing as novel and specific biomarkers of cancers. Although much work is required to clarify the release mechanism, origin of tumor-specific circulating RNAs, and selectivity of carrier complexes

  20. Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

    PubMed

    Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József

    2017-02-05

    Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Quantitative phase imaging and complex field reconstruction by pupil modulation differential phase contrast

    PubMed Central

    Lu, Hangwen; Chung, Jaebum; Ou, Xiaoze; Yang, Changhuei

    2016-01-01

    Differential phase contrast (DPC) is a non-interferometric quantitative phase imaging method achieved by using an asymmetric imaging procedure. We report a pupil modulation differential phase contrast (PMDPC) imaging method by filtering a sample’s Fourier domain with half-circle pupils. A phase gradient image is captured with each half-circle pupil, and a quantitative high resolution phase image is obtained after a deconvolution process with a minimum of two phase gradient images. Here, we introduce PMDPC quantitative phase image reconstruction algorithm and realize it experimentally in a 4f system with an SLM placed at the pupil plane. In our current experimental setup with the numerical aperture of 0.36, we obtain a quantitative phase image with a resolution of 1.73μm after computationally removing system aberrations and refocusing. We also extend the depth of field digitally by 20 times to ±50μm with a resolution of 1.76μm. PMID:27828473

  2. The potential role of sensory testing, skin biopsy, and functional brain imaging as biomarkers in chronic pain clinical trials: IMMPACT considerations

    PubMed Central

    Smith, Shannon M.; Dworkin, Robert H.; Turk, Dennis C.; Baron, Ralf; Polydefkis, Michael; Tracey, Irene; Borsook, David; Edwards, Robert R.; Harris, Richard E.; Wager, Tor D.; Arendt-Nielsen, Lars; Burke, Laurie B.; Carr, Daniel B.; Chappell, Amy; Farrar, John T.; Freeman, Roy; Gilron, Ian; Goli, Veeraindar; Haeussler, Juergen; Jensen, Troels; Katz, Nathaniel P.; Kent, Jeffrey; Kopecky, Ernest A.; Lee, David A.; Maixner, William; Markman, John D.; McArthur, Justin C.; McDermott, Michael P.; Parvathenani, Lav; Raja, Srinivasa N.; Rappaport, Bob A.; Rice, Andrew S. C.; Rowbotham, Michael C.; Tobias, Jeffrey K.; Wasan, Ajay D.; Witter, James

    2017-01-01

    Valid and reliable biomarkers can play an important role in clinical trials as indicators of biological or pathogenic processes or as a signal of treatment response. Currently, there are no biomarkers for pain qualified by the US Food and Drug Administration or the European Medicines Agency for use in clinical trials. This article summarizes an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) meeting in which 3 potential biomarkers were discussed for use in the development of analgesic treatments: (1) sensory testing, (2), skin punch biopsy, and (3) brain imaging. The empirical evidence supporting the use of these tests is described within the context of the 4 categories of biomarkers: (1) diagnostic, (2) prognostic, (3) predictive, and (4) pharmacodynamic. Although sensory testing, skin punch biopsy, and brain imaging are promising tools for pain in clinical trials, additional evidence is needed to further support and standardize these tests for use as biomarkers in pain clinical trials. PMID:28254585

  3. Quantum dot nanoprobe-based quantitative analysis for prostate cancer (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Kang, Benedict J.; Jang, Gun Hyuk; Park, Sungwook; Lee, Kwan Hyi

    2016-09-01

    Prostate cancer causes one of the leading cancer-related deaths among the Caucasian adult males in Europe and the United State of America. However, it has a high recovery rate indicating when a proper treatment is delivered to a patient. There are cases of over- or under-treatments which exacerbate the disease states indicating the importance of proper therapeutic approach depending on stage of the disease. Recognition of the unmet needs has raised a need for stratification of the disease. There have been attempts to stratify based on biomarker expression patterns in the course of disease progression. To closely observe the biomarker expression patterns, we propose the use of quantitative imaging method by using fabricated quantum dot-based nanoprobe to quantify biomarker expression on the surface of prostate cancer cells. To characterize the cell line and analyze the biomarker levels, cluster of differentiation 44 (CD 44), prostate specific membrane antigen (PSMA), and epithelial cell adhesion molecule (EpCAM) are used. Each selected biomarker per cell line has been quantified from which we established a signature of biomarkers of a prostate cancer cell line.

  4. Prognostic biomarkers in osteoarthritis

    PubMed Central

    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

  5. Quantitative assessment of dynamic PET imaging data in cancer imaging.

    PubMed

    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.

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

    NASA Technical Reports Server (NTRS)

    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.

  7. On Quantitative Biomarkers of VNS Therapy Using EEG and ECG Signals.

    PubMed

    Ravan, Maryam; Sabesan, Shivkumar; D'Cruz, O'Neill

    2017-02-01

    The goal of this work is to objectively evaluate the effectiveness of neuromodulation therapies, specifically, Vagus nerve stimulation (VNS) in reducing the severity of seizures in patients with medically refractory epilepsy. Using novel quantitative features obtained from combination of electroencephalographic (EEG) and electrocardiographic (ECG) signals around seizure events in 16 patients who underwent implantation of closed-loop VNS therapy system, namely AspireSR, we evaluated if automated delivery of VNS at the time of seizure onset reduces the severity of seizures by reducing EEG spatial synchronization as well as the duration and magnitude of heart rate increase. Unsupervised classification was subsequently applied to test the discriminative ability and validity of these features to measure responsiveness to VNS therapy. Results of application of this methodology to compare 105 pre-VNS treatment and 107 post-VNS treatment seizures revealed that seizures that were acutely stimulated using VNS had a reduced ictal spread as well as reduced impact on cardiovascular function compared to the ones that occurred prior to any treatment. Furthermore, application of an unsupervised fuzzy-c-mean classifier to evaluate the ability of the combined EEG-ECG based features to classify pre and post-treatment seizures achieved a classification accuracy of 85.85%. These results indicate the importance of timely delivery of VNS to reduce seizure severity and thus help achieve better seizure control for patients with epilepsy. The proposed set of quantitative features could be used as potential biomarkers for predicting long-term response to VNS therapy.

  8. Quantitative imaging of bilirubin by photoacoustic microscopy

    NASA Astrophysics Data System (ADS)

    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.

  9. Dependence of quantitative accuracy of CT perfusion imaging on system parameters

    NASA Astrophysics Data System (ADS)

    Li, Ke; Chen, Guang-Hong

    2017-03-01

    Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

  10. Accuracy of a remote quantitative image analysis in the whole slide images.

    PubMed

    Słodkowska, Janina; Markiewicz, Tomasz; Grala, Bartłomiej; Kozłowski, Wojciech; Papierz, Wielisław; Pleskacz, Katarzyna; Murawski, Piotr

    2011-03-30

    The rationale for choosing a remote quantitative method supporting a diagnostic decision requires some empirical studies and knowledge on scenarios including valid telepathology standards. The tumours of the central nervous system [CNS] are graded on the base of the morphological features and the Ki-67 labelling Index [Ki-67 LI]. Various methods have been applied for Ki-67 LI estimation. Recently we have introduced the Computerized Analysis of Medical Images [CAMI] software for an automated Ki-67 LI counting in the digital images. Aims of our study was to explore the accuracy and reliability of a remote assessment of Ki-67 LI with CAMI software applied to the whole slide images [WSI]. The WSI representing CNS tumours: 18 meningiomas and 10 oligodendrogliomas were stored on the server of the Warsaw University of Technology. The digital copies of entire glass slides were created automatically by the Aperio ScanScope CS with objective 20x or 40x. Aperio's Image Scope software provided functionality for a remote viewing of WSI. The Ki-67 LI assessment was carried on within 2 out of 20 selected fields of view (objective 40x) representing the highest labelling areas in each WSI. The Ki-67 LI counting was performed by 3 various methods: 1) the manual reading in the light microscope - LM, 2) the automated counting with CAMI software on the digital images - DI , and 3) the remote quantitation on the WSIs - as WSI method. The quality of WSIs and technical efficiency of the on-line system were analysed. The comparative statistical analysis was performed for the results obtained by 3 methods of Ki-67 LI counting. The preliminary analysis showed that in 18% of WSI the results of Ki-67 LI differed from those obtained in other 2 methods of counting when the quality of the glass slides was below the standard range. The results of our investigations indicate that the remote automated Ki-67 LI analysis performed with the CAMI algorithm on the whole slide images of meningiomas and

  11. Modulation of renal oxygenation and perfusion in rat kidney monitored by quantitative diffusion and blood oxygen level dependent magnetic resonance imaging on a clinical 1.5T platform.

    PubMed

    Jerome, Neil P; Boult, Jessica K R; Orton, Matthew R; d'Arcy, James; Collins, David J; Leach, Martin O; Koh, Dow-Mu; Robinson, Simon P

    2016-10-03

    To investigate the combined use of intravoxel incoherent motion (IVIM) diffusion-weighted (DW) and blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) to assess rat renal function using a 1.5T clinical platform. Multiple b-value DW and BOLD MR images were acquired from adult rats using a parallel clinical coil arrangement, enabling quantitation of the apparent diffusion coefficient (ADC), IVIM-derived diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f), and the transverse relaxation time T 2 *, for whole kidney, renal cortex, and medulla. Following the acquisition of two baseline datasets to assess measurement repeatability, images were acquired following i.v. administration of hydralazine, furosemide, or angiotensin II for up to 40 min. Excellent repeatability (CoV <10 %) was observed for ADC, D, f and T 2 * measured over the whole kidney. Hydralazine induced a marked and significant (p < 0.05) reduction in whole kidney ADC, D, and T 2 *, and a significant (p < 0.05) increase in D* and f. Furosemide significantly (p < 0.05) increased whole kidney ADC, D, and T 2 *. A more variable response to angiotensin II was determined, with a significant (p < 0.05) increase in medulla D* and significant (p < 0.05) reduction in whole kidney T 2 * established. Multiparametric MRI, incorporating quantitation of IVIM DWI and BOLD biomarkers and performed on a clinical platform, can be used to monitor the acute effects of vascular and tubular modulating drugs on rat kidney function in vivo. Clinical adoption of such functional imaging biomarkers can potentially inform on treatment effects in patients with renal dysfunction.

  12. Widefield quantitative multiplex surface enhanced Raman scattering imaging in vivo

    NASA Astrophysics Data System (ADS)

    McVeigh, Patrick Z.; Mallia, Rupananda J.; Veilleux, Israel; Wilson, Brian C.

    2013-04-01

    In recent years numerous studies have shown the potential advantages of molecular imaging in vitro and in vivo using contrast agents based on surface enhanced Raman scattering (SERS), however the low throughput of traditional point-scanned imaging methodologies have limited their use in biological imaging. In this work we demonstrate that direct widefield Raman imaging based on a tunable filter is capable of quantitative multiplex SERS imaging in vivo, and that this imaging is possible with acquisition times which are orders of magnitude lower than achievable with comparable point-scanned methodologies. The system, designed for small animal imaging, has a linear response from (0.01 to 100 pM), acquires typical in vivo images in <10 s, and with suitable SERS reporter molecules is capable of multiplex imaging without compensation for spectral overlap. To demonstrate the utility of widefield Raman imaging in biological applications, we show quantitative imaging of four simultaneous SERS reporter molecules in vivo with resulting probe quantification that is in excellent agreement with known quantities (R2>0.98).

  13. Novel MRI-derived quantitative biomarker for cardiac function applied to classifying ischemic cardiomyopathy within a Bayesian rule learning framework

    NASA Astrophysics Data System (ADS)

    Menon, Prahlad G.; Morris, Lailonny; Staines, Mara; Lima, Joao; Lee, Daniel C.; Gopalakrishnan, Vanathi

    2014-03-01

    index (LV-ESVI). This improved to 91.9% with inclusion of the RMS-P2PD biomarker and was congruent with improvements in both sensitivity for classifying patients and specificity for identifying asymptomatic controls from 82.6% up to 95.7%. RMS-P2PD, when contrasted against a collective normal reference, is a promising biomarker to investigate further in its utility for identifying quantitative signs of pathological endocardial function which may boost standard image makers as precursors of declining cardiac performance.

  14. Radiomics biomarkers for accurate tumor progression prediction of oropharyngeal cancer

    NASA Astrophysics Data System (ADS)

    Hadjiiski, Lubomir; Chan, Heang-Ping; Cha, Kenny H.; Srinivasan, Ashok; Wei, Jun; Zhou, Chuan; Prince, Mark; Papagerakis, Silvana

    2017-03-01

    Accurate tumor progression prediction for oropharyngeal cancers is crucial for identifying patients who would best be treated with optimized treatment and therefore minimize the risk of under- or over-treatment. An objective decision support system that can merge the available radiomics, histopathologic and molecular biomarkers in a predictive model based on statistical outcomes of previous cases and machine learning may assist clinicians in making more accurate assessment of oropharyngeal tumor progression. In this study, we evaluated the feasibility of developing individual and combined predictive models based on quantitative image analysis from radiomics, histopathology and molecular biomarkers for oropharyngeal tumor progression prediction. With IRB approval, 31, 84, and 127 patients with head and neck CT (CT-HN), tumor tissue microarrays (TMAs) and molecular biomarker expressions, respectively, were collected. For 8 of the patients all 3 types of biomarkers were available and they were sequestered in a test set. The CT-HN lesions were automatically segmented using our level sets based method. Morphological, texture and molecular based features were extracted from CT-HN and TMA images, and selected features were merged by a neural network. The classification accuracy was quantified using the area under the ROC curve (AUC). Test AUCs of 0.87, 0.74, and 0.71 were obtained with the individual predictive models based on radiomics, histopathologic, and molecular features, respectively. Combining the radiomics and molecular models increased the test AUC to 0.90. Combining all 3 models increased the test AUC further to 0.94. This preliminary study demonstrates that the individual domains of biomarkers are useful and the integrated multi-domain approach is most promising for tumor progression prediction.

  15. Automatic vertebral bodies detection of x-ray images using invariant multiscale template matching

    NASA Astrophysics Data System (ADS)

    Sharifi Sarabi, Mona; Villaroman, Diane; Beckett, Joel; Attiah, Mark; Marcus, Logan; Ahn, Christine; Babayan, Diana; Gaonkar, Bilwaj; Macyszyn, Luke; Raghavendra, Cauligi

    2017-03-01

    Lower back pain and pathologies related to it are one of the most common results for a referral to a neurosurgical clinic in the developed and the developing world. Quantitative evaluation of these pathologies is a challenge. Image based measurements of angles/vertebral heights and disks could provide a potential quantitative biomarker for tracking and measuring these pathologies. Detection of vertebral bodies is a key element and is the focus of the current work. From the variety of medical imaging techniques, MRI and CT scans have been typically used for developing image segmentation methods. However, CT scans are known to give a large dose of x-rays, increasing cancer risk [8]. MRI can be substituted for CTs when the risk is high [8] but are difficult to obtain in smaller facilities due to cost and lack of expertise in the field [2]. X-rays provide another option with its ability to control the x-ray dosage, especially for young people, and its accessibility for smaller facilities. Hence, the ability to create quantitative biomarkers from x-ray data is especially valuable. Here, we develop a multiscale template matching, inspired by [9], to detect centers of vertebral bodies from x-ray data. The immediate application of such detection lies in developing quantitative biomarkers and in querying similar images in a database. Previously, shape similarity classification methods have been used to address this problem, but these are challenging to use in the presence of variation due to gross pathology and even subtle effects [1].

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

    PubMed

    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 < .01) with changes in forced expiratory volume in 1 second (r = 0.70), forced vital capacity (r = 0.84), and %VV (r = 0.56). A significant (P < .01) positive 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

  17. Quantitative MR imaging of pulmonary hypertension: A practical approach to the current state of the art

    PubMed Central

    Swift, Andrew J.; Wild, Jim M.; Nagle, Scott K.; Roldán-Alzate, Alejandro; François, Christopher J.; Fain, Sean; Johnson, Kevin; Capener, Dave; van Beek, Edwin J. R.; Kiely, David G.; Wang, Kang; Schiebler, Mark L.

    2014-01-01

    Pulmonary hypertension (PH) is a condition of varied aetiology, commonly associated with a poor clinical outcome. Patients are categorised on the basis of pathophysiological, clinical, radiological and therapeutic similarities. Pulmonary arterial hypertension (PAH) is often diagnosed late in its disease course with outcome dependent on aetiology, disease severity and response to treatment. Recent advances in quantitative MR imaging allow for a better initial characterization and measurement of the morphologic and flow related changes that accompany the response of the heart-lung axis to prolonged elevation of pulmonary arterial pressure and resistance and provide a reproducible, comprehensive and non-invasive means of assessing the course of the disease and response to treatment. Typical features of pulmonary arterial hypertension (PAH) occur primarily as a result of increased pulmonary vascular resistance and resultant increased RV afterload. Several MRI derived diagnostic markers have emerged, such as ventricular mass index (VMI), interventricular septal configuration and average pulmonary artery velocity having reported diagnostic accuracy similar to Doppler echocardiography. Furthermore, prognostic markers have been identified with independent predictive value for identification of treatment failure. Such markers include: large right ventricular end-diastolic volume index (RVEDVI), low left ventricular end diastolic volume index (LVEDVI), low right ventricular ejection fraction (RVEF) and relative area change of the pulmonary trunk. MRI is ideally suited to longitudinal follow-up of patients with PAH due to its non-invasive nature, high reproducibility and has the advantage over other biomarkers in PAH due to its sensitivity to change in morphological, functional and flow related parameters. Further study the role of MR imaging as a biomarker in the clinical environment is warranted. PMID:24552882

  18. Quantitative imaging of protein targets in the human brain with PET

    NASA Astrophysics Data System (ADS)

    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

  19. Imaging-based biomarkers of cognitive performance in older adults constructed via high-dimensional pattern regression applied to MRI and PET.

    PubMed

    Wang, Ying; Goh, Joshua O; Resnick, Susan M; Davatzikos, Christos

    2013-01-01

    In this study, we used high-dimensional pattern regression methods based on structural (gray and white matter; GM and WM) and functional (positron emission tomography of regional cerebral blood flow; PET) brain data to identify cross-sectional imaging biomarkers of cognitive performance in cognitively normal older adults from the Baltimore Longitudinal Study of Aging (BLSA). We focused on specific components of executive and memory domains known to decline with aging, including manipulation, semantic retrieval, long-term memory (LTM), and short-term memory (STM). For each imaging modality, brain regions associated with each cognitive domain were generated by adaptive regional clustering. A relevance vector machine was adopted to model the nonlinear continuous relationship between brain regions and cognitive performance, with cross-validation to select the most informative brain regions (using recursive feature elimination) as imaging biomarkers and optimize model parameters. Predicted cognitive scores using our regression algorithm based on the resulting brain regions correlated well with actual performance. Also, regression models obtained using combined GM, WM, and PET imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with LTM showing stronger correlation with the temporal lobe than STM. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. The PET modality had higher contribution to most cognitive domains except manipulation, which had higher WM contribution from the superior longitudinal fasciculus and the genu of the corpus callosum. These findings based on machine-learning methods demonstrate the importance of combining structural and functional imaging data in understanding complex cognitive mechanisms and also their potential usage as biomarkers that predict cognitive status.

  20. Quantitative subsurface analysis using frequency modulated thermal wave imaging

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  2. Utility of Traditional Circulating and Imaging-Based Cardiac Biomarkers in Patients with Predialysis CKD

    PubMed Central

    Colbert, Gates; Jain, Nishank; de Lemos, James A.

    2015-01-01

    Cardiac biomarkers, such as cardiac troponin T (cTnT), brain natriuretic peptide (BNP), and N-terminal-pro-BNP (NT-pro-BNP), are commonly used to diagnose acute coronary syndrome and congestive heart failure exacerbation in symptomatic patients. Levels of these biomarkers are frequently chronically elevated in asymptomatic patients with ESRD who are receiving maintenance dialysis. Other imaging biomarkers commonly encountered in nephrologists’ clinical practice, such as coronary artery calcium measured by computed tomography, left ventricular hypertrophy, and carotid intima-media thickness, are also frequently abnormal in asymptomatic patients with ESRD. This article critically reviews the limited observational data on associations between cTnT, BNP, NT-pro-BNP, coronary artery calcium, left ventricular hypertrophy, and carotid intima-media thickness with cardiovascular events and death in non–dialysis-dependent patients with CKD. Although sufficient evidence suggests that these biomarkers may be used for prognostication, the diagnostic utility of cTnT, BNP, and NT-pro-BNP remain challenging in patients with CKD. Decreased renal clearance may affect the plasma levels of these biomarkers, and upper reference limits were originally derived in patients without CKD. Until better data are available, higher cutoffs, or a rise in level compared with previous values, have been proposed to help distinguish acute myocardial infarction from chronic elevations of cTnT in symptomatic patients with CKD. Additionally, it is not known whether these biomarkers are modifiable and amenable to interventions that could change hard clinical outcomes in patients with CKD not yet undergoing long-term dialysis. PMID:25403922

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

    Cancer.gov

    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.

  4. Qualitative and quantitative mass spectrometry imaging of drugs and metabolites

    PubMed Central

    Lietz, Christopher B.; Gemperline, Erin; Li, Lingjun

    2013-01-01

    Mass spectrometric imaging (MSI) has rapidly increased its presence in the pharmaceutical sciences. While quantitative whole-body autoradiography and microautoradiography are the traditional techniques for molecular imaging of drug delivery and metabolism, MSI provides advantageous specificity that can distinguish the parent drug from metabolites and modified endogenous molecules. This review begins with the fundamentals of MSI sample preparation/ionization, and then moves on to both qualitative and quantitative applications with special emphasis on drug discovery and delivery. Cutting-edge investigations on sub-cellular imaging and endogenous signaling peptides are also highlighted, followed by perspectives on emerging technology and the path for MSI to become a routine analysis technique. PMID:23603211

  5. Quantitative Imaging in Laboratory: Fast Kinetics and Fluorescence Quenching

    ERIC Educational Resources Information Center

    Cumberbatch, Tanya; Hanley, Quentin S.

    2007-01-01

    The process of quantitative imaging, which is very commonly used in laboratory, is shown to be very useful for studying the fast kinetics and fluorescence quenching of many experiments. The imaging technique is extremely cheap and hence can be used in many absorption and luminescence experiments.

  6. Isolating specific cell and tissue compartments from 3D images for quantitative regional distribution analysis using novel computer algorithms.

    PubMed

    Fenrich, Keith K; Zhao, Ethan Y; Wei, Yuan; Garg, Anirudh; Rose, P Ken

    2014-04-15

    Isolating specific cellular and tissue compartments from 3D image stacks for quantitative distribution analysis is crucial for understanding cellular and tissue physiology under normal and pathological conditions. Current approaches are limited because they are designed to map the distributions of synapses onto the dendrites of stained neurons and/or require specific proprietary software packages for their implementation. To overcome these obstacles, we developed algorithms to Grow and Shrink Volumes of Interest (GSVI) to isolate specific cellular and tissue compartments from 3D image stacks for quantitative analysis and incorporated these algorithms into a user-friendly computer program that is open source and downloadable at no cost. The GSVI algorithm was used to isolate perivascular regions in the cortex of live animals and cell membrane regions of stained spinal motoneurons in histological sections. We tracked the real-time, intravital biodistribution of injected fluorophores with sub-cellular resolution from the vascular lumen to the perivascular and parenchymal space following a vascular microlesion, and mapped the precise distributions of membrane-associated KCC2 and gephyrin immunolabeling in dendritic and somatic regions of spinal motoneurons. Compared to existing approaches, the GSVI approach is specifically designed for isolating perivascular regions and membrane-associated regions for quantitative analysis, is user-friendly, and free. The GSVI algorithm is useful to quantify regional differences of stained biomarkers (e.g., cell membrane-associated channels) in relation to cell functions, and the effects of therapeutic strategies on the redistributions of biomolecules, drugs, and cells in diseased or injured tissues. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. Simultaneous imaging of cellular morphology and multiple biomarkers using an acousto-optic tunable filter-based bright field microscope.

    PubMed

    Wachman, Elliot S; Geyer, Stanley J; Recht, Joel M; Ward, Jon; Zhang, Bill; Reed, Murray; Pannell, Chris

    2014-05-01

    An acousto-optic tunable filter (AOTF)-based multispectral imaging microscope system allows the combination of cellular morphology and multiple biomarker stainings on a single microscope slide. We describe advances in AOTF technology that have greatly improved spectral purity, field uniformity, and image quality. A multispectral imaging bright field microscope using these advances demonstrates pathology results that have great potential for clinical use.

  8. Quantitative HDL Proteomics Identifies Peroxiredoxin-6 as a Biomarker of Human Abdominal Aortic Aneurysm

    PubMed Central

    Burillo, Elena; Jorge, Inmaculada; Martínez-López, Diego; Camafeita, Emilio; Blanco-Colio, Luis Miguel; Trevisan-Herraz, Marco; Ezkurdia, Iakes; Egido, Jesús; Michel, Jean-Baptiste; Meilhac, Olivier; Vázquez, Jesús; Martin-Ventura, Jose Luis

    2016-01-01

    High-density lipoproteins (HDLs) are complex protein and lipid assemblies whose composition is known to change in diverse pathological situations. Analysis of the HDL proteome can thus provide insight into the main mechanisms underlying abdominal aortic aneurysm (AAA) and potentially detect novel systemic biomarkers. We performed a multiplexed quantitative proteomics analysis of HDLs isolated from plasma of AAA patients (N = 14) and control study participants (N = 7). Validation was performed by western-blot (HDL), immunohistochemistry (tissue), and ELISA (plasma). HDL from AAA patients showed elevated expression of peroxiredoxin-6 (PRDX6), HLA class I histocompatibility antigen (HLA-I), retinol-binding protein 4, and paraoxonase/arylesterase 1 (PON1), whereas α-2 macroglobulin and C4b-binding protein were decreased. The main pathways associated with HDL alterations in AAA were oxidative stress and immune-inflammatory responses. In AAA tissue, PRDX6 colocalized with neutrophils, vascular smooth muscle cells, and lipid oxidation. Moreover, plasma PRDX6 was higher in AAA (N = 47) than in controls (N = 27), reflecting increased systemic oxidative stress. Finally, a positive correlation was recorded between PRDX6 and AAA diameter. The analysis of the HDL proteome demonstrates that redox imbalance is a major mechanism in AAA, identifying the antioxidant PRDX6 as a novel systemic biomarker of AAA. PMID:27934969

  9. Ultrasound introscopic image quantitative characteristics for medical diagnosis

    NASA Astrophysics Data System (ADS)

    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.

  10. Portable Biomarker Detection with Magnetic Nanotags

    PubMed Central

    Hall, Drew A.; Wang, Shan X.; Murmann, Boris; Gaster, Richard S.

    2012-01-01

    This paper presents a hand-held, portable biosensor platform for quantitative biomarker measurement. By combining magnetic nanoparticle (MNP) tags with giant magnetoresistive (GMR) spin-valve sensors, the hand-held platform achieves highly sensitive (picomolar) and specific biomarker detection in less than 20 minutes. The rapid analysis and potential low cost make this technology ideal for point-of-care (POC) diagnostics. Furthermore, this platform is able to detect multiple biomarkers simultaneously in a single assay, creating a promising diagnostic tool for a vast number of applications. PMID:22495252

  11. The Use of Quantitative SPECT/CT Imaging to Assess Residual Limb Health

    DTIC Science & Technology

    2016-10-01

    AWARD NUMBER: W81XWH-15-1-0669 TITLE: The Use of Quantitative SPECT/CT Imaging to Assess Residual Limb Health PRINCIPAL INVESTIGATOR...3. DATES COVERED 30 Sep 2015 - 29 Sep 2016 4. TITLE AND SUBTITLE The Use of Quantitative SPECT/CT Imaging to Assess Residual Limb Health 5a...amputation and subsequently evaluate the utility of non-invasive imaging for evaluating the impact of next-generation socket technologies on the health of

  12. Qualitative and quantitative mass spectrometry imaging of drugs and metabolites.

    PubMed

    Lietz, Christopher B; Gemperline, Erin; Li, Lingjun

    2013-07-01

    Mass spectrometric imaging (MSI) has rapidly increased its presence in the pharmaceutical sciences. While quantitative whole-body autoradiography and microautoradiography are the traditional techniques for molecular imaging of drug delivery and metabolism, MSI provides advantageous specificity that can distinguish the parent drug from metabolites and modified endogenous molecules. This review begins with the fundamentals of MSI sample preparation/ionization, and then moves on to both qualitative and quantitative applications with special emphasis on drug discovery and delivery. Cutting-edge investigations on sub-cellular imaging and endogenous signaling peptides are also highlighted, followed by perspectives on emerging technology and the path for MSI to become a routine analysis technique. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Quantitative energy-filtered TEM imaging of interfaces

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bentley, J.; Kenik, E.A.; Siangchaew, K.

    Quantitative elemental mapping by inner shell core-loss energy-filtered transmission electron microscopy (TEM) with a Gatan Imaging Filter (GIF) interfaced to a Philips CM30 TEM operated with a LaB{sub 6} filament at 300 kV has been applied to interfaces in a range of materials. In sensitized type 304L stainless steel aged 15 h at 600{degrees}C, grain-boundary Cr depletion occurs between Cr-rich intergranular M{sub 23}C{sub 6} particles. Images of net Cr L{sub 23} intensity show segregation profiles that agree quantitatively with focused-probe spectrum-line measurements recorded with a Gatan PEELS on a Philips EM400T/FEG (0.8 nA in 2-nm-diam probe) of the same regions.more » Rare-earth oxide additives that are used for the liquid-phase sintering of Si{sub 3}N{sub 4} generate second phases of complex composition at grain boundaries and edges. These grain boundary phases often control corrosion, crack growth and creep damage behavior. High resolution imaging has been widely and with focused probes can be compromised by beam damage, but elemental mapping by EFTEM appears not to cause appreciable beam damage.« less

  14. Quantitative image quality evaluation of MR images using perceptual difference models

    PubMed Central

    Miao, Jun; Huo, Donglai; Wilson, David L.

    2008-01-01

    The authors are using a perceptual difference model (Case-PDM) to quantitatively evaluate image quality of the thousands of test images which can be created when optimizing fast magnetic resonance (MR) imaging strategies and reconstruction techniques. In this validation study, they compared human evaluation of MR images from multiple organs and from multiple image reconstruction algorithms to Case-PDM and similar models. The authors found that Case-PDM compared very favorably to human observers in double-stimulus continuous-quality scale and functional measurement theory studies over a large range of image quality. The Case-PDM threshold for nonperceptible differences in a 2-alternative forced choice study varied with the type of image under study, but was ≈1.1 for diffuse image effects, providing a rule of thumb. Ordering the image quality evaluation models, we found in overall Case-PDM ≈ IDM (Sarnoff Corporation) ≈ SSIM [Wang et al. IEEE Trans. Image Process. 13, 600–612 (2004)] > mean squared error ≈ NR [Wang et al. (2004) (unpublished)] > DCTune (NASA) > IQM (MITRE Corporation). The authors conclude that Case-PDM is very useful in MR image evaluation but that one should probably restrict studies to similar images and similar processing, normally not a limitation in image reconstruction studies. PMID:18649487

  15. SU-F-R-24: Identifying Prognostic Imaging Biomarkers in Early Stage Lung Cancer Using Radiomics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zeng, X; Wu, J; Cui, Y

    2016-06-15

    Purpose: Patients diagnosed with early stage lung cancer have favorable outcomes when treated with surgery or stereotactic radiotherapy. However, a significant proportion (∼20%) of patients will develop metastatic disease and eventually die of the disease. The purpose of this work is to identify quantitative imaging biomarkers from CT for predicting overall survival in early stage lung cancer. Methods: In this institutional review board-approved HIPPA-compliant retrospective study, we retrospectively analyzed the diagnostic CT scans of 110 patients with early stage lung cancer. Data from 70 patients were used for training/discovery purposes, while those of remaining 40 patients were used for independentmore » validation. We extracted 191 radiomic features, including statistical, histogram, morphological, and texture features. Cox proportional hazard regression model, coupled with the least absolute shrinkage and selection operator (LASSO), was used to predict overall survival based on the radiomic features. Results: The optimal prognostic model included three image features from the Law’s feature and wavelet texture. In the discovery cohort, this model achieved a concordance index or CI=0.67, and it separated the low-risk from high-risk groups in predicting overall survival (hazard ratio=2.72, log-rank p=0.007). In the independent validation cohort, this radiomic signature achieved a CI=0.62, and significantly stratified the low-risk and high-risk groups in terms of overall survival (hazard ratio=2.20, log-rank p=0.042). Conclusion: We identified CT imaging characteristics associated with overall survival in early stage lung cancer. If prospectively validated, this could potentially help identify high-risk patients who might benefit from adjuvant systemic therapy.« less

  16. Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.

    PubMed

    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 <0.05 in all cases). Quantitative imaging analysis of renal sonograms in children with 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.

  17. Towards real-time quantitative optical imaging for surgery

    NASA Astrophysics Data System (ADS)

    Gioux, Sylvain

    2017-07-01

    There is a pressing clinical need to provide image guidance during surgery. Currently, assessment of tissue that needs to be resected or avoided is performed subjectively leading to a large number of failures, patient morbidity and increased healthcare cost. Because near-infrared (NIR) optical imaging is safe, does not require contact, and can provide relatively deep information (several mm), it offers unparalleled capabilities for providing image guidance during surgery. In this work, we introduce a novel concept that enables the quantitative imaging of endogenous molecular information over large fields-of-view. Because this concept can be implemented in real-time, it is amenable to provide video-rate endogenous information during surgery.

  18. Automated assessment of imaging biomarkers for the PanCan lung cancer risk prediction model with validation on NLST data

    NASA Astrophysics Data System (ADS)

    Wiemker, Rafael; Sevenster, Merlijn; MacMahon, Heber; Li, Feng; Dalal, Sandeep; Tahmasebi, Amir; Klinder, Tobias

    2017-03-01

    The imaging biomarkers EmphysemaPresence and NoduleSpiculation are crucial inputs for most models aiming to predict the risk of indeterminate pulmonary nodules detected at CT screening. To increase reproducibility and to accelerate screening workflow it is desirable to assess these biomarkers automatically. Validation on NLST images indicates that standard histogram measures are not sufficient to assess EmphysemaPresence in screenees. However, automatic scoring of bulla-resembling low attenuation areas can achieve agreement with experts with close to 80% sensitivity and specificity. NoduleSpiculation can be automatically assessed with similar accuracy. We find a dedicated spiculi tracing score to slightly outperform generic combinations of texture features with classifiers.

  19. Subsurface imaging and cell refractometry using quantitative phase/ shear-force feedback microscopy

    NASA Astrophysics Data System (ADS)

    Edward, Kert; Farahi, Faramarz

    2009-10-01

    Over the last few years, several novel quantitative phase imaging techniques have been developed for the study of biological cells. However, many of these techniques are encumbered by inherent limitations including 2π phase ambiguities and diffraction limited spatial resolution. In addition, subsurface information in the phase data is not exploited. We hereby present a novel quantitative phase imaging system without 2 π ambiguities, which also allows for subsurface imaging and cell refractometry studies. This is accomplished by utilizing simultaneously obtained shear-force topography information. We will demonstrate how the quantitative phase and topography data can be used for subsurface and cell refractometry analysis and will present results for a fabricated structure and a malaria infected red blood cell.

  20. Quantitative imaging of aggregated emulsions.

    PubMed

    Penfold, Robert; Watson, Andrew D; Mackie, Alan R; Hibberd, David J

    2006-02-28

    Noise reduction, restoration, and segmentation methods are developed for the quantitative structural analysis in three dimensions of aggregated oil-in-water emulsion systems imaged by fluorescence confocal laser scanning microscopy. Mindful of typical industrial formulations, the methods are demonstrated for concentrated (30% volume fraction) and polydisperse emulsions. Following a regularized deconvolution step using an analytic optical transfer function and appropriate binary thresholding, novel application of the Euclidean distance map provides effective discrimination of closely clustered emulsion droplets with size variation over at least 1 order of magnitude. The a priori assumption of spherical nonintersecting objects provides crucial information to combat the ill-posed inverse problem presented by locating individual particles. Position coordinates and size estimates are recovered with sufficient precision to permit quantitative study of static geometrical features. In particular, aggregate morphology is characterized by a novel void distribution measure based on the generalized Apollonius problem. This is also compared with conventional Voronoi/Delauney analysis.

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

    NASA Astrophysics Data System (ADS)

    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.

  2. Iterative optimization method for design of quantitative magnetization transfer imaging experiments.

    PubMed

    Levesque, Ives R; Sled, John G; Pike, G Bruce

    2011-09-01

    Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging. Copyright © 2011 Wiley-Liss, Inc.

  3. Quantitative OCT and MRI biomarkers for the differentiation of cartilage degeneration.

    PubMed

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

    2016-04-01

    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.

  4. Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization

    NASA Astrophysics Data System (ADS)

    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.

  5. Real-time quantitative fluorescence imaging using a single snapshot optical properties technique for neurosurgical guidance

    NASA Astrophysics Data System (ADS)

    Valdes, Pablo A.; Angelo, Joseph; Gioux, Sylvain

    2015-03-01

    Fluorescence imaging has shown promise as an adjunct to improve the extent of resection in neurosurgery and oncologic surgery. Nevertheless, current fluorescence imaging techniques do not account for the heterogeneous attenuation effects of tissue optical properties. In this work, we present a novel imaging system that performs real time quantitative fluorescence imaging using Single Snapshot Optical Properties (SSOP) imaging. We developed the technique and performed initial phantom studies to validate the quantitative capabilities of the system for intraoperative feasibility. Overall, this work introduces a novel real-time quantitative fluorescence imaging method capable of being used intraoperatively for neurosurgical guidance.

  6. 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.

    PubMed

    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.

  7. Quantitative oxygen concentration imaging in toluene atmospheres using Dual Imaging with Modeling Evaluation

    NASA Astrophysics Data System (ADS)

    Ehn, Andreas; Jonsson, Malin; Johansson, Olof; Aldén, Marcus; Bood, Joakim

    2013-01-01

    Fluorescence lifetimes of toluene as a function of oxygen concentration in toluene/nitrogen/oxygen mixtures have been measured at room temperature using picosecond-laser excitation of the S1-S0 transition at 266 nm. The data satisfy the Stern-Volmer relation with high accuracy, providing an updated value of the Stern-Volmer slope. A newly developed fluorescence lifetime imaging scheme, called Dual Imaging with Modeling Evaluation (DIME), is evaluated and successfully demonstrated for quantitative oxygen concentration imaging in toluene-seeded O2/N2 gas mixtures.

  8. Quantitative oxygen concentration imaging in toluene atmospheres using Dual Imaging with Modeling Evaluation

    NASA Astrophysics Data System (ADS)

    Ehn, Andreas; Jonsson, Malin; Johansson, Olof; Aldén, Marcus; Bood, Joakim

    2012-12-01

    Fluorescence lifetimes of toluene as a function of oxygen concentration in toluene/nitrogen/oxygen mixtures have been measured at room temperature using picosecond-laser excitation of the S1-S0 transition at 266 nm. The data satisfy the Stern-Volmer relation with high accuracy, providing an updated value of the Stern-Volmer slope. A newly developed fluorescence lifetime imaging scheme, called Dual Imaging with Modeling Evaluation (DIME), is evaluated and successfully demonstrated for quantitative oxygen concentration imaging in toluene-seeded O2/N2 gas mixtures.

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

    PubMed

    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.

  10. Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

    PubMed

    Baños, Núria; Perez-Moreno, Alvaro; Migliorelli, Federico; Triginer, Laura; Cobo, Teresa; Bonet-Carne, Elisenda; Gratacos, Eduard; Palacio, Montse

    2017-01-01

    Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant. © 2016 S. Karger AG, Basel.

  11. Clustering methods applied in the detection of Ki67 hot-spots in whole tumor slide images: an efficient way to characterize heterogeneous tissue-based biomarkers.

    PubMed

    Lopez, Xavier Moles; Debeir, Olivier; Maris, Calliope; Rorive, Sandrine; Roland, Isabelle; Saerens, Marco; Salmon, Isabelle; Decaestecker, Christine

    2012-09-01

    Whole-slide scanners allow the digitization of an entire histological slide at very high resolution. This new acquisition technique opens a wide range of possibilities for addressing challenging image analysis problems, including the identification of tissue-based biomarkers. In this study, we use whole-slide scanner technology for imaging the proliferating activity patterns in tumor slides based on Ki67 immunohistochemistry. Faced with large images, pathologists require tools that can help them identify tumor regions that exhibit high proliferating activity, called "hot-spots" (HSs). Pathologists need tools that can quantitatively characterize these HS patterns. To respond to this clinical need, the present study investigates various clustering methods with the aim of identifying Ki67 HSs in whole tumor slide images. This task requires a method capable of identifying an unknown number of clusters, which may be highly variable in terms of shape, size, and density. We developed a hybrid clustering method, referred to as Seedlink. Compared to manual HS selections by three pathologists, we show that Seedlink provides an efficient way of detecting Ki67 HSs and improves the agreement among pathologists when identifying HSs. Copyright © 2012 International Society for Advancement of Cytometry.

  12. MR Fingerprinting for Rapid Quantitative Abdominal Imaging

    PubMed Central

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

    2016-01-01

    Purpose To develop a magnetic resonance (MR) “fingerprinting” technique for quantitative abdominal imaging. Materials and Methods 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. Results 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). Conclusion A rapid technique for quantitative abdominal imaging was developed that

  13. MR Fingerprinting for Rapid Quantitative Abdominal Imaging.

    PubMed

    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

  14. Noninvasive quantitative documentation of cutaneous inflammation in vivo using spectral imaging

    NASA Astrophysics Data System (ADS)

    Stamatas, Georgios N.; Kollias, Nikiforos

    2006-02-01

    Skin inflammation is often accompanied by edema and erythema. While erythema is the result of capillary dilation and subsequent local increase of oxygenated hemoglobin (oxy-Hb) concentration, edema is characterized by an increase in extracellular fluid in the dermis leading to local tissue swelling. Edema and erythema are typically graded visually. In this work we tested the potential of spectral imaging as a non-invasive method for quantitative documentation of both the erythema and the edema reactions. As examples of dermatological conditions that exhibit skin inflammation we imaged patients suffering from acne, herpes zoster, and poison ivy rashes using a hyperspectral-imaging camera. Spectral images were acquired in the visible and near infrared part of the spectrum, where oxy-Hb and water demonstrate absorption bands. The values of apparent concentrations of oxy-Hb and water were calculated based on an algorithm that takes into account spectral contributions of deoxy-hemoglobin, melanin, and scattering. In each case examined concentration maps of oxy-Hb and water can be constructed that represent quantitative visualizations of the intensity and extent of erythema and edema correspondingly. In summary, we demonstrate that spectral imaging can be used in dermatology to quantitatively document parameters relating to skin inflammation. Applications may include monitoring of disease progression as well as efficacy of treatments.

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

    PubMed

    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

  16. Evaluation of high intensity focused ultrasound ablation of prostate tumor with hyperpolarized 13C imaging biomarkers

    NASA Astrophysics Data System (ADS)

    Lee, Jessie E.; Diederich, Chris J.; Salgaonkar, Vasant A.; Bok, Robert; Taylor, Andrew G.; Kurhanewicz, John

    2015-03-01

    Real-time hyperpolarized (HP) 13C MR can be utilized during high-intensity focal ultrasound (HIFU) therapy to improve treatment delivery strategies, provide treatment verification, and thus reduce the need for more radical therapies for lowand intermediate-risk prostate cancers. The goal is to develop imaging biomarkers specific to thermal therapies of prostate cancer using HIFU, and to predict the success of thermal coagulation and identify tissues potentially sensitized to adjuvant treatment by sub-ablative hyperthermic heat doses. Mice with solid prostate tumors received HIFU treatment (5.6 MHz, 160W/cm2, 60 s), and the MR imaging follow-ups were performed on a wide-bore 14T microimaging system. 13C-labeled pyruvate and urea were used to monitor tumor metabolism and perfusion accordingly. After treatment, the ablated tumor tissue had a loss in metabolism and perfusion. In the regions receiving sub-ablative heat dose, a timedependent change in metabolism and perfusion was observed. The untreated regions behaved as a normal untreated TRAMP prostate tumor would. This promising preliminary study shows the potential of using 13C MR imaging as biomarkers of HIFU/thermal therapies.

  17. Biomarkers of response and resistance to antiangiogenic therapy

    PubMed Central

    Jain, Rakesh K.; Duda, Dan G.; Willett, Christopher G.; Sahani, Dushyant V.; Zhu, Andrew X.; Loeffler, Jay S.; Batchelor, Tracy T.; Sorensen, A. Gregory

    2011-01-01

    No validated biological markers (or biomarkers) currently exist for appropriately selecting patients with cancer for antiangiogenic therapy. Nor are there biomarkers identifying escape pathways that should be targeted after tumors develop resistance to a given antiangiogenic agent. A number of potential systemic, circulating, tissue and imaging biomarkers have emerged from recently completed phase I–III studies. Some of these are measured at baseline (for example VEGF polymorphisms), others are measured during treatment (such as hypertension, MRI-measured Ktrans, circulating angiogenic molecules or collagen IV), and all are mechanistically based. Some of these biomarkers might be pharmacodynamic (for example, increase in circulating VEGF, placental growth factor) while others have potential for predicting clinical benefit or identifying the escape pathways (for example, stromal-cell-derived factor 1α, interleukin-6). Most biomarkers are disease and/or agent specific and all of them need to be validated prospectively. We discuss the current challenges in establishing biomarkers of antiangiogenic therapy, define systemic, circulating, tissue and imaging biomarkers and their advantages and disadvantages, and comment on the future opportunities for validating biomarkers of antiangiogenic therapy. PMID:19483739

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

    NASA Astrophysics Data System (ADS)

    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.

  19. 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

    PubMed Central

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

    2018-01-01

    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 114mm3/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. PMID:29861868

  20. Image segmentation evaluation for very-large datasets

    NASA Astrophysics Data System (ADS)

    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.

  1. Susceptibility-Weighted Imaging and Quantitative Susceptibility Mapping in the Brain

    PubMed Central

    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

  2. Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

    PubMed

    Liu, Tianming; Lu, Jianfeng; Wang, Ye; Campbell, William A; Huang, Ling; Zhu, Jinmin; Xia, Weiming; Wong, Stephen T C

    2006-06-15

    An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.

  3. Genetic study of multimodal imaging Alzheimer's disease progression score implicates novel loci.

    PubMed

    Scelsi, Marzia A; Khan, Raiyan R; Lorenzi, Marco; Christopher, Leigh; Greicius, Michael D; Schott, Jonathan M; Ourselin, Sebastien; Altmann, Andre

    2018-05-30

    Identifying genetic risk factors underpinning different aspects of Alzheimer's disease has the potential to provide important insights into pathogenesis. Moving away from simple case-control definitions, there is considerable interest in using quantitative endophenotypes, such as those derived from imaging as outcome measures. Previous genome-wide association studies of imaging-derived biomarkers in sporadic late-onset Alzheimer's disease focused only on phenotypes derived from single imaging modalities. In contrast, we computed a novel multi-modal neuroimaging phenotype comprising cortical amyloid burden and bilateral hippocampal volume. Both imaging biomarkers were used as input to a disease progression modelling algorithm, which estimates the biomarkers' long-term evolution curves from population-based longitudinal data. Among other parameters, the algorithm computes the shift in time required to optimally align a subjects' biomarker trajectories with these population curves. This time shift serves as a disease progression score and it was used as a quantitative trait in a discovery genome-wide association study with n = 944 subjects from the Alzheimer's Disease Neuroimaging Initiative database diagnosed as Alzheimer's disease, mild cognitive impairment or healthy at the time of imaging. We identified a genome-wide significant locus implicating LCORL (rs6850306, chromosome 4; P = 1.03 × 10-8). The top variant rs6850306 was found to act as an expression quantitative trait locus for LCORL in brain tissue. The clinical role of rs6850306 in conversion from healthy ageing to mild cognitive impairment or Alzheimer's disease was further validated in an independent cohort comprising healthy, older subjects from the National Alzheimer's Coordinating Center database. Specifically, possession of a minor allele at rs6850306 was protective against conversion from mild cognitive impairment to Alzheimer's disease in the National Alzheimer's Coordinating Center cohort (hazard

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Patch, S; Hull, D; See, W

    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 signalmore » 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

  5. Quantitative analysis of rib movement based on dynamic chest bone images: preliminary results

    NASA Astrophysics Data System (ADS)

    Tanaka, R.; Sanada, S.; Oda, M.; Mitsutaka, M.; Suzuki, K.; Sakuta, K.; Kawashima, H.

    2014-03-01

    Rib movement during respiration is one of the diagnostic criteria in pulmonary impairments. In general, the rib movement is assessed in fluoroscopy. However, the shadows of lung vessels and bronchi overlapping ribs prevent accurate quantitative analysis of rib movement. Recently, an image-processing technique for separating bones from soft tissue in static chest radiographs, called "bone suppression technique", has been developed. Our purpose in this study was to evaluate the usefulness of dynamic bone images created by the bone suppression technique in quantitative analysis of rib movement. Dynamic chest radiographs of 10 patients were obtained using a dynamic flat-panel detector (FPD). Bone suppression technique based on a massive-training artificial neural network (MTANN) was applied to the dynamic chest images to create bone images. Velocity vectors were measured in local areas on the dynamic bone images, which formed a map. The velocity maps obtained with bone and original images for scoliosis and normal cases were compared to assess the advantages of bone images. With dynamic bone images, we were able to quantify and distinguish movements of ribs from those of other lung structures accurately. Limited rib movements of scoliosis patients appeared as reduced rib velocity vectors. Vector maps in all normal cases exhibited left-right symmetric distributions, whereas those in abnormal cases showed nonuniform distributions. In conclusion, dynamic bone images were useful for accurate quantitative analysis of rib movements: Limited rib movements were indicated as a reduction of rib movement and left-right asymmetric distribution on vector maps. Thus, dynamic bone images can be a new diagnostic tool for quantitative analysis of rib movements without additional radiation dose.

  6. Quantitative analysis for peripheral vascularity assessment based on clinical photoacoustic and ultrasound images

    NASA Astrophysics Data System (ADS)

    Murakoshi, Dai; Hirota, Kazuhiro; Ishii, Hiroyasu; Hashimoto, Atsushi; Ebata, Tetsurou; Irisawa, Kaku; Wada, Takatsugu; Hayakawa, Toshiro; Itoh, Kenji; Ishihara, Miya

    2018-02-01

    Photoacoustic (PA) imaging technology is expected to be applied to clinical assessment for peripheral vascularity. We started a clinical evaluation with the prototype PA imaging system we recently developed. Prototype PA imaging system was composed with in-house Q-switched Alexandrite laser system which emits short-pulsed laser with 750 nm wavelength, handheld ultrasound transducer where illumination optics were integrated and signal processing for PA image reconstruction implemented in the clinical ultrasound (US) system. For the purpose of quantitative assessment of PA images, an image analyzing function has been developed and applied to clinical PA images. In this analyzing function, vascularity derived from PA signal intensity ranged for prescribed threshold was defined as a numerical index of vessel fulfillment and calculated for the prescribed region of interest (ROI). Skin surface was automatically detected by utilizing B-mode image acquired simultaneously with PA image. Skinsurface position is utilized to place the ROI objectively while avoiding unwanted signals such as artifacts which were imposed due to melanin pigment in the epidermal layer which absorbs laser emission and generates strong PA signals. Multiple images were available to support the scanned image set for 3D viewing. PA images for several fingers of patients with systemic sclerosis (SSc) were quantitatively assessed. Since the artifact region is trimmed off in PA images, the visibility of vessels with rather low PA signal intensity on the 3D projection image was enhanced and the reliability of the quantitative analysis was improved.

  7. Quantitative fractography by digital image processing: NIH Image macro tools for stereo pair analysis and 3-D reconstruction.

    PubMed

    Hein, L R

    2001-10-01

    A set of NIH Image macro programs was developed to make qualitative and quantitative analyses from digital stereo pictures produced by scanning electron microscopes. These tools were designed for image alignment, anaglyph representation, animation, reconstruction of true elevation surfaces, reconstruction of elevation profiles, true-scale elevation mapping and, for the quantitative approach, surface area and roughness calculations. Limitations on time processing, scanning techniques and programming concepts are also discussed.

  8. PCA-based groupwise image registration for quantitative MRI.

    PubMed

    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

    2016-04-01

    Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as

  9. Diffraction enhance x-ray imaging for quantitative phase contrast studies

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Agrawal, A. K.; Singh, B., E-mail: balwants@rrcat.gov.in; Kashyap, Y. S.

    2016-05-23

    Conventional X-ray imaging based on absorption contrast permits limited visibility of feature having small density and thickness variations. For imaging of weakly absorbing material or materials possessing similar densities, a novel phase contrast imaging techniques called diffraction enhanced imaging has been designed and developed at imaging beamline Indus-2 RRCAT Indore. The technique provides improved visibility of the interfaces and show high contrast in the image forsmall density or thickness gradients in the bulk. This paper presents basic principle, instrumentation and analysis methods for this technique. Initial results of quantitative phase retrieval carried out on various samples have also been presented.

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

    PubMed

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

    2011-11-07

    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.

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

    PubMed

    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.

  12. Quantitative detection of liver-relevant biomarkers by SERS-immunolabeled gold nanoparticles

    NASA Astrophysics Data System (ADS)

    Payne, William Mark

    Lab-on-a-chip technology has the potential to rapidly change the way experiments are conducted in a variety of fields ranging from medicine to environmental science. Specifically, sensors, detectors, and monitoring devices are increasingly being miniaturized to perform many experiments or measurements on a single chip. In this research, we develop an immunolabeled gold nanoparticle complex capable of detecting liver organoid biomarkers intended for use in a microfluidic device. Human Serum Albumin (HSA) and alpha-Glutathione S-Transferase (alpha-GST) are liver biomarkers that indicate liver health and damage respectively. Herein we demonstrate detection of the liver organoid biomarkers at nanomolar concentrations. Through plasmonic coupling induced by aggregation in the presence of analyte, the SERS signal obtained from the nanoparticles is dramatically increased. Furthermore, detection is demonstrated in a simple fluidic device to show the feasibility of implementing an optimized SERS-immunolabeled nanoparticle for translational application.

  13. Pulmonary 3He Magnetic Resonance Imaging Biomarkers of Regional Airspace Enlargement in Alpha-1 Antitrypsin Deficiency.

    PubMed

    Lessard, Eric; Young, Heather M; Bhalla, Anurag; Pike, Damien; Sheikh, Khadija; McCormack, David G; Ouriadov, Alexei; Parraga, Grace

    2017-11-01

    Thoracic x-ray computed tomography (CT) and hyperpolarized 3 He magnetic resonance imaging (MRI) provide quantitative measurements of airspace enlargement in patients with emphysema. For patients with panlobular emphysema due to alpha-1 antitrypsin deficiency (AATD), sensitive biomarkers of disease progression and response to therapy have been difficult to develop and exploit, especially those biomarkers that correlate with outcomes like quality of life. Here, our objective was to generate and compare CT and diffusion-weighted inhaled-gas MRI measurements of emphysema including apparent diffusion coefficient (ADC) and MRI-derived mean linear intercept (L m ) in patients with AATD, chronic obstructive pulmonary disease (COPD) ex-smokers, and elderly never-smokers. We enrolled patients with AATD (n = 8; 57 ± 7 years), ex-smokers with COPD (n = 8; 77 ± 6 years), and a control group of never-smokers (n = 5; 64 ± 2 years) who underwent thoracic CT, MRI, spirometry, plethysmography, the St. George's Respiratory Questionnaire, and the 6-minute walk test during a single 2-hour visit. MRI-derived ADC, L m , surface-to-volume ratio, and ventilation defect percent were generated for the apical, basal, and whole lung as was CT lung area ≤-950 Hounsfield units (RA 950 ), low attenuating clusters, and airway count. In patients with AATD, there was a significantly different MRI-derived ADC (P = .03), L m (P < .0001), and surface-to-volume ratio (P < .0001), but not diffusing capacity of carbon monoxide, residual volume or total lung capacity, or CT RA 950 (P > .05) compared to COPD ex-smokers with a significantly different St. George's Respiratory Questionnaire. In this proof-of-concept demonstration, we evaluated CT and MRI lung emphysema measurements and observed significantly worse MRI biomarkers of emphysema in patients with AATD compared to patients with COPD, although CT RA 950 and diffusing capacity of carbon monoxide were not

  14. Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics.

    PubMed

    Magdalinou, N K; Noyce, A J; Pinto, R; Lindstrom, E; Holmén-Larsson, J; Holtta, M; Blennow, K; Morris, H R; Skillbäck, T; Warner, T T; Lees, A J; Pike, I; Ward, M; Zetterberg, H; Gobom, J

    2017-04-01

    Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than α-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive. To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls. CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set. 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism. Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as

  15. A novel approach for quantitative harmonization in PET.

    PubMed

    Namías, M; Bradshaw, T; Menezes, V O; Machado, M A D; Jeraj, R

    2018-05-04

    Positron emission tomography (PET) imaging allows for measurement of activity concentrations of a given radiotracer in vivo. The quantitative capabilities of PET imaging are particularly important in the context of monitoring response to treatment, where quantitative changes in tracer uptake could be used as a biomarker of treatment response. Reconstruction algorithms and settings have a significant impact on PET quantification. In this work we introduce a novel harmonization methodology requiring only a simple cylindrical phantom and show that it can match the performance of more complex harmonization approaches based on phantoms with spherical inserts. Resolution and noise measurements from cylindrical phantoms are used to simulate the spherical inserts from NEMA image quality phantoms. An optimization algorithm was used to find the optimal smoothing filters for the simulated NEMA phantom images to identify those that best harmonized the PET scanners. Our methodology was tested on seven different PET models from two manufacturers installed at five institutions. Our methodology is able to predict contrast recovery coefficients (CRCs) from NEMA phantoms with errors within  ±5.2% for CRCmax and  ±3.7% for CRCmean (limits of agreement  =  95%). After applying the proposed harmonization protocol, all the CRC values were within the tolerances from EANM. Quantitative harmonization in compliance with the EARL FDG-PET/CT accreditation program is achieved in a simpler way, without the need of NEMA phantoms. This may lead to simplified scanner harmonization workflows more accessible to smaller institutions.

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

    PubMed

    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.

  17. High resolution quantitative phase imaging of live cells with constrained optimization approach

    NASA Astrophysics Data System (ADS)

    Pandiyan, Vimal Prabhu; Khare, Kedar; John, Renu

    2016-03-01

    Quantitative phase imaging (QPI) aims at studying weakly scattering and absorbing biological specimens with subwavelength accuracy without any external staining mechanisms. Use of a reference beam at an angle is one of the necessary criteria for recording of high resolution holograms in most of the interferometric methods used for quantitative phase imaging. The spatial separation of the dc and twin images is decided by the reference beam angle and Fourier-filtered reconstructed image will have a very poor resolution if hologram is recorded below a minimum reference angle condition. However, it is always inconvenient to have a large reference beam angle while performing high resolution microscopy of live cells and biological specimens with nanometric features. In this paper, we treat reconstruction of digital holographic microscopy images as a constrained optimization problem with smoothness constraint in order to recover only complex object field in hologram plane even with overlapping dc and twin image terms. We solve this optimization problem by gradient descent approach iteratively and the smoothness constraint is implemented by spatial averaging with appropriate size. This approach will give excellent high resolution image recovery compared to Fourier filtering while keeping a very small reference angle. We demonstrate this approach on digital holographic microscopy of live cells by recovering the quantitative phase of live cells from a hologram recorded with nearly zero reference angle.

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

    PubMed

    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.

  19. Quantitative MR Imaging of Hepatic Steatosis: Validation in Ex Vivo Human Livers

    PubMed Central

    Bannas, Peter; Kramer, Harald; Hernando, Diego; Agni, Rashmi; Cunningham, Ashley M.; Mandal, Rakesh; Motosugi, Utaroh; Sharma, Samir D.; del Rio, Alejandro Munoz; Fernandez, Luis; Reeder, Scott B.

    2015-01-01

    Emerging magnetic resonance imaging (MRI) biomarkers of hepatic steatosis have demonstrated tremendous promise for accurate quantification of hepatic triglyceride concentration. These methods quantify the “proton density fat-fraction” (PDFF), which reflects the concentration of triglycerides in tissue. Previous in vivo studies have compared MRI-PDFF with histologic steatosis grading for assessment of hepatic steatosis. However, the correlation of MRI-PDFF with the underlying hepatic triglyceride content remained unknown. The aim of this ex vivo study was to validate the accuracy of MRI-PDFF as an imaging biomarker of hepatic steatosis. Using ex vivo human livers, we compared MRI-PDFF with magnetic resonance spectroscopy-PDFF (MRS-PDFF), biochemical triglyceride extraction and histology as three independent reference standards. A secondary aim was to compare the precision of MRI-PDFF relative to biopsy for the quantification of hepatic steatosis. MRI-PDFF was prospectively performed at 1.5T in 13 explanted human livers. We performed co-localized paired evaluation of liver fat content in all nine Couinaud segments using single-voxel MRS-PDFF (n=117), tissue wedges for biochemical triglyceride extraction (n=117), and five core biopsies performed in each segment for histologic grading (n=585). Accuracy of MRI-PDFF was assessed through linear regression with MRS-PDFF, triglyceride extraction and histology. Intra-observer agreement, inter-observer agreement and repeatability of MRI-PDFF and histologic grading were assessed through Bland-Altman analyses. MRI-PDFF showed an excellent correlation with MRS-PDFF (r=0.984; CI: 0.978–0.989) and strong correlation with histology (r=0.850; CI: 0.791–0.894) and triglyceride extraction (r=0.871; CI: 0.818–0.909). Intra-observer agreement, inter-observer agreement and repeatability showed a significantly smaller variance for MRI-PDFF than for histologic steatosis grading (all p<0.001). Conclusion MRI-PDFF is an accurate

  20. Quantitative assessment of image motion blur in diffraction images of moving biological cells

    NASA Astrophysics Data System (ADS)

    Wang, He; Jin, Changrong; Feng, Yuanming; Qi, Dandan; Sa, Yu; Hu, Xin-Hua

    2016-02-01

    Motion blur (MB) presents a significant challenge for obtaining high-contrast image data from biological cells with a polarization diffraction imaging flow cytometry (p-DIFC) method. A new p-DIFC experimental system has been developed to evaluate the MB and its effect on image analysis using a time-delay-integration (TDI) CCD camera. Diffraction images of MCF-7 and K562 cells have been acquired with different speed-mismatch ratios and compared to characterize MB quantitatively. Frequency analysis of the diffraction images shows that the degree of MB can be quantified by bandwidth variations of the diffraction images along the motion direction. The analytical results were confirmed by the p-DIFC image data acquired at different speed-mismatch ratios and used to validate a method of numerical simulation of MB on blur-free diffraction images, which provides a useful tool to examine the blurring effect on diffraction images acquired from the same cell. These results provide insights on the dependence of diffraction image on MB and allow significant improvement on rapid biological cell assay with the p-DIFC method.

  1. Histological Image Processing Features Induce a Quantitative Characterization of Chronic Tumor Hypoxia

    PubMed Central

    Grabocka, Elda; Bar-Sagi, Dafna; Mishra, Bud

    2016-01-01

    Hypoxia in tumors signifies resistance to therapy. Despite a wealth of tumor histology data, including anti-pimonidazole staining, no current methods use these data to induce a quantitative characterization of chronic tumor hypoxia in time and space. We use image-processing algorithms to develop a set of candidate image features that can formulate just such a quantitative description of xenographed colorectal chronic tumor hypoxia. Two features in particular give low-variance measures of chronic hypoxia near a vessel: intensity sampling that extends radially away from approximated blood vessel centroids, and multithresholding to segment tumor tissue into normal, hypoxic, and necrotic regions. From these features we derive a spatiotemporal logical expression whose truth value depends on its predicate clauses that are grounded in this histological evidence. As an alternative to the spatiotemporal logical formulation, we also propose a way to formulate a linear regression function that uses all of the image features to learn what chronic hypoxia looks like, and then gives a quantitative similarity score once it is trained on a set of histology images. PMID:27093539

  2. The challenges for quantitative photoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Cox, B. T.; Laufer, J. G.; Beard, P. C.

    2009-02-01

    In recent years, some of the promised potential of biomedical photoacoustic imaging has begun to be realised. It has been used to produce good, three-dimensional, images of blood vasculature in mice and other small animals, and in human skin in vivo, to depths of several mm, while maintaining a spatial resolution of <100 μm. Furthermore, photoacoustic imaging depends for contrast on the optical absorption distribution of the tissue under study, so, in the same way that the measurement of optical spectra has traditionally provided a means of determining the molecular constituents of an object, there is hope that multiwavelength photoacoustic imaging will provide a way to distinguish and quantify the component molecules of optically-scattering biological tissue (which may include exogeneous, targeted, chromophores). In simple situations with only a few significant absorbers and some prior knowledge of the geometry of the arrangement, this has been shown to be possible, but significant hurdles remain before the general problem can be solved. The general problem may be stated as follows: is it possible, in general, to take a set of photoacoustic images obtained at multiple optical wavelengths, and process them in a way that results in a set of quantitatively accurate images of the concentration distributions of the constituent chromophores of the imaged tissue? If such an 'inversion' procedure - not specific to any particular situation and free of restrictive suppositions - were designed, then photoacoustic imaging would offer the possibility of high resolution 'molecular' imaging of optically scattering tissue: a very powerful technique that would find uses in many areas of the life sciences and in clinical practice. This paper describes the principal challenges that must be overcome for such a general procedure to be successful.

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

    PubMed

    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.

  4. A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials.

    PubMed

    Verma, Nishant; Beretvas, S Natasha; Pascual, Belen; Masdeu, Joseph C; Markey, Mia K

    2018-03-14

    Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer's disease. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  5. MR Imaging in Spinocerebellar Ataxias: A Systematic Review.

    PubMed

    Klaes, A; Reckziegel, E; Franca, M C; Rezende, T J R; Vedolin, L M; Jardim, L B; Saute, J A

    2016-08-01

    Polyglutamine expansion spinocerebellar ataxias are autosomal dominant slowly progressive neurodegenerative diseases with no current treatment. MR imaging is the best-studied surrogate biomarker candidate for polyglutamine expansion spinocerebellar ataxias, though with conflicting results. We aimed to review quantitative central nervous system MR imaging technique findings in patients with polyglutamine expansion spinocerebellar ataxias and correlations with well-established clinical and molecular disease markers. We searched MEDLINE, LILACS, and Cochrane data bases of clinical trials between January 1995 and January 2016, for quantitative MR imaging volumetric approaches, MR spectroscopy, diffusion tensor imaging, or other quantitative techniques, comparing patients with polyglutamine expansion spinocerebellar ataxias (SCAs) with controls. Pertinent details for each study regarding participants, imaging methods, and results were extracted. After reviewing the 706 results, 18 studies were suitable for inclusion: 2 studies in SCA1, 1 in SCA2, 15 in SCA3, 1 in SCA7, 1 in SCA1 and SCA6 presymptomatic carriers, and none in SCA17 and dentatorubropallidoluysian atrophy. Cerebellar hemispheres and vermis, whole brain stem, midbrain, pons, medulla oblongata, cervical spine, striatum, and thalamus presented significant atrophy in SCA3. The caudate, putamen and whole brain stem presented similar sensitivity to change compared with ataxia scales after 2 years of follow-up in a single prospective study in SCA3. MR spectroscopy and DTI showed abnormalities only in cross-sectional studies in SCA3. Results from single studies in other polyglutamine expansion spinocerebellar ataxias should be replicated in different cohorts. Additional cross-sectional and prospective volumetric analysis, MR spectroscopy, and DTI studies are necessary in polyglutamine expansion spinocerebellar ataxias. The properties of preclinical disease biomarkers (presymptomatic) of MR imaging should be

  6. Quantitative imaging biomarkers for dural sinus patterns in idiopathic intracranial hypertension.

    PubMed

    Zur, Dinah; Anconina, Reut; Kesler, Anat; Lublinsky, Svetlana; Toledano, Ronen; Shelef, Ilan

    2017-02-01

    To quantitatively characterize transverse dural sinuses (TS) on magnetic resonance venography (MRV) in patients with idiopathic intracranial hypertension (IIH), compared to healthy controls, using a computer assisted detection (CAD) method. We retrospectively analyzed MRV studies of 38 IIH patients and 30 controls, matched by age and gender. Data analysis was performed using a specially developed Matlab algorithm for vessel cross-sectional analysis. The cross-sectional area and shape measurements were evaluated in patients and controls. Mean, minimal, and maximal cross-sectional areas as well as volumetric parameters of the right and left transverse sinuses were significantly smaller in IIH patients than in controls ( p  < .005 for all). Idiopathic intracranial hypertension patients showed a narrowed segment in both TS, clustering near the junction with the sigmoid sinus. In 36% (right TS) and 43% (left TS), the stenosis extended to >50% of the entire length of the TS, i.e. the TS was hypoplastic. Narrower vessels tended to have a more triangular shape than did wider vessels. Using CAD we precisely quantified TS stenosis and its severity in IIH patients by cross-sectional and volumetric analysis. This method can be used as an exact tool for investigating mechanisms of IIH development and response to treatment.

  7. Quantitative criteria for assessment of gamma-ray imager performance

    NASA Astrophysics Data System (ADS)

    Gottesman, Steve; Keller, Kristi; Malik, Hans

    2015-08-01

    In recent years gamma ray imagers such as the GammaCamTM and Polaris have demonstrated good imaging performance in the field. Imager performance is often summarized as "resolution", either angular, or spatial at some distance from the imager, however the definition of resolution is not always related to the ability to image an object. It is difficult to quantitatively compare imagers without a common definition of image quality. This paper examines three categories of definition: point source; line source; and area source. It discusses the details of those definitions and which ones are more relevant for different situations. Metrics such as Full Width Half Maximum (FWHM), variations on the Rayleigh criterion, and some analogous to National Imagery Interpretability Rating Scale (NIIRS) are discussed. The performance against these metrics is evaluated for a high resolution coded aperture imager modeled using Monte Carlo N-Particle (MCNP), and for a medium resolution imager measured in the lab.

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

    PubMed Central

    Cohen Freue, Gabriela V.; Meredith, Anna; Smith, Derek; Bergman, Axel; Sasaki, Mayu; Lam, Karen K. Y.; Hollander, Zsuzsanna; Opushneva, Nina; Takhar, Mandeep; Lin, David; Wilson-McManus, Janet; Balshaw, Robert; Keown, Paul A.; Borchers, Christoph H.; McManus, Bruce; Ng, Raymond T.; McMaster, W. Robert

    2013-01-01

    Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac

  10. WONOEP appraisal: Biomarkers of epilepsy-associated comorbidities.

    PubMed

    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

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

    NASA Astrophysics Data System (ADS)

    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

  12. Summary of Quantitative Interpretation of Image Far Ultraviolet Auroral Data

    NASA Technical Reports Server (NTRS)

    Frey, H. U.; Immel, T. J.; Mende, S. B.; Gerard, J.-C.; Hubert, B.; Habraken, S.; Span, J.; Gladstone, G. R.; Bisikalo, D. V.; Shematovich, V. I.; hide

    2002-01-01

    Direct imaging of the magnetosphere by instruments on the IMAGE spacecraft is supplemented by simultaneous observations of the global aurora in three far ultraviolet (FUV) wavelength bands. The purpose of the multi-wavelength imaging is to study the global auroral particle and energy input from thc magnetosphere into the atmosphere. This paper describes provides the method for quantitative interpretation of FUV measurements. The Wide-Band Imaging Camera (WIC) provides broad band ultraviolet images of the aurora with maximum spatial and temporal resolution by imaging the nitrogen lines and bands between 140 and 180 nm wavelength. The Spectrographic Imager (SI), a dual wavelength monochromatic instrument, images both Doppler-shifted Lyman alpha emissions produced by precipitating protons, in the SI-12 channel and OI 135.6 nm emissions in the SI-13 channel. From the SI-12 Doppler shifted Lyman alpha images it is possible to obtain the precipitating proton flux provided assumptions are made regarding the mean energy of the protons. Knowledge of the proton (flux and energy) component allows the calculation of the contribution produced by protons in the WIC and SI-13 instruments. Comparison of the corrected WIC and SI-13 signals provides a measure of the electron mean energy, which can then be used to determine the electron energy fluxun-. To accomplish this reliable modeling emission modeling and instrument calibrations are required. In-flight calibration using early-type stars was used to validate the pre-flight laboratory calibrations and determine long-term trends in sensitivity. In general, very reasonable agreement is found between in-situ measurements and remote quantitative determinations.

  13. Quantitative Imaging of Single Unstained Magnetotactic Bacteria by Coherent X-ray Diffraction Microscopy.

    PubMed

    Fan, Jiadong; Sun, Zhibin; Zhang, Jian; Huang, Qingjie; Yao, Shengkun; Zong, Yunbing; Kohmura, Yoshiki; Ishikawa, Tetsuya; Liu, Hong; Jiang, Huaidong

    2015-06-16

    Novel coherent diffraction microscopy provides a powerful lensless imaging method to obtain a better understanding of the microorganism at the nanoscale. Here we demonstrated quantitative imaging of intact unstained magnetotactic bacteria using coherent X-ray diffraction microscopy combined with an iterative phase retrieval algorithm. Although the signal-to-noise ratio of the X-ray diffraction pattern from single magnetotactic bacterium is weak due to low-scattering ability of biomaterials, an 18.6 nm half-period resolution of reconstructed image was achieved by using a hybrid input-output phase retrieval algorithm. On the basis of the quantitative reconstructed images, the morphology and some intracellular structures, such as nucleoid, polyβ-hydroxybutyrate granules, and magnetosomes, were identified, which were also confirmed by scanning electron microscopy and energy dispersive spectroscopy. With the benefit from the quantifiability of coherent diffraction imaging, for the first time to our knowledge, an average density of magnetotactic bacteria was calculated to be ∼1.19 g/cm(3). This technique has a wide range of applications, especially in quantitative imaging of low-scattering biomaterials and multicomponent materials at nanoscale resolution. Combined with the cryogenic technique or X-ray free electron lasers, the method could image cells in a hydrated condition, which helps to maintain their natural structure.

  14. Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging

    PubMed Central

    Yang, Yaliang; Li, Fuhai; Gao, Liang; Wang, Zhiyong; Thrall, Michael J.; Shen, Steven S.; Wong, Kelvin K.; Wong, Stephen T. C.

    2011-01-01

    We present a label-free, chemically-selective, quantitative imaging strategy to identify breast cancer and differentiate its subtypes using coherent anti-Stokes Raman scattering (CARS) microscopy. Human normal breast tissue, benign proliferative, as well as in situ and invasive carcinomas, were imaged ex vivo. Simply by visualizing cellular and tissue features appearing on CARS images, cancerous lesions can be readily separated from normal tissue and benign proliferative lesion. To further distinguish cancer subtypes, quantitative disease-related features, describing the geometry and distribution of cancer cell nuclei, were extracted and applied to a computerized classification system. The results show that in situ carcinoma was successfully distinguished from invasive carcinoma, while invasive ductal carcinoma (IDC) and invasive lobular carcinoma were also distinguished from each other. Furthermore, 80% of intermediate-grade IDC and 85% of high-grade IDC were correctly distinguished from each other. The proposed quantitative CARS imaging method has the potential to enable rapid diagnosis of breast cancer. PMID:21833355

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

    PubMed

    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.

  16. Quantitative photothermal phase imaging of red blood cells using digital holographic photothermal microscope.

    PubMed

    Vasudevan, Srivathsan; Chen, George C K; Lin, Zhiping; Ng, Beng Koon

    2015-05-10

    Photothermal microscopy (PTM), a noninvasive pump-probe high-resolution microscopy, has been applied as a bioimaging tool in many biomedical studies. PTM utilizes a conventional phase contrast microscope to obtain highly resolved photothermal images. However, phase information cannot be extracted from these photothermal images, as they are not quantitative. Moreover, the problem of halos inherent in conventional phase contrast microscopy needs to be tackled. Hence, a digital holographic photothermal microscopy technique is proposed as a solution to obtain quantitative phase images. The proposed technique is demonstrated by extracting phase values of red blood cells from their photothermal images. These phase values can potentially be used to determine the temperature distribution of the photothermal images, which is an important study in live cell monitoring applications.

  17. Evaluation of quantitative image analysis criteria for the high-resolution microendoscopic detection of neoplasia in Barrett's esophagus

    NASA Astrophysics Data System (ADS)

    Muldoon, Timothy J.; Thekkek, Nadhi; Roblyer, Darren; Maru, Dipen; Harpaz, Noam; Potack, Jonathan; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

    2010-03-01

    Early detection of neoplasia in patients with Barrett's esophagus is essential to improve outcomes. The aim of this ex vivo study was to evaluate the ability of high-resolution microendoscopic imaging and quantitative image analysis to identify neoplastic lesions in patients with Barrett's esophagus. Nine patients with pathologically confirmed Barrett's esophagus underwent endoscopic examination with biopsies or endoscopic mucosal resection. Resected fresh tissue was imaged with fiber bundle microendoscopy; images were analyzed by visual interpretation or by quantitative image analysis to predict whether the imaged sites were non-neoplastic or neoplastic. The best performing pair of quantitative features were chosen based on their ability to correctly classify the data into the two groups. Predictions were compared to the gold standard of histopathology. Subjective analysis of the images by expert clinicians achieved average sensitivity and specificity of 87% and 61%, respectively. The best performing quantitative classification algorithm relied on two image textural features and achieved a sensitivity and specificity of 87% and 85%, respectively. This ex vivo pilot trial demonstrates that quantitative analysis of images obtained with a simple microendoscope system can distinguish neoplasia in Barrett's esophagus with good sensitivity and specificity when compared to histopathology and to subjective image interpretation.

  18. Analysis of Vaginal Microbicide Film Hydration Kinetics by Quantitative Imaging Refractometry

    PubMed Central

    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. PMID:24736376

  19. Inverse transport problems in quantitative PAT for molecular imaging

    NASA Astrophysics Data System (ADS)

    Ren, Kui; Zhang, Rongting; Zhong, Yimin

    2015-12-01

    Fluorescence photoacoustic tomography (fPAT) is a molecular imaging modality that combines photoacoustic tomography with fluorescence imaging to obtain high-resolution imaging of fluorescence distributions inside heterogeneous media. The objective of this work is to study inverse problems in the quantitative step of fPAT where we intend to reconstruct physical coefficients in a coupled system of radiative transport equations using internal data recovered from ultrasound measurements. We derive uniqueness and stability results on the inverse problems and develop some efficient algorithms for image reconstructions. Numerical simulations based on synthetic data are presented to validate the theoretical analysis. The results we present here complement these in Ren K and Zhao H (2013 SIAM J. Imaging Sci. 6 2024-49) on the same problem but in the diffusive regime.

  20. I Vivo Quantitative Ultrasound Imaging and Scatter Assessments.

    NASA Astrophysics Data System (ADS)

    Lu, Zheng Feng

    There is evidence that "instrument independent" measurements of ultrasonic scattering properties would provide useful diagnostic information that is not available with conventional ultrasound imaging. This dissertation is a continuing effort to test the above hypothesis and to incorporate quantitative ultrasound methods into clinical examinations for early detection of diffuse liver disease. A well-established reference phantom method was employed to construct quantitative ultrasound images of tissue in vivo. The method was verified by extensive phantom tests. A new method was developed to measure the effective attenuation coefficient of the body wall. The method relates the slope of the difference between the echo signal power spectrum from a uniform region distal to the body wall and the echo signal power spectrum from a reference phantom to the body wall attenuation. The accuracy obtained from phantom tests suggests further studies with animal experiments. Clinically, thirty-five healthy subjects and sixteen patients with diffuse liver disease were studied by these quantitative ultrasound methods. The average attenuation coefficient in normals agreed with previous investigators' results; in vivo backscatter coefficients agreed with the results from normals measured by O'Donnell. Strong discriminating power (p < 0.001) was found for both attenuation and backscatter coefficients between fatty livers and normals; a significant difference (p < 0.01) was observed in the backscatter coefficient but not in the attenuation coefficient between cirrhotic livers and normals. An in vivo animal model of steroid hepatopathy was used to investigate the system sensitivity in detecting early changes in canine liver resulting from corticosteroid administration. The average attenuation coefficient slope increased from 0.7 dB/cm/MHz in controls to 0.82 dB/cm/MHz (at 6 MHz) in treated animals on day 14 into the treatment, and the backscatter coefficient was 26times 10^{ -4}cm^{-1}sr

  1. Quantitative damage imaging using Lamb wave diffraction tomography

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

    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. Project supported by the National Natural Science Foundation of China (Grant Nos. 11474195, 11274226, 11674214, and 51478258).

  2. qFlow Cytometry-Based Receptoromic Screening: A High-Throughput Quantification Approach Informing Biomarker Selection and Nanosensor Development.

    PubMed

    Chen, Si; Weddell, Jared; Gupta, Pavan; Conard, Grace; Parkin, James; Imoukhuede, Princess I

    2017-01-01

    Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression.

  3. A quantitative systems pharmacology model of blood coagulation network describes in vivo biomarker changes in non-bleeding subjects.

    PubMed

    Lee, D; Nayak, S; Martin, S W; Heatherington, A C; Vicini, P; Hua, F

    2016-12-01

    Essentials Baseline coagulation activity can be detected in non-bleeding state by in vivo biomarker levels. A detailed mathematical model of coagulation was developed to describe the non-bleeding state. Optimized model described in vivo biomarkers with recombinant activated factor VII treatment. Sensitivity analysis predicted prothrombin fragment 1 + 2 and D-dimer are regulated differently. Background Prothrombin fragment 1 + 2 (F 1 + 2 ), thrombin-antithrombin III complex (TAT) and D-dimer can be detected in plasma from non-bleeding hemostatically normal subjects or hemophilic patients. They are often used as safety or pharmacodynamic biomarkers for hemostatis-modulating therapies in the clinic, and provide insights into in vivo coagulation activity. Objectives To develop a quantitative systems pharmacology (QSP) model of the blood coagulation network to describe in vivo biomarkers, including F 1 + 2 , TAT, and D-dimer, under non-bleeding conditions. Methods The QSP model included intrinsic and extrinsic coagulation pathways, platelet activation state-dependent kinetics, and a two-compartment pharmacokinetics model for recombinant activated factor VII (rFVIIa). Literature data on F 1 + 2 and D-dimer at baseline and changes with rFVIIa treatment were used for parameter optimization. Multiparametric sensitivity analysis (MPSA) was used to understand key proteins that regulate F 1 + 2 , TAT and D-dimer levels. Results The model was able to describe tissue factor (TF)-dependent baseline levels of F 1 + 2 , TAT and D-dimer in a non-bleeding state, and their increases in hemostatically normal subjects and hemophilic patients treated with different doses of rFVIIa. The amount of TF required is predicted to be very low in a non-bleeding state. The model also predicts that these biomarker levels will be similar in hemostatically normal subjects and hemophilic patients. MPSA revealed that F 1 + 2 and TAT levels are highly correlated, and that D-dimer is

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

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

    PubMed

    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.

  8. Impact of image quality on OCT angiography based quantitative measurements.

    PubMed

    Al-Sheikh, Mayss; Ghasemi Falavarjani, Khalil; Akil, Handan; Sadda, SriniVas R

    2017-01-01

    To study the impact of image quality on quantitative measurements and the frequency of segmentation error with optical coherence tomography angiography (OCTA). Seventeen eyes of 10 healthy individuals were included in this study. OCTA was performed using a swept-source device (Triton, Topcon). Each subject underwent three scanning sessions 1-2 min apart; the first two scans were obtained under standard conditions and for the third session, the image quality index was reduced using application of a topical ointment. En face OCTA images of the retinal vasculature were generated using the default segmentation for the superficial and deep retinal layer (SRL, DRL). Intraclass correlation coefficient (ICC) was used as a measure for repeatability. The frequency of segmentation error, motion artifact, banding artifact and projection artifact was also compared among the three sessions. The frequency of segmentation error, and motion artifact was statistically similar between high and low image quality sessions (P = 0.707, and P = 1 respectively). However, the frequency of projection and banding artifact was higher with a lower image quality. The vessel density in the SRL was highly repeatable in the high image quality sessions (ICC = 0.8), however, the repeatability was low, comparing the high and low image quality measurements (ICC = 0.3). In the DRL, the repeatability of the vessel density measurements was fair in the high quality sessions (ICC = 0.6 and ICC = 0.5, with and without automatic artifact removal, respectively) and poor comparing high and low image quality sessions (ICC = 0.3 and ICC = 0.06, with and without automatic artifact removal, respectively). The frequency of artifacts is higher and the repeatability of the measurements is lower with lower image quality. The impact of image quality index should be always considered in OCTA based quantitative measurements.

  9. A critical insight into the development pipeline of microfluidic immunoassay devices for the sensitive quantitation of protein biomarkers at the point of care.

    PubMed

    Barbosa, Ana I; Reis, Nuno M

    2017-03-13

    The latest clinical procedures for the timely and cost-effective diagnosis of chronic and acute clinical conditions, such as cardiovascular diseases, cancer, chronic respiratory diseases, diabetes or sepsis (i.e. the biggest causes of death worldwide), involve the quantitation of specific protein biomarkers released into the blood stream or other physiological fluids (e.g. urine or saliva). The clinical thresholds are usually in the femtomolar to picolomar range, and consequently the measurement of these protein biomarkers heavily relies on highly sophisticated, bulky and automated equipment in centralised pathology laboratories. The first microfluidic devices capable of measuring protein biomarkers in miniaturised immunoassays were presented nearly two decades ago and promised to revolutionise point-of-care (POC) testing by offering unmatched sensitivity and automation in a compact POC format; however, the development and adoption of microfluidic protein biomarker tests has fallen behind expectations. This review presents a detailed critical overview into the pipeline of microfluidic devices developed in the period 2005-2016 capable of measuring protein biomarkers from the pM to fM range in formats compatible with POC testing, with a particular focus on the use of affordable microfluidic materials and compact low-cost signal interrogation. The integration of these two important features (essential unique selling points for the successful microfluidic diagnostic products) has been missed in previous review articles and explain the poor adoption of microfluidic technologies in this field. Most current miniaturised devices compromise either on the affordability, compactness and/or performance of the test, making current tests unsuitable for the POC measurement of protein biomarkers. Seven core technical areas, including (i) the selected strategy for antibody immobilisation, (ii) the surface area and surface-area-to-volume ratio, (iii) surface passivation, (iv) the

  10. Levels of biomarkers correlate with magnetic resonance imaging progression of knee cartilage degeneration: a study on canine.

    PubMed

    Qi, Chang; Changlin, Huang

    2007-07-01

    To examine the association between levers of cartilage oligomeric matrix protein (COMP), matrix metalloproteinases-1 (MMP-1), matrix metalloproteinases-3 (MMP-3), tissue inhibitor of matrix metalloproteinases-1 (TIMP-1) in serum and synovial fluid, and MR imaging of cartilage degeneration in knee joint, and to understand the effects of movement training with different intensity on cartilage of knee joint. 20 adult canines were randomly divided into three groups (8 in the light training group; 8 in the intensive training group; 4 in the control group), and canines of the two training groups were trained daily at different intensity. The training lasted for 10 weeks in all. Magnetic resonance imaging (MRI) examinations were performed regularly (2, 4, 6, 8, 10 week) to investigate the changes of articular cartilage in the canine knee, while concentrations of COMP, MMP-1, MMP-3, TIMP-1 in serum and synovial fluid were measured by ELISA assays. We could find imaging changes of cartilage degeneration in both the training groups by MRI examination during training period, compared with the control group. However, there was no significant difference between these two training groups. Elevations of levels of COMP, MMP-1, MMP-3, TIMP-1, MMP-3/TIMP-1 were seen in serum and synovial fluid after training, and their levels had obvious association with knee MRI grades of cartilage lesion. Furthermore, there were statistically significant associations between biomarkers levels in serum and in synovial fluid. Long-time and high-intensity movement training induces cartilage degeneration in knee joint. Within the intensity extent applied in this study, knee cartilage degeneration caused by light training or intensive training has no difference in MR imaging, but has a comparatively obvious difference in biomarkers level. To detect articular cartilage degeneration in early stage and monitor pathological process, the associated application of several biomarkers has a very good practical

  11. The Role of Biomarkers in Clinical Trials for Alzheimer Disease

    PubMed Central

    Thal, Leon J.; Kantarci, Kejal; Reiman, Eric M.; Klunk, William E.; Weiner, Michael W.; Zetterberg, Henrik; Galasko, Douglas; Praticò, Domenico; Griffin, Sue; Schenk, Dale; Siemers, Eric

    2007-01-01

    Biomarkers are likely to be important in the study of Alzheimer disease (AD) for a variety of reasons. A clinical diagnosis of Alzheimer disease is inaccurate even among experienced investigators in about 10% to 15% of cases, and biomarkers might improve the accuracy of diagnosis. Importantly for the development of putative disease-modifying drugs for Alzheimer disease, biomarkers might also serve as indirect measures of disease severity. When used in this way, sample sizes of clinical trials might be reduced, and a change in biomarker could be considered supporting evidence of disease modification. This review summarizes a meeting of the Alzheimer’s Association’s Research Roundtable, during which existing and emerging biomarkers for AD were evaluated. Imaging biomarkers including volumetric magnetic resonance imaging and positron emission tomography assessing either glucose utilization or ligands binding to amyloid plaque are discussed. Additionally, biochemical biomarkers in blood or cerebrospinal fluid are assessed. Currently appropriate uses of biomarkers in the study of Alzheimer disease, and areas where additional work is needed, are discussed. PMID:16493230

  12. Quantitative imaging with fluorescent biosensors.

    PubMed

    Okumoto, Sakiko; Jones, Alexander; Frommer, Wolf B

    2012-01-01

    Molecular activities are highly dynamic and can occur locally in subcellular domains or compartments. Neighboring cells in the same tissue can exist in different states. Therefore, quantitative information on the cellular and subcellular dynamics of ions, signaling molecules, and metabolites is critical for functional understanding of organisms. Mass spectrometry is generally used for monitoring ions and metabolites; however, its temporal and spatial resolution are limited. Fluorescent proteins have revolutionized many areas of biology-e.g., fluorescent proteins can report on gene expression or protein localization in real time-yet promoter-based reporters are often slow to report physiologically relevant changes such as calcium oscillations. Therefore, novel tools are required that can be deployed in specific cells and targeted to subcellular compartments in order to quantify target molecule dynamics directly. We require tools that can measure enzyme activities, protein dynamics, and biophysical processes (e.g., membrane potential or molecular tension) with subcellular resolution. Today, we have an extensive suite of tools at our disposal to address these challenges, including translocation sensors, fluorescence-intensity sensors, and Förster resonance energy transfer sensors. This review summarizes sensor design principles, provides a database of sensors for more than 70 different analytes/processes, and gives examples of applications in quantitative live cell imaging.

  13. Some selected quantitative methods of thermal image analysis in Matlab.

    PubMed

    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.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Brynolfsson, Patrik; Hauksson, Jón; Karlsson, Mikael

    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 treatedmore » 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

  15. Novel quantitative analysis of autofluorescence images for oral cancer screening.

    PubMed

    Huang, Tze-Ta; Huang, Jehn-Shyun; Wang, Yen-Yun; Chen, Ken-Chung; Wong, Tung-Yiu; Chen, Yi-Chun; Wu, Che-Wei; Chan, Leong-Perng; Lin, Yi-Chu; Kao, Yu-Hsun; Nioka, Shoko; Yuan, Shyng-Shiou F; Chung, Pau-Choo

    2017-05-01

    VELscope® was developed to inspect oral mucosa autofluorescence. However, its accuracy is heavily dependent on the examining physician's experience. This study was aimed toward the development of a novel quantitative analysis of autofluorescence images for oral cancer screening. Patients with either oral cancer or precancerous lesions and a control group with normal oral mucosa were enrolled in this study. White light images and VELscope® autofluorescence images of the lesions were taken with a digital camera. The lesion in the image was chosen as the region of interest (ROI). The average intensity and heterogeneity of the ROI were calculated. A quadratic discriminant analysis (QDA) was utilized to compute boundaries based on sensitivity and specificity. 47 oral cancer lesions, 54 precancerous lesions, and 39 normal oral mucosae controls were analyzed. A boundary of specificity of 0.923 and a sensitivity of 0.979 between the oral cancer lesions and normal oral mucosae were validated. The oral cancer and precancerous lesions could also be differentiated from normal oral mucosae with a specificity of 0.923 and a sensitivity of 0.970. The novel quantitative analysis of the intensity and heterogeneity of VELscope® autofluorescence images used in this study in combination with a QDA classifier can be used to differentiate oral cancer and precancerous lesions from normal oral mucosae. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Structural-functional relationships between eye orbital imaging biomarkers and clinical visual assessments

    NASA Astrophysics Data System (ADS)

    Yao, Xiuya; Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina; Plassard, Andrew; Harrigan, Rob L.; Mawn, Louise A.; Landman, Bennett A.

    2017-02-01

    Eye diseases and visual impairment affect millions of Americans and induce billions of dollars in annual economic burdens. Expounding upon existing knowledge of eye diseases could lead to improved treatment and disease prevention. This research investigated the relationship between structural metrics of the eye orbit and visual function measurements in a cohort of 470 patients from a retrospective study of ophthalmology records for patients (with thyroid eye disease, orbital inflammation, optic nerve edema, glaucoma, intrinsic optic nerve disease), clinical imaging, and visual function assessments. Orbital magnetic resonance imaging (MRI) and computed tomography (CT) images were retrieved and labeled in 3D using multi-atlas label fusion. Based on the 3D structures, both traditional radiology measures (e.g., Barrett index, volumetric crowding index, optic nerve length) and novel volumetric metrics were computed. Using stepwise regression, the associations between structural metrics and visual field scores (visual acuity, functional acuity, visual field, functional field, and functional vision) were assessed. Across all models, the explained variance was reasonable (R2 0.1-0.2) but highly significant (p < 0.001). Instead of analyzing a specific pathology, this study aimed to analyze data across a variety of pathologies. This approach yielded a general model for the connection between orbital structural imaging biomarkers and visual function.

  17. The Quantitative Science of Evaluating Imaging Evidence.

    PubMed

    Genders, Tessa S S; Ferket, Bart S; Hunink, M G Myriam

    2017-03-01

    Cardiovascular diagnostic imaging tests are increasingly used in everyday clinical practice, but are often imperfect, just like any other diagnostic test. The performance of a cardiovascular diagnostic imaging test is usually expressed in terms of sensitivity and specificity compared with the reference standard (gold standard) for diagnosing the disease. However, evidence-based application of a diagnostic test also requires knowledge about the pre-test probability of disease, the benefit of making a correct diagnosis, the harm caused by false-positive imaging test results, and potential adverse effects of performing the test itself. To assist in clinical decision making regarding appropriate use of cardiovascular diagnostic imaging tests, we reviewed quantitative concepts related to diagnostic performance (e.g., sensitivity, specificity, predictive values, likelihood ratios), as well as possible biases and solutions in diagnostic performance studies, Bayesian principles, and the threshold approach to decision making. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  18. Quantitative nuclear magnetic resonance imaging: characterisation of experimental cerebral oedema.

    PubMed Central

    Barnes, D; McDonald, W I; Johnson, G; Tofts, P S; Landon, D N

    1987-01-01

    Magnetic resonance imaging (MRI) has been used quantitatively to define the characteristics of two different models of experimental cerebral oedema in cats: vasogenic oedema produced by cortical freezing and cytotoxic oedema induced by triethyl tin. The MRI results have been correlated with the ultrastructural changes. The images accurately delineated the anatomical extent of the oedema in the two lesions, but did not otherwise discriminate between them. The patterns of measured increase in T1' and T2' were, however, characteristic for each type of oedema, and reflected the protein content. The magnetisation decay characteristics of both normal and oedematous white matter were monoexponential for T1 but biexponential for T2 decay. The relative sizes of the two component exponentials of the latter corresponded with the physical sizes of the major tissue water compartments. Quantitative MRI data can provide reliable information about the physico-chemical environment of tissue water in normal and oedematous cerebral tissue, and are useful for distinguishing between acute and chronic lesions in multiple sclerosis. Images PMID:3572428

  19. NIA-AA staging of preclinical Alzheimer disease: discordance and concordance of CSF and imaging biomarkers.

    PubMed

    Vos, Stephanie J B; Gordon, Brian A; Su, Yi; Visser, Pieter Jelle; Holtzman, David M; Morris, John C; Fagan, Anne M; Benzinger, Tammie L S

    2016-08-01

    The National Institute of Aging and Alzheimer's Association (NIA-AA) criteria for Alzheimer disease (AD) treat neuroimaging and cerebrospinal fluid (CSF) markers of AD pathology as if they would be interchangeable. We tested this assumption in 212 cognitively normal participants who have both neuroimaging and CSF measures of β-amyloid (CSF Aβ1-42 and positron emission tomography imaging with Pittsburgh Compound B) and neuronal injury (CSF t-tau and p-tau and structural magnetic resonance imaging) with longitudinal clinical follow-up. Participants were classified in preclinical AD stage 1 (β-amyloidosis) or preclinical AD stage 2+ (β-amyloidosis and neuronal injury) using the NIA-AA criteria, or in the normal or suspected non-Alzheimer disease pathophysiology group (neuronal injury without β-amyloidosis). At baseline, 21% of participants had preclinical AD based on CSF and 28% based on neuroimaging. Between modalities, staging was concordant in only 47% of participants. Disagreement resulted from low concordance between biomarkers of neuronal injury. Still, individuals in stage 2+ using either criterion had an increased risk for clinical decline. This highlights the heterogeneity of the definition of neuronal injury and has important implications for clinical trials using biomarkers for enrollment or as surrogate end point measures. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Cerebrospinal Fluid Levels of Amyloid Beta 1-43 Mirror 1-42 in Relation to Imaging Biomarkers of Alzheimer’s Disease

    PubMed Central

    Almdahl, Ina S.; Lauridsen, Camilla; Selnes, Per; Kalheim, Lisa F.; Coello, Christopher; Gajdzik, Beata; Møller, Ina; Wettergreen, Marianne; Grambaite, Ramune; Bjørnerud, Atle; Bråthen, Geir; Sando, Sigrid B.; White, Linda R.; Fladby, Tormod

    2017-01-01

    Introduction: Amyloid beta 1-43 (Aβ43), with its additional C-terminal threonine residue, is hypothesized to play a role in early Alzheimer’s disease pathology possibly different from that of amyloid beta 1-42 (Aβ42). Cerebrospinal fluid (CSF) Aβ43 has been suggested as a potential novel biomarker for predicting conversion from mild cognitive impairment (MCI) to dementia in Alzheimer’s disease. However, the relationship between CSF Aβ43 and established imaging biomarkers of Alzheimer’s disease has never been assessed. Materials and Methods: In this observational study, CSF Aβ43 was measured with ELISA in 89 subjects; 34 with subjective cognitive decline (SCD), 51 with MCI, and four with resolution of previous cognitive complaints. All subjects underwent structural MRI; 40 subjects on a 3T and 50 on a 1.5T scanner. Forty subjects, including 24 with SCD and 12 with MCI, underwent 18F-Flutemetamol PET. Seventy-eight subjects were assessed with 18F-fluorodeoxyglucose PET (21 SCD/7 MCI and 11 SCD/39 MCI on two different scanners). Ten subjects with SCD and 39 with MCI also underwent diffusion tensor imaging. Results: Cerebrospinal fluid Aβ43 was both alone and together with p-tau a significant predictor of the distinction between SCD and MCI. There was a marked difference in CSF Aβ43 between subjects with 18F-Flutemetamol PET scans visually interpreted as negative (37 pg/ml, n = 27) and positive (15 pg/ml, n = 9), p < 0.001. Both CSF Aβ43 and Aβ42 were negatively correlated with standardized uptake value ratios for all analyzed regions; CSF Aβ43 average rho -0.73, Aβ42 -0.74. Both CSF Aβ peptides correlated significantly with hippocampal volume, inferior parietal and frontal cortical thickness and axial diffusivity in the corticospinal tract. There was a trend toward CSF Aβ42 being better correlated with cortical glucose metabolism. None of the studied correlations between CSF Aβ43/42 and imaging biomarkers were significantly different for the two A

  1. Cardiovascular disease biomarkers across autoimmune diseases.

    PubMed

    Ahearn, Joseph; Shields, Kelly J; Liu, Chau-Ching; Manzi, Susan

    2015-11-01

    Cardiovascular disease is increasingly recognized as a major cause of premature mortality among those with autoimmune disorders. There is an urgent need to identify those patients with autoimmune disease who are at risk for CVD so as to optimize therapeutic intervention and ultimately prevention. Accurate identification, monitoring and stratification of such patients will depend upon a panel of biomarkers of cardiovascular disease. This review will discuss some of the most recent biomarkers of cardiovascular diseases in autoimmune disease, including lipid oxidation, imaging biomarkers to characterize coronary calcium, plaque, and intima media thickness, biomarkers of inflammation and activated complement, genetic markers, endothelial biomarkers, and antiphospholipid antibodies. Clinical implementation of these biomarkers will not only enhance patient care but also likely accelerate the pharmaceutical pipeline for targeted intervention to reduce or eliminate cardiovascular disease in the setting of autoimmunity. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Development of a multi-biomarker disease activity test for rheumatoid arthritis.

    PubMed

    Centola, Michael; Cavet, Guy; Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A; Turner, Mary; Sutton, Chris; Smith, Dustin R; Haney, Douglas J; Chernoff, David; Hesterberg, Lyndal K; Carulli, John P; Taylor, Peter C; Shadick, Nancy A; Weinblatt, Michael E; Curtis, Jeffrey R

    2013-01-01

    Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to

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

    NASA Astrophysics Data System (ADS)

    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.

  4. Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

    PubMed

    Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

    2018-01-01

    Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

    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.

  6. End-to-end deep neural network for optical inversion in quantitative photoacoustic imaging.

    PubMed

    Cai, Chuangjian; Deng, Kexin; Ma, Cheng; Luo, Jianwen

    2018-06-15

    An end-to-end deep neural network, ResU-net, is developed for quantitative photoacoustic imaging. A residual learning framework is used to facilitate optimization and to gain better accuracy from considerably increased network depth. The contracting and expanding paths enable ResU-net to extract comprehensive context information from multispectral initial pressure images and, subsequently, to infer a quantitative image of chromophore concentration or oxygen saturation (sO 2 ). According to our numerical experiments, the estimations of sO 2 and indocyanine green concentration are accurate and robust against variations in both optical property and object geometry. An extremely short reconstruction time of 22 ms is achieved.

  7. FLASH proton density imaging for improved surface coil intensity correction in quantitative and semi-quantitative SSFP perfusion cardiovascular magnetic resonance.

    PubMed

    Nielles-Vallespin, Sonia; Kellman, Peter; Hsu, Li-Yueh; Arai, Andrew E

    2015-02-17

    A low excitation flip angle (α < 10°) steady-state free precession (SSFP) proton-density (PD) reference scan is often used to estimate the B1-field inhomogeneity for surface coil intensity correction (SCIC) of the saturation-recovery (SR) prepared high flip angle (α = 40-50°) SSFP myocardial perfusion images. The different SSFP off-resonance response for these two flip angles might lead to suboptimal SCIC when there is a spatial variation in the background B0-field. The low flip angle SSFP-PD frames are more prone to parallel imaging banding artifacts in the presence of off-resonance. The use of FLASH-PD frames would eliminate both the banding artifacts and the uneven frequency response in the presence of off-resonance in the surface coil inhomogeneity estimate and improve homogeneity of semi-quantitative and quantitative perfusion measurements. B0-field maps, SSFP and FLASH-PD frames were acquired in 10 healthy volunteers to analyze the SSFP off-resonance response. Furthermore, perfusion scans preceded by both FLASH and SSFP-PD frames from 10 patients with no myocardial infarction were analyzed semi-quantitatively and quantitatively (rest n = 10 and stress n = 1). Intra-subject myocardial blood flow (MBF) coefficient of variation (CoV) over the whole left ventricle (LV), as well as intra-subject peak contrast (CE) and upslope (SLP) standard deviation (SD) over 6 LV sectors were investigated. In the 6 out of 10 cases where artifacts were apparent in the LV ROI of the SSFP-PD images, all three variability metrics were statistically significantly lower when using the FLASH-PD frames as input for the SCIC (CoVMBF-FLASH = 0.3 ± 0.1, CoVMBF-SSFP = 0.4 ± 0.1, p = 0.03; SDCE-FLASH = 10 ± 2, SDCE-SSFP = 32 ± 7, p = 0.01; SDSLP-FLASH = 0.02 ± 0.01, SDSLP-SSFP = 0.06 ± 0.02, p = 0.03). Example rest and stress data sets from the patient pool demonstrate that the low flip angle SSFP protocol

  8. Imaging of cartilage and bone: promises and pitfalls in clinical trials of osteoarthritis

    PubMed Central

    Eckstein, F.; Guermazi, A.; Gold, G.; Duryea, J.; Le Graverand, M.-P. Hellio; Wirth, W.; Miller, C.G.

    2015-01-01

    summary Imaging in clinical trials is used to evaluate subject eligibility, and/or efficacy of intervention, supporting decision making in drug development by ascertaining treatment effects on joint structure. This review focusses on imaging of bone and cartilage in clinical trials of (knee) osteoarthritis. We narratively review the full-text literature on imaging of bone and cartilage, adding primary experience in the implementation of imaging methods in clinical trials. Aims and constraints of applying imaging in clinical trials are outlined. The specific uses of semi-quantitative and quantitative imaging biomarkers of bone and cartilage in osteoarthritis trials are summarized, focusing on radiography and magnetic resonance imaging (MRI). Studies having compared both imaging methodologies directly and those having established a relationship between imaging biomarkers and clinical outcomes are highlighted. To make this review of practical use, recommendations are provided as to which imaging protocols are ideal for capturing specific aspects of bone and cartilage tissue, and pitfalls in their usage are highlighted. Further, the longitudinal sensitivity to change, of different imaging methods is reported for various patient strata. From these power calculations can be accomplished, provided the strength of the treatment effect is known. In conclusion, current imaging methodologies provide powerful tools for scoring and measuring morphological and compositional aspects of most articular tissues, capturing longitudinal change with reasonable to excellent sensitivity. When employed properly, imaging has tremendous potential for ascertaining treatment effects on various joint structures, potentially over shorter time scales than required for demonstrating effects on clinical outcomes. PMID:25278061

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

    PubMed

    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.

  10. Quantitative imaging assay for NF-κB nuclear translocation in primary human macrophages

    PubMed Central

    Noursadeghi, Mahdad; Tsang, Jhen; Haustein, Thomas; Miller, Robert F.; Chain, Benjamin M.; Katz, David R.

    2008-01-01

    Quantitative measurement of NF-κB nuclear translocation is an important research tool in cellular immunology. Established methodologies have a number of limitations, such as poor sensitivity, high cost or dependence on cell lines. Novel imaging methods to measure nuclear translocation of transcriptionally active components of NF-κB are being used but are also partly limited by the need for specialist imaging equipment or image analysis software. Herein we present a method for quantitative detection of NF-κB rel A nuclear translocation, using immunofluorescence microscopy and the public domain image analysis software ImageJ that can be easily adopted for cellular immunology research without the need for specialist image analysis expertise and at low cost. The method presented here is validated by demonstrating the time course and dose response of NF-κB nuclear translocation in primary human macrophages stimulated with LPS, and by comparison with a commercial NF-κB activation reporter cell line. PMID:18036607

  11. Quantitative MR imaging in fracture dating--Initial results.

    PubMed

    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

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

    NASA Astrophysics Data System (ADS)

    Chen, Chia-Chi; Hwang, Jeng-Jong; Ting, Gann; Tseng, Yun-Long; Wang, Shyh-Jen; Whang-Peng, Jaqueline

    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 ( R2=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 ( R2=0.907). γ Scintigraphy combined with [ 131I]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.

  13. DMS-prefiltered mass spectrometry for the detection of biomarkers

    NASA Astrophysics Data System (ADS)

    Coy, Stephen L.; Krylov, Evgeny V.; Nazarov, Erkinjon G.

    2008-04-01

    Technologies based on Differential Mobility Spectrometry (DMS) are ideally matched to rapid, sensitive, and selective detection of chemicals like biomarkers. Biomarkers linked to exposure to radiation, exposure to CWA's, exposure to toxic materials (TICs and TIMs) and to specific diseases are being examined in a number of laboratories. Screening for these types of exposure can be improved in accuracy and greatly speeded up by using DMS-MS instead of slower techniques like LC-MS and GC-MS. We have performed an extensive series of tests with nanospray-DMS-mass spectroscopy and standalone nanospray-DMS obtaining extensive information on chemistry and detectivity. DMS-MS systems implemented with low-resolution, low-cost, portable mass-spectrometry systems are very promising. Lowresolution mass spectrometry alone would be inadequate for the task, but with DMS pre-filtration to suppress interferences, can be quite effective, even for quantitative measurement. Bio-fluids and digests are well suited to ionization by electrospray and detection by mass-spectrometry, but signals from critical markers are overwhelmed by chemical noise from unrelated species, making essential quantitative analysis impossible. Sionex and collaborators have presented data using DMS to suppress chemical noise, allowing detection of cancer biomarkers in 10,000-fold excess of normal products 1,2. In addition, a linear dynamic range of approximately 2,000 has been demonstrated with accurate quantitation 3. We will review the range of possible applications and present new data on DMS-MS biomarker detection.

  14. Towards precision medicine: from quantitative imaging to radiomics

    PubMed Central

    Acharya, U. Rajendra; Hagiwara, Yuki; Sudarshan, Vidya K.; Chan, Wai Yee; Ng, Kwan Hoong

    2018-01-01

    Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine. PMID:29308604

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

    NASA Astrophysics Data System (ADS)

    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.

  16. Quantitative comparison of bright field and annular bright field imaging modes for characterization of oxygen octahedral tilts

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kim, Young-Min; Pennycook, Stephen J.; Borisevich, Albina Y.

    Octahedral tilt behavior is increasingly recognized as an important contributing factor to the physical behavior of perovskite oxide materials and especially their interfaces, necessitating the development of high-resolution methods of tilt mapping. There are currently two major approaches for quantitative imaging of tilts in scanning transmission electron microscopy (STEM), bright field (BF) and annular bright field (ABF). In this study, we show that BF STEM can be reliably used for measurements of oxygen octahedral tilts. While optimal conditions for BF imaging are more restricted with respect to sample thickness and defocus, we find that BF imaging with an aberration-corrected microscopemore » with the accelerating voltage of 300 kV gives us the most accurate quantitative measurement of the oxygen column positions. Using the tilted perovskite structure of BiFeO 3 (BFO) as our test sample, we simulate BF and ABF images in a wide range of conditions, identifying the optimal imaging conditions for each mode. Finally, we show that unlike ABF imaging, BF imaging remains directly quantitatively interpretable for a wide range of the specimen mistilt, suggesting that it should be preferable to the ABF STEM imaging for quantitative structure determination.« less

  17. Quantitative comparison of bright field and annular bright field imaging modes for characterization of oxygen octahedral tilts

    DOE PAGES

    Kim, Young-Min; Pennycook, Stephen J.; Borisevich, Albina Y.

    2017-04-29

    Octahedral tilt behavior is increasingly recognized as an important contributing factor to the physical behavior of perovskite oxide materials and especially their interfaces, necessitating the development of high-resolution methods of tilt mapping. There are currently two major approaches for quantitative imaging of tilts in scanning transmission electron microscopy (STEM), bright field (BF) and annular bright field (ABF). In this study, we show that BF STEM can be reliably used for measurements of oxygen octahedral tilts. While optimal conditions for BF imaging are more restricted with respect to sample thickness and defocus, we find that BF imaging with an aberration-corrected microscopemore » with the accelerating voltage of 300 kV gives us the most accurate quantitative measurement of the oxygen column positions. Using the tilted perovskite structure of BiFeO 3 (BFO) as our test sample, we simulate BF and ABF images in a wide range of conditions, identifying the optimal imaging conditions for each mode. Finally, we show that unlike ABF imaging, BF imaging remains directly quantitatively interpretable for a wide range of the specimen mistilt, suggesting that it should be preferable to the ABF STEM imaging for quantitative structure determination.« less

  18. Multiparametric Quantitative Ultrasound Imaging in Assessment of Chronic Kidney Disease.

    PubMed

    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 <2 of grade 2) and moderate to severe (at least 2 of grade 2 or 1 of grade 3) CKD groups. Multiparametric 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 < .01). Among 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

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

    PubMed

    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

  20. Comparison of Magnetic Resonance Imaging and Serum Biomarkers for Detection of Human Pluripotent Stem Cell-Derived Teratomas.

    PubMed

    Riegler, Johannes; Ebert, Antje; Qin, Xulei; Shen, Qi; Wang, Mouer; Ameen, Mohamed; Kodo, Kazuki; Ong, Sang-Ging; Lee, Won Hee; Lee, Grace; Neofytou, Evgenios; Gold, Joseph D; Connolly, Andrew J; Wu, Joseph C

    2016-02-09

    The use of cells derived from pluripotent stem cells (PSCs) for regenerative therapies confers a considerable risk for neoplastic growth and teratoma formation. Preclinical and clinical assessment of such therapies will require suitable monitoring strategies to understand and mitigate these risks. Here we generated human-induced pluripotent stem cells (iPSCs), selected clones that continued to express reprogramming factors after differentiation into cardiomyocytes, and transplanted these cardiomyocytes into immunocompromised rat hearts post-myocardial infarction. We compared magnetic resonance imaging (MRI), cardiac ultrasound, and serum biomarkers for their ability to delineate teratoma formation and growth. MRI enabled the detection of teratomas with a volume >8 mm(3). A combination of three plasma biomarkers (CEA, AFP, and HCG) was able to detect teratomas with a volume >17 mm(3) and with a sensitivity of more than 87%. Based on our findings, a combination of serum biomarkers with MRI screening may offer the highest sensitivity for teratoma detection and tracking. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  1. Accurate Construction of Photoactivated Localization Microscopy (PALM) Images for Quantitative Measurements

    PubMed Central

    Coltharp, Carla; Kessler, Rene P.; Xiao, Jie

    2012-01-01

    Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (tThresh and dThresh) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and

  2. Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem.

    PubMed

    Gurcan, Metin N; Tomaszewski, John; Overton, James A; Doyle, Scott; Ruttenberg, Alan; Smith, Barry

    2017-02-01

    Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology - QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Quantitative Analysis Tools and Digital Phantoms for Deformable Image Registration Quality Assurance.

    PubMed

    Kim, Haksoo; Park, Samuel B; Monroe, James I; Traughber, Bryan J; Zheng, Yiran; Lo, Simon S; Yao, Min; Mansur, David; Ellis, Rodney; Machtay, Mitchell; Sohn, Jason W

    2015-08-01

    This article proposes quantitative analysis tools and digital phantoms to quantify intrinsic errors of deformable image registration (DIR) systems and establish quality assurance (QA) procedures for clinical use of DIR systems utilizing local and global error analysis methods with clinically realistic digital image phantoms. Landmark-based image registration verifications are suitable only for images with significant feature points. To address this shortfall, we adapted a deformation vector field (DVF) comparison approach with new analysis techniques to quantify the results. Digital image phantoms are derived from data sets of actual patient images (a reference image set, R, a test image set, T). Image sets from the same patient taken at different times are registered with deformable methods producing a reference DVFref. Applying DVFref to the original reference image deforms T into a new image R'. The data set, R', T, and DVFref, is from a realistic truth set and therefore can be used to analyze any DIR system and expose intrinsic errors by comparing DVFref and DVFtest. For quantitative error analysis, calculating and delineating differences between DVFs, 2 methods were used, (1) a local error analysis tool that displays deformation error magnitudes with color mapping on each image slice and (2) a global error analysis tool that calculates a deformation error histogram, which describes a cumulative probability function of errors for each anatomical structure. Three digital image phantoms were generated from three patients with a head and neck, a lung and a liver cancer. The DIR QA was evaluated using the case with head and neck. © The Author(s) 2014.

  4. Objective breast tissue image classification using Quantitative Transmission ultrasound tomography

    NASA Astrophysics Data System (ADS)

    Malik, Bilal; Klock, John; Wiskin, James; Lenox, Mark

    2016-12-01

    Quantitative Transmission Ultrasound (QT) is a powerful and emerging imaging paradigm which has the potential to perform true three-dimensional image reconstruction of biological tissue. Breast imaging is an important application of QT and allows non-invasive, non-ionizing imaging of whole breasts in vivo. Here, we report the first demonstration of breast tissue image classification in QT imaging. We systematically assess the ability of the QT images’ features to differentiate between normal breast tissue types. The three QT features were used in Support Vector Machines (SVM) classifiers, and classification of breast tissue as either skin, fat, glands, ducts or connective tissue was demonstrated with an overall accuracy of greater than 90%. Finally, the classifier was validated on whole breast image volumes to provide a color-coded breast tissue volume. This study serves as a first step towards a computer-aided detection/diagnosis platform for QT.

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

    PubMed Central

    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

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

    NASA Astrophysics Data System (ADS)

    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.

  7. Lipid biomarker analysis for the quantitative analysis of airborne microorganisms

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Macnaughton, S.J.; Jenkins, T.L.; Cormier, M.R.

    1997-08-01

    There is an ever increasing concern regarding the presence of airborne microbial contaminants within indoor air environments. Exposure to such biocontaminants can give rise to large numbers of different health effects including infectious diseases, allergenic responses and respiratory problems, Biocontaminants typically round in indoor air environments include bacteria, fungi, algae, protozoa and dust mites. Mycotoxins, endotoxins, pollens and residues of organisms are also known to cause adverse health effects. A quantitative detection/identification technique independent of culturability that assays both culturable and non culturable biomass including endotoxin is critical in defining risks from indoor air biocontamination. Traditionally, methods employed for themore » monitoring of microorganism numbers in indoor air environments involve classical culture based techniques and/or direct microscopic counting. It has been repeatedly documented that viable microorganism counts only account for between 0.1-10% of the total community detectable by direct counting. The classic viable microbiologic approach doe`s not provide accurate estimates of microbial fragments or other indoor air components that can act as antigens and induce or potentiate allergic responses. Although bioaerosol samplers are designed to damage the microbes as little as possible, microbial stress has been shown to result from air sampling, aerosolization and microbial collection. Higher collection efficiency results in greater cell damage while less cell damage often results in lower collection efficiency. Filtration can collect particulates at almost 100% efficiency, but captured microorganisms may become dehydrated and damaged resulting in non-culturability, however, the lipid biomarker assays described herein do not rely on cell culture. Lipids are components that are universally distributed throughout cells providing a means to assess independent of culturability.« less

  8. The value of magnetic resonance imaging as a biomarker for amyotrophic lateral sclerosis: a systematic review.

    PubMed

    Grolez, G; Moreau, C; Danel-Brunaud, V; Delmaire, C; Lopes, R; Pradat, P F; El Mendili, M M; Defebvre, L; Devos, D

    2016-08-27

    Amyotrophic lateral sclerosis (ALS) is a fatal, rapidly progressive neurodegenerative disease that mainly affects the motor system. A number of potentially neuroprotective and neurorestorative disease-modifying drugs are currently in clinical development. At present, the evaluation of a drug's clinical efficacy in ALS is based on the ALS Functional Rating Scale Revised, motor tests and survival. However, these endpoints are general, variable and late-stage measures of the ALS disease process and thus require the long-term assessment of large cohorts. Hence, there is a need for more sensitive radiological biomarkers. Various sequences for magnetic resonance imaging (MRI) of the brain and spinal cord have may have value as surrogate biomarkers for use in future clinical trials. Here, we review the MRI findings in ALS, their clinical correlations, and their limitations and potential role as biomarkers. The PubMed database was screened to identify studies using MRI in ALS. We included general MRI studies with a control group and an ALS group and longitudinal studies even if a control group was lacking. A total of 116 studies were analysed with MRI data and clinical correlations. The most disease-sensitive MRI patterns are in motor regions but the brain is more broadly affected. Despite the existing MRI biomarkers, there is a need for large cohorts with long term MRI and clinical follow-up. MRI assessment could be improved by standardized MRI protocols with multicentre studies.

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

    PubMed

    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.

  10. A novel workflow combining plaque imaging, plaque and plasma proteomics identifies biomarkers of human coronary atherosclerotic plaque disruption.

    PubMed

    Lee, Regent; Fischer, Roman; Charles, Philip D; Adlam, David; Valli, Alessandro; Di Gleria, Katalin; Kharbanda, Rajesh K; Choudhury, Robin P; Antoniades, Charalambos; Kessler, Benedikt M; Channon, Keith M

    2017-01-01

    Atherosclerotic plaque rupture is the culprit event which underpins most acute vascular syndromes such as acute myocardial infarction. Novel biomarkers of plaque rupture could improve biological understanding and clinical management of patients presenting with possible acute vascular syndromes but such biomarker(s) remain elusive. Investigation of biomarkers in the context of de novo plaque rupture in humans is confounded by the inability to attribute the plaque rupture as the source of biomarker release, as plaque ruptures are typically associated with prompt down-stream events of myocardial necrosis and systemic inflammation. We developed a novel approach to identify potential biomarkers of plaque rupture by integrating plaque imaging, using optical coherence tomography, with both plaque and plasma proteomic analysis in a human model of angioplasty-induced plaque disruption. We compared two pairs of coronary plaque debris, captured by a FilterWire Device, and their corresponding control samples and found matrix metalloproteinase 9 (MMP9) to be significantly enriched in plaque. Plaque contents, as defined by optical coherence tomography, affect the systemic changes of MMP9. Disruption of lipid-rich plaque led to prompt elevation of plasma MMP9, whereas disruption of non-lipid-rich plaque resulted in delayed elevation of plasma MMP9. Systemic MMP9 elevation is independent of the associated myocardial necrosis and systemic inflammation (measured by Troponin I and C-reactive protein, respectively). This information guided the selection of a subset of subjects of for further label free proteomics analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). We discovered five novel, plaque-enriched proteins (lipopolysaccharide binding protein, Annexin A5, eukaryotic translocation initiation factor, syntaxin 11, cytochrome B5 reductase 3) to be significantly elevated in systemic circulation at 5 min after plaque disruption. This novel approach for biomarker

  11. Quantitative tomographic imaging of intermolecular FRET in small animals

    PubMed Central

    Venugopal, Vivek; Chen, Jin; Barroso, Margarida; Intes, Xavier

    2012-01-01

    Forster resonance energy transfer (FRET) is a nonradiative transfer of energy between two fluorescent molecules (a donor and an acceptor) in nanometer range proximity. FRET imaging methods have been applied to proteomic studies and drug discovery applications based on intermolecular FRET efficiency measurements and stoichiometric measurements of FRET interaction as quantitative parameters of interest. Importantly, FRET provides information about biomolecular interactions at a molecular level, well beyond the diffraction limits of standard microscopy techniques. The application of FRET to small animal imaging will allow biomedical researchers to investigate physiological processes occurring at nanometer range in vivo as well as in situ. In this work a new method for the quantitative reconstruction of FRET measurements in small animals, incorporating a full-field tomographic acquisition system with a Monte Carlo based hierarchical reconstruction scheme, is described and validated in murine models. Our main objective is to estimate the relative concentration of two forms of donor species, i.e., a donor molecule involved in FRETing to an acceptor close by and a nonFRETing donor molecule. PMID:23243567

  12. Alarmin S100A8/S100A9 as a biomarker for molecular imaging of local inflammatory activity.

    PubMed

    Vogl, Thomas; Eisenblätter, Michel; Völler, Tom; Zenker, Stefanie; Hermann, Sven; van Lent, Peter; Faust, Andreas; Geyer, Christiane; Petersen, Beatrix; Roebrock, Kirsten; Schäfers, Michael; Bremer, Christoph; Roth, Johannes

    2014-08-06

    Inflammation has a key role in the pathogenesis of various human diseases. The early detection, localization and monitoring of inflammation are crucial for tailoring individual therapies. However, reliable biomarkers to detect local inflammatory activities and to predict disease outcome are still missing. Alarmins, which are locally released during cellular stress, are early amplifiers of inflammation. Here, using optical molecular imaging, we demonstrate that the alarmin S100A8/S100A9 serves as a sensitive local and systemic marker for the detection of even sub-clinical disease activity in inflammatory and immunological processes like irritative and allergic contact dermatitis. In a model of collagen-induced arthritis, we use S100A8/S100A9 imaging to predict the development of disease activity. Furthermore, S100A8/S100A9 can act as a very early and sensitive biomarker in experimental leishmaniasis for phagocyte activation linked to an effective Th1-response. In conclusion, the alarmin S100A8/S100A9 is a valuable and sensitive molecular target for novel imaging approaches to monitor clinically relevant inflammatory disorders on a molecular level.

  13. Cell Death, Inflammation, Tumor Burden, and Proliferation Blood Biomarkers Predict Lung Cancer Radiotherapy Response and Correlate With Tumor Volume and Proliferation Imaging.

    PubMed

    Salem, Ahmed; Mistry, Hitesh; Backen, Alison; Hodgson, Clare; Koh, Pek; Dean, Emma; Priest, Lynsey; Haslett, Kate; Trigonis, Ioannis; Jackson, Alan; Asselin, Marie-Claude; Dive, Caroline; Renehan, Andrew; Faivre-Finn, Corinne; Blackhall, Fiona

    2018-05-01

    There is an unmet need to develop noninvasive biomarkers to stratify patients in drug-radiotherapy trials. In this pilot study we investigated lung cancer radiotherapy response and toxicity blood biomarkers and correlated findings with tumor volume and proliferation imaging. Blood samples were collected before and during (day 21) radiotherapy. Twenty-six cell-death, hypoxia, angiogenesis, inflammation, proliferation, invasion, and tumor-burden biomarkers were evaluated. Clinical and laboratory data were collected. Univariate analysis was performed on small-cell and non-small-cell lung cancer (NSCLC) whereas multivariate analysis focused on NSCLC. Blood samples from 78 patients were analyzed. Sixty-one (78.2%) harbored NSCLC, 48 (61.5%) received sequential chemoradiotherapy. Of tested baseline biomarkers, undetectable interleukin (IL)-1b (hazard ratio [HR], 4.02; 95% confidence interval [CI], 2.04-7.93; P < .001) was the only significant survival covariate. Of routinely collected laboratory tests, high baseline neutrophil count was a significant survival covariate (HR, 1.07; 95% CI, 1.02-1.11; P = .017). Baseline IL-1b and neutrophil count were prognostic for survival in a multivariate model. The addition of day-21 cytokeratin-19 antigen modestly improved this model's survival prediction (concordance probability, 0.75-0.78). Chemotherapy (P < .001) and baseline keratinocyte growth factor (P = .019) predicted acute esophagitis, but only chemotherapy remained significant after Bonferroni correction. Baseline angioprotein-1 and hepatocyte growth factor showed a direct correlation with tumor volume whereas changes in vascular cell adhesion molecule 1 showed significant correlations with 18F-fluorothymidine (FLT) positron emission tomography (PET). Select biomarkers are prognostic after radiotherapy in this lung cancer series. The correlation between circulating biomarkers and 18F-FLT PET is shown, to our knowledge for the first time, highlighting their potential

  14. Characterization of Regional Left Ventricular Function in Nonhuman Primates Using Magnetic Resonance Imaging Biomarkers: A Test-Retest Repeatability and Inter-Subject Variability Study

    PubMed Central

    Sampath, Smita; Klimas, Michael; Feng, Dai; Baumgartner, Richard; Manigbas, Elaine; Liang, Ai-Leng; Evelhoch, Jeffrey L.; Chin, Chih-Liang

    2015-01-01

    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-rate, diastolic E

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

    NASA Astrophysics Data System (ADS)

    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.

  16. Structural Imaging and Parkinson's Disease: Moving Toward Quantitative Markers of Disease Progression.

    PubMed

    Sterling, N W; Lewis, M M; Du, G; Huang, X

    2016-05-27

    Parkinson's disease (PD) is a progressive age-related neurodegenerative disorder. Although the pathological hallmark of PD is dopaminergic cell death in the substantia nigra pars compacta, widespread neurodegenerative changes occur throughout the brain as disease progresses. Postmortem studies, for example, have demonstrated the presence of Lewy pathology, apoptosis, and loss of neurotransmitters and interneurons in both cortical and subcortical regions of PD patients. Many in vivo structural imaging studies have attempted to gauge PD-related pathology, particularly in gray matter, with the hope of identifying an imaging biomarker. Reports of brain atrophy in PD, however, have been inconsistent, most likely due to differences in the studied populations (i.e. different disease stages and/or clinical subtypes), experimental designs (i.e. cross-sectional vs. longitudinal), and image analysis methodologies (i.e. automatic vs. manual segmentation). This review attempts to summarize the current state of gray matter structural imaging research in PD in relationship to disease progression, reconciling some of the differences in reported results, and to identify challenges and future avenues.

  17. Quantitative phase imaging of retinal cells (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    LaForest, Timothé; Carpentras, Dino; Kowalczuk, Laura; Behar-Cohen, Francine; Moser, Christophe

    2017-02-01

    Vision process is ruled by several cells layers of the retina. Before reaching the photoreceptors, light entering the eye has to pass through a few hundreds of micrometers thick layer of ganglion and neurons cells. Macular degeneration is a non-curable disease of themacula occurring with age. This disease can be diagnosed at an early stage by imaging neuronal cells in the retina and observing their death chronically. These cells are phase objects locatedon a background that presents an absorption pattern and so difficult to see with standard imagingtechniques in vivo. Phase imaging methods usually need the illumination system to be on the opposite side of the sample with respect to theimaging system. This is a constraintand a challenge for phase imaging in-vivo. Recently, the possibility of performing phase contrast imaging from one side using properties of scattering media has been shown. This phase contrast imaging is based on the back illumination generated by the sample itself. Here, we present a reflection phase imaging technique based on oblique back-illumination. The oblique back-illumination creates a dark field image of the sample. Generating asymmetric oblique illumination allows obtaining differential phase contrast image, which in turn can be processed to recover a quantitative phase image. In the case of the eye, a transcleral illumination can generate oblique incident light on the retina and the choroidal layer.The back reflected light is then collected by the eye lens to produce dark field image. We show experimental results of retinal phase imagesin ex vivo samples of human and pig retina.

  18. Towards quantitative magnetic particle imaging: A comparison with magnetic particle spectroscopy

    NASA Astrophysics Data System (ADS)

    Paysen, Hendrik; Wells, James; Kosch, Olaf; Steinhoff, Uwe; Trahms, Lutz; Schaeffter, Tobias; Wiekhorst, Frank

    2018-05-01

    Magnetic Particle Imaging (MPI) is a quantitative imaging modality with promising features for several biomedical applications. Here, we study quantitatively the raw data obtained during MPI measurements. We present a method for the calibration of the MPI scanner output using measurements from a magnetic particle spectrometer (MPS) to yield data in units of magnetic moments. The calibration technique is validated in a simplified MPI mode with a 1D excitation field. Using the calibrated results from MPS and MPI, we determine and compare the detection limits for each system. The detection limits were found to be 5.10-12 Am2 for MPS and 3.6.10-10 Am2 for MPI. Finally, the quantitative information contained in a standard MPI measurement with a 3D excitation is analyzed and compared to the previous results, showing a decrease in signal amplitudes of the odd harmonics related to the case of 1D excitation. We propose physical explanations for all acquired results; and discuss the possible benefits for the improvement of MPI technology.

  19. Preclinical cerebrospinal fluid and volumetric magnetic resonance imaging biomarkers in Swedish familial Alzheimer's disease.

    PubMed

    Thordardottir, Steinunn; Ståhlbom, Anne Kinhult; Ferreira, Daniel; Almkvist, Ove; Westman, Eric; Zetterberg, Henrik; Eriksdotter, Maria; Blennow, Kaj; Graff, Caroline

    2015-01-01

    It is currently believed that therapeutic interventions will be most effective when introduced at the preclinical stage of Alzheimer's disease (AD). This underlines the importance of biomarkers to detect AD pathology in vivo before clinical disease onset. To examine the evolution of cerebrospinal fluid (CSF) biomarker and brain structure changes in the preclinical phase of familial AD. The study included members from four Swedish families at risk for carrying an APPswe, APParc, PSEN1 H163Y, or PSEN1 I143T mutation. Magnetic resonance imaging (MRI) scans were obtained from 13 mutation carriers (MC) and 20 non-carriers (NC) and analyzed using vertex-based analyses of cortical thickness and volume. CSF was collected from 10 MC and 12 NC from familial AD families and analyzed for Aβ42, total tau (T-tau) and phospho-tau (P-tau). The MC had significantly lower levels of CSF Aβ42 and higher levels T-tau and P-tau than the NC. There was a trend for a decrease in Aβ42 15-20 years before expected onset of clinical symptoms, while increasing T-tau and P-tau was not found until close to the expected clinical onset. The MC had decreased volume on MRI in the left precuneus, superior temporal gyrus, and fusiform gyrus. Aberrant biomarker levels in CSF as well as regional brain atrophy are present in preclinical familial AD, several years before the expected onset of clinical symptoms.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Guo, Xuejiang; Tang, Keqi

    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 wouldmore » 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

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lee, J; Nishikawa, R; Reiser, I

    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 benignmore » 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

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

    PubMed

    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.

  3. Quantitative characterization of turbidity by radiative transfer based reflectance imaging

    PubMed Central

    Tian, Peng; Chen, Cheng; Jin, Jiahong; Hong, Heng; Lu, Jun Q.; Hu, Xin-Hua

    2018-01-01

    A new and noncontact approach of multispectral reflectance imaging has been developed to inversely determine the absorption coefficient of μa, the scattering coefficient of μs and the anisotropy factor g of a turbid target from one measured reflectance image. The incident beam was profiled with a diffuse reflectance standard for deriving both measured and calculated reflectance images. A GPU implemented Monte Carlo code was developed to determine the parameters with a conjugate gradient descent algorithm and the existence of unique solutions was shown. We noninvasively determined embedded region thickness in heterogeneous targets and estimated in vivo optical parameters of nevi from 4 patients between 500 and 950nm for melanoma diagnosis to demonstrate the potentials of quantitative reflectance imaging. PMID:29760971

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

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

    1990-09-01

    This report summarizes goals and accomplishments of the research program supported under DOE Grant No. FG02-86ER60418 entitled Instrumentation and Quantitative Methods of Evaluation, with R. Beck, P. I. and M. Cooper, Co-P.I. during the period January 15, 1990 through September 1, 1990. This program addresses the problems involving the basic science and technology underlying the physical and conceptual tools of radioactive tracer methodology as they relate to the measurement of structural and functional parameters of physiologic importance in health and disease. The principal tool is quantitative radionuclide imaging. The overall objective of this program is to further the development andmore » transfer of radiotracer methodology from basic theory to routine clinical practice in order that individual patients and society as a whole will receive the maximum net benefit from the new knowledge gained. The focus of the research is on the development of new instruments and radiopharmaceuticals, and the evaluation of these through the phase of clinical feasibility. 7 figs.« less

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

    PubMed Central

    Herrmann, Kelsey; Johansen, Mette L.; Craig, Sonya E.; Vincent, Jason; Howell, Michael; Gao, Ying; Lu, Lan; Erokwu, Bernadette; Agnes, Richard S.; Lu, Zheng-Rong; Pokorski, Jonathan K.; Basilion, James; Gulani, Vikas; Griswold, Mark; Flask, Chris; Brady-Kalnay, Susann M.

    2015-01-01

    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-DOTA)3 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-DOTA)3 agent over time in comparison to non-targeted control agents. Our results demonstrate that the targeted SBK2-Tris-(Gd-DOTA)3 agent, a scrambled-Tris-(Gd-DOTA)3 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-DOTA)3 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-DOTA)3 agent over time compared to the non-specific contrast agent currently in clinical use. PMID:26435847

  6. Development of a Multi-Biomarker Disease Activity Test for Rheumatoid Arthritis

    PubMed Central

    Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A.; Turner, Mary; Sutton, Chris; Smith, Dustin R.; Haney, Douglas J.; Chernoff, David; Hesterberg, Lyndal K.; Carulli, John P.; Taylor, Peter C.; Shadick, Nancy A.; Weinblatt, Michael E.; Curtis, Jeffrey R.

    2013-01-01

    Background Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. Objectives To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Methods Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. Results 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities

  7. Quantitative bone scan lesion area as an early surrogate outcome measure indicative of overall survival in metastatic prostate cancer.

    PubMed

    Brown, Matthew S; Kim, Grace Hyun J; Chu, Gregory H; Ramakrishna, Bharath; Allen-Auerbach, Martin; Fischer, Cheryce P; Levine, Benjamin; Gupta, Pawan K; Schiepers, Christiaan W; Goldin, Jonathan G

    2018-01-01

    A clinical validation of the bone scan lesion area (BSLA) as a quantitative imaging biomarker was performed in metastatic castration-resistant prostate cancer (mCRPC). BSLA was computed from whole-body bone scintigraphy at baseline and week 12 posttreatment in a cohort of 198 mCRPC subjects (127 treated and 71 placebo) from a clinical trial involving a different drug from the initial biomarker development. BSLA computation involved automated image normalization, lesion segmentation, and summation of the total area of segmented lesions on bone scan AP and PA views as a measure of tumor burden. As a predictive biomarker, treated subjects with baseline BSLA [Formula: see text] had longer survival than those with higher BSLA ([Formula: see text] and [Formula: see text]). As a surrogate outcome biomarker, subjects were categorized as progressive disease (PD) if the BSLA increased by a prespecified 30% or more from baseline to week 12 and non-PD otherwise. Overall survival rates between PD and non-PD groups were statistically different ([Formula: see text] and [Formula: see text]). Subjects without PD at week 12 had longer survival than subjects with PD: median 398 days versus 280 days. BSLA has now been demonstrated to be an early surrogate outcome for overall survival in different prostate cancer drug treatments.

  8. A comparison of phase imaging and quantitative susceptibility mapping in the imaging of multiple sclerosis lesions at ultrahigh field.

    PubMed

    Cronin, Matthew John; Wharton, Samuel; Al-Radaideh, Ali; Constantinescu, Cris; Evangelou, Nikos; Bowtell, Richard; Gowland, Penny Anne

    2016-06-01

    The aim of this study was to compare the use of high-resolution phase and QSM images acquired at ultra-high field in the investigation of multiple sclerosis (MS) lesions with peripheral rings, and to discuss their usefulness for drawing inferences about underlying tissue composition. Thirty-nine Subjects were scanned at 7 T, using 3D T 2*-weighted and T 1-weighted sequences. Phase images were then unwrapped and filtered, and quantitative susceptibility maps were generated using a thresholded k-space division method. Lesions were compared visually and using a 1D profiling algorithm. Lesions displaying peripheral rings in the phase images were identified in 10 of the 39 subjects. Dipolar projections were apparent in the phase images outside of the extent of several of these lesions; however, QSM images showed peripheral rings without such projections. These projections appeared ring-like in a small number of phase images where no ring was observed in QSM. 1D profiles of six well-isolated example lesions showed that QSM contrast corresponds more closely to the magnitude images than phase contrast. Phase images contain dipolar projections, which confounds their use in the investigation of tissue composition in MS lesions. Quantitative susceptibility maps correct these projections, providing insight into the composition of MS lesions showing peripheral rings.

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

    PubMed

    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.

  10. Quantitative image analysis for investigating cell-matrix interactions

    NASA Astrophysics Data System (ADS)

    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.

  11. Development of two-photon fluorescence microscopy for quantitative imaging in turbid tissues

    NASA Astrophysics Data System (ADS)

    Coleno, Mariah Lee

    Two-photon laser scanning fluorescence microscopy (TPM) is a high resolution, non-invasive biological imaging technique that can be used to image turbid tissues both in vitro and in vivo at depths of several hundred microns. Although TPM has been widely used to image tissue structures, no one has focused on using TPM to extract quantitative information from turbid tissues at depth. As a result, this thesis addresses the quantitative characterization of two-photon signals in turbid media. Initially, a two-photon microscope system is constructed, and two-photon images that validate system performance are obtained. Then TPM is established as an imaging technique that can be used to validate theoretical observations already listed in the literature. In particular, TPM is found to validate the exponential dependence of the fluorescence intensity decay with depth in turbid tissue model systems. Results from these studies next prompted experimental investigation into whether TPM could be used to determine tissue optical properties. Comparing the exponential dependence of the decay with a Monte Carlo model involving tissue optical properties, TPM is shown to be useful for determining the optical properties (total attenuation coefficient) of thick, turbid tissues on a small spatial scale. Next, a role for TPM for studying and optimizing wound healing is demonstrated. In particular, TPM is used to study the effects of perturbations (growth factors, PDT) on extracellular matrix remodeling in artificially engineered skin tissues. Results from these studies combined with tissue contraction studies are shown to demonstrate ways to modulate tissues to optimize the wound healing immune response and reduce scarring. In the end, TPM is shown to be an extremely important quantitative biological imaging technique that can be used to optimize wound repair.

  12. Optimal tumor sampling for immunostaining of biomarkers in breast carcinoma

    PubMed Central

    2011-01-01

    Introduction Biomarkers, such as Estrogen Receptor, are used to determine therapy and prognosis in breast carcinoma. Immunostaining assays of biomarker expression have a high rate of inaccuracy; for example, estimates are as high as 20% for Estrogen Receptor. Biomarkers have been shown to be heterogeneously expressed in breast tumors and this heterogeneity may contribute to the inaccuracy of immunostaining assays. Currently, no evidence-based standards exist for the amount of tumor that must be sampled in order to correct for biomarker heterogeneity. The aim of this study was to determine the optimal number of 20X fields that are necessary to estimate a representative measurement of expression in a whole tissue section for selected biomarkers: ER, HER-2, AKT, ERK, S6K1, GAPDH, Cytokeratin, and MAP-Tau. Methods Two collections of whole tissue sections of breast carcinoma were immunostained for biomarkers. Expression was quantified using the Automated Quantitative Analysis (AQUA) method of quantitative immunofluorescence. Simulated sampling of various numbers of fields (ranging from one to thirty five) was performed for each marker. The optimal number was selected for each marker via resampling techniques and minimization of prediction error over an independent test set. Results The optimal number of 20X fields varied by biomarker, ranging between three to fourteen fields. More heterogeneous markers, such as MAP-Tau protein, required a larger sample of 20X fields to produce representative measurement. Conclusions The optimal number of 20X fields that must be sampled to produce a representative measurement of biomarker expression varies by marker with more heterogeneous markers requiring a larger number. The clinical implication of these findings is that breast biopsies consisting of a small number of fields may be inadequate to represent whole tumor biomarker expression for many markers. Additionally, for biomarkers newly introduced into clinical use, especially if

  13. Quantitative imaging of mammalian transcriptional dynamics: from single cells to whole embryos.

    PubMed

    Zhao, Ziqing W; White, Melanie D; Bissiere, Stephanie; Levi, Valeria; Plachta, Nicolas

    2016-12-23

    Probing dynamic processes occurring within the cell nucleus at the quantitative level has long been a challenge in mammalian biology. Advances in bio-imaging techniques over the past decade have enabled us to directly visualize nuclear processes in situ with unprecedented spatial and temporal resolution and single-molecule sensitivity. Here, using transcription as our primary focus, we survey recent imaging studies that specifically emphasize the quantitative understanding of nuclear dynamics in both time and space. These analyses not only inform on previously hidden physical parameters and mechanistic details, but also reveal a hierarchical organizational landscape for coordinating a wide range of transcriptional processes shared by mammalian systems of varying complexity, from single cells to whole embryos.

  14. A quantitative image cytometry technique for time series or population analyses of signaling networks.

    PubMed

    Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

    2010-04-01

    Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

  15. Combined fluorescence and reflectance spectroscopy for in vivo quantification of cancer biomarkers in low- and high-grade glioma surgery

    NASA Astrophysics Data System (ADS)

    Valdés, Pablo A.; Kim, Anthony; Leblond, Frederic; Conde, Olga M.; Harris, Brent T.; Paulsen, Keith D.; Wilson, Brian C.; Roberts, David W.

    2011-11-01

    Biomarkers are indicators of biological processes and hold promise for the diagnosis and treatment of disease. Gliomas represent a heterogeneous group of brain tumors with marked intra- and inter-tumor variability. The extent of surgical resection is a significant factor influencing post-surgical recurrence and prognosis. Here, we used fluorescence and reflectance spectral signatures for in vivo quantification of multiple biomarkers during glioma surgery, with fluorescence contrast provided by exogenously-induced protoporphyrin IX (PpIX) following administration of 5-aminolevulinic acid. We performed light-transport modeling to quantify multiple biomarkers indicative of tumor biological processes, including the local concentration of PpIX and associated photoproducts, total hemoglobin concentration, oxygen saturation, and optical scattering parameters. We developed a diagnostic algorithm for intra-operative tissue delineation that accounts for the combined tumor-specific predictive capabilities of these quantitative biomarkers. Tumor tissue delineation achieved accuracies of up to 94% (specificity = 94%, sensitivity = 94%) across a range of glioma histologies beyond current state-of-the-art optical approaches, including state-of-the-art fluorescence image guidance. This multiple biomarker strategy opens the door to optical methods for surgical guidance that use quantification of well-established neoplastic processes. Future work would seek to validate the predictive power of this proof-of-concept study in a separate larger cohort of patients.

  16. Quantitative coronary angiography using image recovery techniques for background estimation in unsubtracted images

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wong, Jerry T.; Kamyar, Farzad; Molloi, Sabee

    2007-10-15

    Densitometry measurements have been performed previously using subtracted images. However, digital subtraction angiography (DSA) in coronary angiography is highly susceptible to misregistration artifacts due to the temporal separation of background and target images. Misregistration artifacts due to respiration and patient motion occur frequently, and organ motion is unavoidable. Quantitative densitometric techniques would be more clinically feasible if they could be implemented using unsubtracted images. The goal of this study is to evaluate image recovery techniques for densitometry measurements using unsubtracted images. A humanoid phantom and eight swine (25-35 kg) were used to evaluate the accuracy and precision of the followingmore » image recovery techniques: Local averaging (LA), morphological filtering (MF), linear interpolation (LI), and curvature-driven diffusion image inpainting (CDD). Images of iodinated vessel phantoms placed over the heart of the humanoid phantom or swine were acquired. In addition, coronary angiograms were obtained after power injections of a nonionic iodinated contrast solution in an in vivo swine study. Background signals were estimated and removed with LA, MF, LI, and CDD. Iodine masses in the vessel phantoms were quantified and compared to known amounts. Moreover, the total iodine in left anterior descending arteries was measured and compared with DSA measurements. In the humanoid phantom study, the average root mean square errors associated with quantifying iodine mass using LA and MF were approximately 6% and 9%, respectively. The corresponding average root mean square errors associated with quantifying iodine mass using LI and CDD were both approximately 3%. In the in vivo swine study, the root mean square errors associated with quantifying iodine in the vessel phantoms with LA and MF were approximately 5% and 12%, respectively. The corresponding average root mean square errors using LI and CDD were both 3%. The standard

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

    PubMed Central

    Spagnolo, Daniel M.; Gyanchandani, Rekha; Al-Kofahi, Yousef; Stern, Andrew M.; Lezon, Timothy R.; Gough, Albert; Meyer, Dan E.; Ginty, Fiona; Sarachan, Brion; Fine, Jeffrey; Lee, Adrian V.; Taylor, D. Lansing; Chennubhotla, S. Chakra

    2016-01-01

    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 components

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

    PubMed

    Spagnolo, Daniel M; Gyanchandani, Rekha; Al-Kofahi, Yousef; Stern, Andrew M; Lezon, Timothy R; Gough, Albert; Meyer, Dan E; Ginty, Fiona; Sarachan, Brion; Fine, Jeffrey; Lee, Adrian V; Taylor, D Lansing; Chennubhotla, S Chakra

    2016-01-01

    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. 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. 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. 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 components within the TME. We hypothesize that PMI will

  19. Single-exposure quantitative phase imaging in color-coded LED microscopy.

    PubMed

    Lee, Wonchan; Jung, Daeseong; Ryu, Suho; Joo, Chulmin

    2017-04-03

    We demonstrate single-shot quantitative phase imaging (QPI) in a platform of color-coded LED microscopy (cLEDscope). The light source in a conventional microscope is replaced by a circular LED pattern that is trisected into subregions with equal area, assigned to red, green, and blue colors. Image acquisition with a color image sensor and subsequent computation based on weak object transfer functions allow for the QPI of a transparent specimen. We also provide a correction method for color-leakage, which may be encountered in implementing our method with consumer-grade LEDs and image sensors. Most commercially available LEDs and image sensors do not provide spectrally isolated emissions and pixel responses, generating significant error in phase estimation in our method. We describe the correction scheme for this color-leakage issue, and demonstrate improved phase measurement accuracy. The computational model and single-exposure QPI capability of our method are presented by showing images of calibrated phase samples and cellular specimens.

  20. The quantitative control and matching of an optical false color composite imaging system

    NASA Astrophysics Data System (ADS)

    Zhou, Chengxian; Dai, Zixin; Pan, Xizhe; Li, Yinxi

    1993-10-01

    Design of an imaging system for optical false color composite (OFCC) capable of high-precision density-exposure time control and color balance is presented. The system provides high quality FCC image data that can be analyzed using a quantitative calculation method. The quality requirement to each part of the image generation system is defined, and the distribution of satellite remote sensing image information is analyzed. The proposed technology makes it possible to present the remote sensing image data more effectively and accurately.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  4. Label-free hyperspectral dark-field microscopy for quantitative scatter imaging

    NASA Astrophysics Data System (ADS)

    Cheney, Philip; McClatchy, David; Kanick, Stephen; Lemaillet, Paul; Allen, David; Samarov, Daniel; Pogue, Brian; Hwang, Jeeseong

    2017-03-01

    A hyperspectral dark-field microscope has been developed for imaging spatially distributed diffuse reflectance spectra from light-scattering samples. In this report, quantitative scatter spectroscopy is demonstrated with a uniform scattering phantom, namely a solution of polystyrene microspheres. A Monte Carlo-based inverse model was used to calculate the reduced scattering coefficients of samples of different microsphere concentrations from wavelength-dependent backscattered signal measured by the dark-field microscope. The results are compared to the measurement results from a NIST double-integrating sphere system for validation. Ongoing efforts involve quantitative mapping of scattering and absorption coefficients in samples with spatially heterogeneous optical properties.

  5. Qualification of a Quantitative Laryngeal Imaging System Using Videostroboscopy and Videokymography

    PubMed Central

    Popolo, Peter S.; Titze, Ingo R.

    2008-01-01

    Objectives: We sought to determine whether full-cycle glottal width measurements could be obtained with a quantitative laryngeal imaging system using videostroboscopy, and whether glottal width and vocal fold length measurements were repeatable and reliable. Methods: Synthetic vocal folds were phonated on a laboratory bench, and dynamic images were obtained in repeated trials by use of videostroboscopy and videokymography (VKG) with an imaging system equipped with a 2-point laser projection device for measuring absolute dimensions. Video images were also obtained with an industrial videoscope system with a built-in laser measurement capability. Maximum glottal width and vocal fold length were compared among these 3 methods. Results: The average variation in maximum glottal width measurements between stroboscopic data and VKG data was 3.10%. The average variations in width measurements between the clinical system and the industrial system were 1.93% (stroboscopy) and 3.49% (VKG). The variations in vocal fold length were similarly small. The standard deviations across trials were 0.29 mm for width and 0.48 mm for length (stroboscopy), 0.18 mm for width (VKG), and 0.25 mm for width and 0.84 mm for length (industrial). Conclusions: For stable, periodic vibration, the full extent of the glottal width can be reliably measured with the quantitative videostroboscopy system. PMID:18646436

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

    PubMed

    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 < .001). The elevation of semi-quantitative serum procalcitonin levels was more frequently observed in subjects with proven etiology, especially pneumococcal 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

  7. Green light for quantitative live-cell imaging in plants.

    PubMed

    Grossmann, Guido; Krebs, Melanie; Maizel, Alexis; Stahl, Yvonne; Vermeer, Joop E M; Ott, Thomas

    2018-01-29

    Plants exhibit an intriguing morphological and physiological plasticity that enables them to thrive in a wide range of environments. To understand the cell biological basis of this unparalleled competence, a number of methodologies have been adapted or developed over the last decades that allow minimal or non-invasive live-cell imaging in the context of tissues. Combined with the ease to generate transgenic reporter lines in specific genetic backgrounds or accessions, we are witnessing a blooming in plant cell biology. However, the imaging of plant cells entails a number of specific challenges, such as high levels of autofluorescence, light scattering that is caused by cell walls and their sensitivity to environmental conditions. Quantitative live-cell imaging in plants therefore requires adapting or developing imaging techniques, as well as mounting and incubation systems, such as micro-fluidics. Here, we discuss some of these obstacles, and review a number of selected state-of-the-art techniques, such as two-photon imaging, light sheet microscopy and variable angle epifluorescence microscopy that allow high performance and minimal invasive live-cell imaging in plants. © 2018. Published by The Company of Biologists Ltd.

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

    PubMed Central

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

    2007-01-01

    Background 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. Methods 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. Results 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. Conclusion 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. PMID:17822559

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

    PubMed

    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

  10. A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

    PubMed Central

    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

  11. Quantitative description of solid breast nodules by ultrasound imaging

    NASA Astrophysics Data System (ADS)

    Sehgal, Chandra M.; Kangas, Sarah A.; Cary, Ted W.; Weinstein, Susan P.; Schultz, Susan M.; Arger, Peter H.; Conant, Emily F.

    2004-04-01

    Various features based on qualitative description of shape, contour, margin and echogenicity of solid breast nodules are used clinically to classify them as benign or malignant. However, there continues to be considerable overlap in the sonographic findings for the two types of lesions. This is related to the lack of precise definition of the various features as well as to the lack of agreement among observers, among other factors. The goal of this investigation is to define clinical features quantitatively and evaluate if they differ significantly in malignant and benign cases. Features based on margin sharpness and continuity, shadowing, and attenuation were defined and calculated from the images. These features were tested on digital phantoms. Following the evaluation, the features were measured on 116 breast sonograms of 58 biopsy-proven masses. Biopsy had been recommended for all of these breast lesions based on physical exams and conventional diagnostic imaging of ultrasound and/or mammography. Of the 58 masses, 20 were identified as malignant and 38 as benign histologically. Margin sharpness, margin echogenicity, and angular margin variation were significantly different for the two groups (p<0.03, two-tailed student t-test). Shadowing and attenuation of ultrasound did not show significant difference. The results of this preliminary study show that quantitative margin characteristics measured for the malignant and benign masses from the ultrasound images are different and could potentially be useful in identifying a subgroup of solid breast nodules that have low risk of being malignant.

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

    PubMed

    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.

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

    PubMed Central

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

    2014-01-01

    Objective To develop and validate an image analysis method for quantitative analysis of γ-oryzanol in cold pressed rice bran oil. Methods 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. Results Both assays provided good linearity, accuracy, reproducibility and selectivity for determination of γ-oryzanol. Conclusions 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. PMID:25182282

  14. Dual-isotope Cryo-imaging Quantitative Autoradiography (CIQA): Anvestigating Antibody-Drug Conjugate Distribution And Payload Delivery Through Imaging.

    PubMed

    Ilovich, Ohad; Qutaish, Mohammed; Hesterman, Jacob; Orcutt, Kelly; Hoppin, Jack; Polyak, Ildiko; Seaman, Marc; Abu-Yousif, Adnan; Cvet, Donna; Bradley, Daniel

    2018-05-04

    In vitro properties of antibody drug conjugates (ADCs) such as binding, internalization, and cytotoxicity are often well characterized prior to in vivo studies. Interpretation of in vivo studies could significantly be enhanced by molecular imaging tools. We present here a dual-isotope cryo-imaging quantitative autoradiography (CIQA) methodology combined with advanced 3D imaging and analysis allowing for the simultaneous study of both antibody and payload distribution in tissues of interest. in a pre-clinical setting. Methods: TAK-264, an investigational anti-guanylyl cyclase C (GCC) targeting ADC was synthesized utilizing tritiated Monomethyl auristatin E (MMAE). The tritiated ADC was then conjugated to DTPA, labeled with indium-111 and evaluated in vivo in GCC-positive and GCC-negative tumor-bearing animals. Results: Cryo-imaging Quantitative Autoradiography (CIQA) reveals the time course of drug release from ADC and its distribution into various tumor regions seemingly impenetrablethat are less accessible to the antibody. For GCC-positive tumors, a representative section obtained 96 hours post tracer injection showed only 0.8% of the voxels have co-localized signal versus over 15% of the voxels for a GCC-negative tumor section., suggesting successful and specific cleaving of the toxin in the antigen positive lesions. Conclusion: The combination of a veteran established autoradiography technology with advanced image analysis methodologies affords an experimental tool that can support detailed characterization of ADC tumor penetration and pharmacokinetics. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

  15. Phase II cancer clinical trials for biomarker-guided treatments.

    PubMed

    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.

  16. Quantitation of tumor uptake with molecular breast imaging.

    PubMed

    Bache, Steven T; Kappadath, S Cheenu

    2017-09-01

    We developed scatter and attenuation-correction techniques for quantifying images obtained with Molecular Breast Imaging (MBI) systems. To investigate scatter correction, energy spectra of a 99m Tc point source were acquired with 0-7-cm-thick acrylic to simulate scatter between the detector heads. System-specific scatter correction factor, k, was calculated as a function of thickness using a dual energy window technique. To investigate attenuation correction, a 7-cm-thick rectangular phantom containing 99m Tc-water simulating breast tissue and fillable spheres simulating tumors was imaged. Six spheres 10-27 mm in diameter were imaged with sphere-to-background ratios (SBRs) of 3.5, 2.6, and 1.7 and located at depths of 0.5, 1.5, and 2.5 cm from the center of the water bath for 54 unique tumor scenarios (3 SBRs × 6 sphere sizes × 3 depths). Phantom images were also acquired in-air under scatter- and attenuation-free conditions, which provided ground truth counts. To estimate true counts, T, from each tumor, the geometric mean (GM) of the counts within a prescribed region of interest (ROI) from the two projection images was calculated as T=C1C2eμtF, where C are counts within the square ROI circumscribing each sphere on detectors 1 and 2, μ is the linear attenuation coefficient of water, t is detector separation, and the factor F accounts for background activity. Four unique F definitions-standard GM, background-subtraction GM, MIRD Primer 16 GM, and a novel "volumetric GM"-were investigated. Error in T was calculated as the percentage difference with respect to in-air. Quantitative accuracy using the different GM definitions was calculated as a function of SBR, depth, and sphere size. Sensitivity of quantitative accuracy to ROI size was investigated. We developed an MBI simulation to investigate the robustness of our corrections for various ellipsoidal tumor shapes and detector separations. Scatter correction factor k varied slightly (0.80-0.95) over a compressed

  17. Accurate single-shot quantitative phase imaging of biological specimens with telecentric digital holographic microscopy.

    PubMed

    Doblas, Ana; Sánchez-Ortiga, Emilio; Martínez-Corral, Manuel; Saavedra, Genaro; Garcia-Sucerquia, Jorge

    2014-04-01

    The advantages of using a telecentric imaging system in digital holographic microscopy (DHM) to study biological specimens are highlighted. To this end, the performances of nontelecentric DHM and telecentric DHM are evaluated from the quantitative phase imaging (QPI) point of view. The evaluated stability of the microscope allows single-shot QPI in DHM by using telecentric imaging systems. Quantitative phase maps of a section of the head of the drosophila melanogaster fly and of red blood cells are obtained via single-shot DHM with no numerical postprocessing. With these maps we show that the use of telecentric DHM provides larger field of view for a given magnification and permits more accurate QPI measurements with less number of computational operations.

  18. Three modality image registration of brain SPECT/CT and MR images for quantitative analysis of dopamine transporter imaging

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Yuzuho; Takeda, Yuta; Hara, Takeshi; Zhou, Xiangrong; Matsusako, Masaki; Tanaka, Yuki; Hosoya, Kazuhiko; Nihei, Tsutomu; Katafuchi, Tetsuro; Fujita, Hiroshi

    2016-03-01

    Important features in Parkinson's disease (PD) are degenerations and losses of dopamine neurons in corpus striatum. 123I-FP-CIT can visualize activities of the dopamine neurons. The activity radio of background to corpus striatum is used for diagnosis of PD and Dementia with Lewy Bodies (DLB). The specific activity can be observed in the corpus striatum on SPECT images, but the location and the shape of the corpus striatum on SPECT images only are often lost because of the low uptake. In contrast, MR images can visualize the locations of the corpus striatum. The purpose of this study was to realize a quantitative image analysis for the SPECT images by using image registration technique with brain MR images that can determine the region of corpus striatum. In this study, the image fusion technique was used to fuse SPECT and MR images by intervening CT image taken by SPECT/CT. The mutual information (MI) for image registration between CT and MR images was used for the registration. Six SPECT/CT and four MR scans of phantom materials are taken by changing the direction. As the results of the image registrations, 16 of 24 combinations were registered within 1.3mm. By applying the approach to 32 clinical SPECT/CT and MR cases, all of the cases were registered within 0.86mm. In conclusions, our registration method has a potential in superimposing MR images on SPECT images.

  19. Comparative assessment of fluorescent transgene methods for quantitative imaging in human cells.

    PubMed

    Mahen, Robert; Koch, Birgit; Wachsmuth, Malte; Politi, Antonio Z; Perez-Gonzalez, Alexis; Mergenthaler, Julia; Cai, Yin; Ellenberg, Jan

    2014-11-05

    Fluorescence tagging of proteins is a widely used tool to study protein function and dynamics in live cells. However, the extent to which different mammalian transgene methods faithfully report on the properties of endogenous proteins has not been studied comparatively. Here we use quantitative live-cell imaging and single-molecule spectroscopy to analyze how different transgene systems affect imaging of the functional properties of the mitotic kinase Aurora B. We show that the transgene method fundamentally influences level and variability of expression and can severely compromise the ability to report on endogenous binding and localization parameters, providing a guide for quantitative imaging studies in mammalian cells. © 2014 Mahen et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  20. Development of Diagnostic Biomarkers for Detecting Diabetic Retinopathy at Early Stages Using Quantitative Proteomics

    PubMed Central

    Min, Hophil; Kim, Sang Jin; Oh, Sohee; Kim, Kyunggon; Yu, Hyeong Gon; Park, Taesung; Kim, Youngsoo

    2016-01-01

    Diabetic retinopathy (DR) is a common microvascular complication caused by diabetes mellitus (DM) and is a leading cause of vision impairment and loss among adults. Here, we performed a comprehensive proteomic analysis to discover biomarkers for DR. First, to identify biomarker candidates that are specifically expressed in human vitreous, we performed data-mining on both previously published DR-related studies and our experimental data; 96 proteins were then selected. To confirm and validate the selected biomarker candidates, candidates were selected, confirmed, and validated using plasma from diabetic patients without DR (No DR) and diabetics with mild or moderate nonproliferative diabetic retinopathy (Mi or Mo NPDR) using semiquantitative multiple reaction monitoring (SQ-MRM) and stable-isotope dilution multiple reaction monitoring (SID-MRM). Additionally, we performed a multiplex assay using 15 biomarker candidates identified in the SID-MRM analysis, which resulted in merged AUC values of 0.99 (No DR versus Mo NPDR) and 0.93 (No DR versus Mi and Mo NPDR). Although further validation with a larger sample size is needed, the 4-protein marker panel (APO4, C7, CLU, and ITIH2) could represent a useful multibiomarker model for detecting the early stages of DR. PMID:26665153

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

  3. Refractive index variance of cells and tissues measured by quantitative phase imaging.

    PubMed

    Shan, Mingguang; Kandel, Mikhail E; Popescu, Gabriel

    2017-01-23

    The refractive index distribution of cells and tissues governs their interaction with light and can report on morphological modifications associated with disease. Through intensity-based measurements, refractive index information can be extracted only via scattering models that approximate light propagation. As a result, current knowledge of refractive index distributions across various tissues and cell types remains limited. Here we use quantitative phase imaging and the statistical dispersion relation (SDR) to extract information about the refractive index variance in a variety of specimens. Due to the phase-resolved measurement in three-dimensions, our approach yields refractive index results without prior knowledge about the tissue thickness. With the recent progress in quantitative phase imaging systems, we anticipate that using SDR will become routine in assessing tissue optical properties.

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

    PubMed

    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

  5. Rapid Verification of Candidate Serological Biomarkers Using Gel-based, Label-free Multiple Reaction Monitoring

    PubMed Central

    Tang, Hsin-Yao; Beer, Lynn A.; Barnhart, Kurt T.; Speicher, David W.

    2011-01-01

    Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves, quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1-D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μl serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers. PMID:21726088

  6. Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring.

    PubMed

    Tang, Hsin-Yao; Beer, Lynn A; Barnhart, Kurt T; Speicher, David W

    2011-09-02

    Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μL of serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers.

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

    PubMed

    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.

  8. Biochemical magnetic resonance imaging of knee articular cartilage: T1rho and T2 mapping as cartilage degeneration biomarkers.

    PubMed

    Le, Jenna; Peng, Qi; Sperling, Karen

    2016-11-01

    Osteoarthritis (OA) is a disease whose hallmark is the degeneration of articular cartilage. There is a worsening epidemic of OA in the United States today, with considerable economic costs. In order to develop more effective treatments for OA, noninvasive biomarkers that permit early diagnosis and treatment monitoring are necessary. T1rho and T2 mapping are two magnetic resonance imaging techniques that have shown great promise as noninvasive biomarkers of cartilage degeneration. Each of the two techniques is endowed with advantages and disadvantages: T1rho can discern earlier biochemical changes of OA than T2 mapping, while T2 mapping is more widely available and can be incorporated into existing imaging protocols in a more time-efficient manner than T1rho. Both techniques have been applied in numerous instances to study how cartilage is affected by OA risk factors, such as age and exercise. Additionally, both techniques have been repeatedly applied to the study of posttraumatic OA in patients with torn anterior cruciate ligaments. © 2016 New York Academy of Sciences.

  9. Retinal status analysis method based on feature extraction and quantitative grading in OCT images.

    PubMed

    Fu, Dongmei; Tong, Hejun; Zheng, Shuang; Luo, Ling; Gao, Fulin; Minar, Jiri

    2016-07-22

    Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). Firstly, the normal retinal reference model based on retinal boundaries was presented. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. The proposed method can obtain the parameters and the features that are associated with retinal morphology. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosis.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Quantitative contrast-enhanced ultrasound imaging: a review of sources of variability

    PubMed Central

    Tang, M.-X.; Mulvana, H.; Gauthier, T.; Lim, A. K. P.; Cosgrove, D. O.; Eckersley, R. J.; Stride, E.

    2011-01-01

    Ultrasound provides a valuable tool for medical diagnosis offering real-time imaging with excellent spatial resolution and low cost. The advent of microbubble contrast agents has provided the additional ability to obtain essential quantitative information relating to tissue vascularity, tissue perfusion and even endothelial wall function. This technique has shown great promise for diagnosis and monitoring in a wide range of clinical conditions such as cardiovascular diseases and cancer, with considerable potential benefits in terms of patient care. A key challenge of this technique, however, is the existence of significant variations in the imaging results, and the lack of understanding regarding their origin. The aim of this paper is to review the potential sources of variability in the quantification of tissue perfusion based on microbubble contrast-enhanced ultrasound images. These are divided into the following three categories: (i) factors relating to the scanner setting, which include transmission power, transmission focal depth, dynamic range, signal gain and transmission frequency, (ii) factors relating to the patient, which include body physical differences, physiological interaction of body with bubbles, propagation and attenuation through tissue, and tissue motion, and (iii) factors relating to the microbubbles, which include the type of bubbles and their stability, preparation and injection and dosage. It has been shown that the factors in all the three categories can significantly affect the imaging results and contribute to the variations observed. How these factors influence quantitative imaging is explained and possible methods for reducing such variations are discussed. PMID:22866229

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lee, Soyoung

    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 subpanelmore » 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

  13. Visualisation and quantitative analysis of the rodent malaria liver stage by real time imaging.

    PubMed

    Ploemen, Ivo H J; Prudêncio, Miguel; Douradinha, Bruno G; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J F; Hermsen, Cornelus C; Sauerwein, Robert W; Baptista, Fernanda G; Mota, Maria M; Waters, Andrew P; Que, Ivo; Lowik, Clemens W G M; Khan, Shahid M; Janse, Chris J; Franke-Fayard, Blandine M D

    2009-11-18

    The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luc(con), expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1-5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of

  14. Visualisation and Quantitative Analysis of the Rodent Malaria Liver Stage by Real Time Imaging

    PubMed Central

    Douradinha, Bruno G.; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J. F.; Hermsen, Cornelus C.; Sauerwein, Robert W.; Baptista, Fernanda G.; Mota, Maria M.; Waters, Andrew P.; Que, Ivo; Lowik, Clemens W. G. M.; Khan, Shahid M.; Janse, Chris J.; Franke-Fayard, Blandine M. D.

    2009-01-01

    The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luccon, expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1–5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of

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

    NASA Astrophysics Data System (ADS)

    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.

  16. Qualitative and quantitative effects of harmonic echocardiographic imaging on endocardial edge definition and side-lobe artifacts

    NASA Technical Reports Server (NTRS)

    Rubin, D. N.; Yazbek, N.; Garcia, M. J.; Stewart, W. J.; Thomas, J. D.

    2000-01-01

    Harmonic imaging is a new ultrasonographic technique that is designed to improve image quality by exploiting the spontaneous generation of higher frequencies as ultrasound propagates through tissue. We studied 51 difficult-to-image patients with blinded side-by-side cineloop evaluation of endocardial border definition by harmonic versus fundamental imaging. In addition, quantitative intensities from cavity versus wall were compared for harmonic versus fundamental imaging. Harmonic imaging improved left ventricular endocardial border delineation over fundamental imaging (superior: harmonic = 71.1%, fundamental = 18.7%; similar: 10.2%; P <.001). Quantitative analysis of 100 wall/cavity combinations demonstrated brighter wall segments and more strikingly darker cavities during harmonic imaging (cavity intensity on a 0 to 255 scale: fundamental = 15.6 +/- 8.6; harmonic = 6.0 +/- 5.3; P <.0001), which led to enhanced contrast between the wall and cavity (1.89 versus 1.19, P <.0001). Harmonic imaging reduces side-lobe artifacts, resulting in a darker cavity and brighter walls, thereby improving image contrast and endocardial delineation.

  17. Neuroimaging and Other Biomarkers for Alzheimer's Disease: The Changing Landscape of Early Detection

    PubMed Central

    Risacher, Shannon L.; Saykin, Andrew J.

    2014-01-01

    The goal of this review is to provide an overview of biomarkers for Alzheimer's disease (AD), with emphasis on neuroimaging and cerebrospinal fluid (CSF) biomarkers. We first review biomarker changes in patients with late-onset AD, including findings from studies using structural and functional magnetic resonance imaging (MRI), advanced MRI techniques (diffusion tensor imaging, magnetic resonance spectroscopy, perfusion), positron emission tomography with fluorodeoxyglucose, amyloid tracers, and other neurochemical tracers, and CSF protein levels. Next, we evaluate findings from these biomarkers in preclinical and prodromal stages of AD including mild cognitive impairment (MCI) and pre-MCI conditions conferring elevated risk. We then discuss related findings in patients with dominantly inherited AD. We conclude with a discussion of the current theoretical framework for the role of biomarkers in AD and emergent directions for AD biomarker research. PMID:23297785

  18. The role of biomarkers in the management of epithelial ovarian cancer.

    PubMed

    Yang, Wei-Lei; Lu, Zhen; Bast, Robert C

    2017-06-01

    Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.

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

    PubMed

    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

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

    NASA Astrophysics Data System (ADS)

    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.

  1. Quantitative volumetric Raman imaging of three dimensional cell cultures

    NASA Astrophysics Data System (ADS)

    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.

  2. Buccal Cell Cytokeratin 14 Correlates with Multiple Blood Biomarkers of Alzheimer's Disease Risk.

    PubMed

    Leifert, Wayne R; Nguyen, Tori; Rembach, Alan; Martins, Ralph; Rainey-Smith, Stephanie; Masters, Colin L; Ames, David; Rowe, Christopher C; Macaulay, S Lance; François, Maxime; Fenech, Michael F

    2015-01-01

    Mild cognitive impairment (MCI) may reflect early stages of neurodegenerative disorders such as Alzheimer's disease (AD). Our hypothesis was that cytokeratin 14 (CK14) expression could be used with blood-based biomarkers such as homocysteine, vitamin B12, and folate to identify individuals with MCI or AD from the Australian Imaging, Biomarkers and Lifestyle (AIBL) flagship study of aging. Buccal cells from 54 individuals were analyzed by a newly developed method that is rapid, automated, and quantitative for buccal cell CK14 expression levels. CK14 was negatively correlated with plasma Mg²⁺ and LDL, while positively correlated with vitamin B12, red cell hematocrit/volume, and basophils in the MCI group and positively correlated with insulin and vitamin B12 in the AD group. The combined biomarker panel (CK14 expression, plasma vitamin B12, and homocysteine) was significantly lower in the MCI (p = 0.003) and AD (p = 0.0001) groups compared with controls. Receiver-operating characteristic curves yielded area under the curve (AUC) values of 0.829 for the MCI (p = 0.002) group and 0.856 for the AD (p = 0.0003) group. These complex associations of multiple related parameters highlight the differences between the MCI and AD cohorts and possibly an underlying metabolic pathology associated with the development of early memory impairment. The changes in buccal cell CK14 expression observed in this pilot study supports previous results suggesting the peripheral biomarkers and metabolic changes are not restricted to brain pathology alone in MCI and AD and could prove useful as a potential biomarker in identifying individuals with an increased risk of developing MCI and eventually AD.

  3. A quantitative experimental phantom study on MRI image uniformity.

    PubMed

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

    2018-05-23

    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, Brain, and temporomandibular joint 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 National Electrical Manufacturers Association peak-deviation non-uniformity method. Results showed that temporomandibular joint coils elicited the least uniform image and brain coils outperformed head and neck coils when metallic materials were present. Additionally, when metallic materials were present, spin echo outperformed gradient echo 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.

  4. Laser scanning cytometry as a tool for biomarker validation

    NASA Astrophysics Data System (ADS)

    Mittag, Anja; Füldner, Christiane; Lehmann, Jörg; Tarnok, Attila

    2013-03-01

    Biomarkers are essential for diagnosis, prognosis, and therapy. As diverse is the range of diseases the broad is the range of biomarkers and the material used for analysis. Whereas body fluids can be relatively easily obtained and analyzed, the investigation of tissue is in most cases more complicated. The same applies for the screening and the evaluation of new biomarkers and the estimation of the binding of biomarkers found in animal models which need to be transferred into applications in humans. The latter in particular is difficult if it recognizes proteins or cells in tissue. A better way to find suitable cellular biomarkers for immunoscintigraphy or PET analyses may be therefore the in situ analysis of the cells in the respective tissue. In this study we present a method for biomarker validation using Laser Scanning Cytometry which allows the emulation of future in vivo analysis. The biomarker validation is exemplarily shown for rheumatoid arthritis (RA) on synovial membrane. Cryosections were scanned and analyzed by phantom contouring. Adequate statistical methods allowed the identification of suitable markers and combinations. The fluorescence analysis of the phantoms allowed the discrimination between synovial membrane of RA patients and non-RA control sections by using median fluorescence intensity and the "affected area". As intensity and area are relevant parameters of in vivo imaging (e.g. PET scan) too, the presented method allows emulation of a probable outcome of in vivo imaging, i.e. the binding of the target protein and hence, the validation of the potential of the respective biomarker.

  5. Searching for biomarkers of CDKL5 disorder: early-onset visual impairment in CDKL5 mutant mice

    PubMed Central

    Mazziotti, Raffaele; Lupori, Leonardo; Sagona, Giulia; Gennaro, Mariangela; Della Sala, Grazia; Putignano, Elena

    2017-01-01

    Abstract CDKL5 disorder is a neurodevelopmental disorder still without a cure. Murine models of CDKL5 disorder have been recently generated raising the possibility of preclinical testing of treatments. However, unbiased, quantitative biomarkers of high translational value to monitor brain function are still missing. Moreover, the analysis of treatment is hindered by the challenge of repeatedly and non-invasively testing neuronal function. We analyzed the development of visual responses in a mouse model of CDKL5 disorder to introduce visually evoked responses as a quantitative method to assess cortical circuit function. Cortical visual responses were assessed in CDKL5 null male mice, heterozygous females, and their respective control wild-type littermates by repeated transcranial optical imaging from P27 until P32. No difference between wild-type and mutant mice was present at P25-P26 whereas defective responses appeared from P27-P28 both in heterozygous and homozygous CDKL5 mutant mice. These results were confirmed by visually evoked potentials (VEPs) recorded from the visual cortex of a different cohort. The previously imaged mice were also analyzed at P60–80 using VEPs, revealing a persistent reduction of response amplitude, reduced visual acuity and defective contrast function. The level of adult impairment was significantly correlated with the reduction in visual responses observed during development. Support vector machine showed that multi-dimensional visual assessment can be used to automatically classify mutant and wt mice with high reliability. Thus, monitoring visual responses represents a promising biomarker for preclinical and clinical studies on CDKL5 disorder. PMID:28369421

  6. Quantitative proteomics in cardiovascular research: global and targeted strategies

    PubMed Central

    Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun

    2014-01-01

    Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501

  7. 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.

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Brain and cord myelin water imaging: a progressive multiple sclerosis biomarker

    PubMed Central

    Kolind, Shannon; Seddigh, Arshia; Combes, Anna; Russell-Schulz, Bretta; Tam, Roger; Yogendrakumar, Vignan; Deoni, Sean; Sibtain, Naomi A.; Traboulsee, Anthony; Williams, Steven C.R.; Barker, Gareth J.; Brex, Peter A.

    2015-01-01

    Objectives Conventional magnetic resonance imaging (MRI) is used to diagnose and monitor inflammatory disease in relapsing remitting (RR) multiple sclerosis (MS). In the less common primary progressive (PP) form of MS, in which focal inflammation is less evident, biomarkers are still needed to enable evaluation of novel therapies in clinical trials. Our objective was to characterize the association — across the brain and cervical spinal cord — between clinical disability measures in PPMS and two potential biomarkers (one for myelin, and one for atrophy, both resulting from the same imaging technique). Methods Multi-component driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) MRI of the brain and cervical spinal cord were obtained for 15 PPMS patients and 11 matched controls. Data were analysed to estimate the signal related to myelin water (VFM), as well as volume measurements. MS disability was assessed using the Multiple Sclerosis Functional Composite score, which includes measures of cognitive processing (Paced Auditory Serial Addition Test), manual dexterity (9-Hole Peg Test) and ambulatory function (Timed 25-Foot Walk); and the Expanded Disability Status Scale. Results Brain and spinal cord volumes were different in PPMS compared to controls, particularly ventricular (+ 46%, p = 0.0006) and cervical spinal cord volume (− 16%, p = 0.0001). Brain and spinal cord myelin (VFM) were also reduced in PPMS (brain: − 11%, p = 0.01; spine: − 19%, p = 0.000004). Cognitive processing correlated with brain ventricular volume (p = 0.009). Manual dexterity correlated with brain ventricular volume (p = 0.007), and both brain and spinal cord VFM (p = 0.01 and 0.06, respectively). Ambulation correlated with spinal cord volume (p = 0.04) and spinal cord VFM (p = 0.04). Interpretation In this study we demonstrated that mcDESPOT can be used to measure myelin and atrophy in the brain and spinal cord. Results correlate well with

  10. Quantitative Live-Cell Confocal Imaging of 3D Spheroids in a High-Throughput Format.

    PubMed

    Leary, Elizabeth; Rhee, Claire; Wilks, Benjamin T; Morgan, Jeffrey R

    2018-06-01

    Accurately predicting the human response to new compounds is critical to a wide variety of industries. Standard screening pipelines (including both in vitro and in vivo models) often lack predictive power. Three-dimensional (3D) culture systems of human cells, a more physiologically relevant platform, could provide a high-throughput, automated means to test the efficacy and/or toxicity of novel substances. However, the challenge of obtaining high-magnification, confocal z stacks of 3D spheroids and understanding their respective quantitative limitations must be overcome first. To address this challenge, we developed a method to form spheroids of reproducible size at precise spatial locations across a 96-well plate. Spheroids of variable radii were labeled with four different fluorescent dyes and imaged with a high-throughput confocal microscope. 3D renderings of the spheroid had a complex bowl-like appearance. We systematically analyzed these confocal z stacks to determine the depth of imaging and the effect of spheroid size and dyes on quantitation. Furthermore, we have shown that this loss of fluorescence can be addressed through the use of ratio imaging. Overall, understanding both the limitations of confocal imaging and the tools to correct for these limits is critical for developing accurate quantitative assays using 3D spheroids.

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

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed

    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.

  13. In Vivo Two-Photon Fluorescence Imaging of the Activity of the Inflammatory Biomarker LTA4H in a Mouse Pneumonia Model.

    PubMed

    Wang, Hui; Xue, Ke; Li, Ping; Yang, Yuyun; He, Zixu; Zhang, Wei; Zhang, Wen; Tang, Bo

    2018-05-15

    Severe atmospheric haze caused by industrial pollution has severely affected human health and led to the increasing incidence of cardiopulmonary diseases, including pneumonia. Conventional methods for diagnosis of pneumonia are complicated and tedious, and current clinical imaging techniques might cause organ injuries to some extent. Therefore, an accurate, fast, and intact imaging method must be developed to diagnose pneumonia in the early stages. In this study, we propose a new two-photon fluorescence probe, named as ASPC, for detection of the activity of the inflammatory biomarker LTA 4 H through specific recognition and cleavage of amides containing the unnatural amino acid l-AspBzl. The activity of LTA 4 H in the lung tissues of mice was rapidly and accurately monitored for the first time and could be an indicator for diagnosis of pneumonia. The severity of pneumonia in mice caused by haze particulate was determined through imaging the activity of LTA 4 H as biomarker and confirmed using a commercial ELISA kit of interleukin-1β. This work provides a promising method for clinical detection of pneumonia and for screening specific depressors of LTA 4 H as potential drug candidates.

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

    PubMed

    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.

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

    PubMed Central

    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

  16. Quantitative phase imaging of living cells with a swept laser source

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

  18. Hyperspectral and differential CARS microscopy for quantitative chemical imaging in human adipocytes

    PubMed Central

    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

  19. Reproducibility and Prognosis of Quantitative Features Extracted from CT Images12

    PubMed Central

    Balagurunathan, Yoganand; Gu, Yuhua; Wang, Hua; Kumar, Virendra; Grove, Olya; Hawkins, Sam; Kim, Jongphil; Goldgof, Dmitry B; Hall, Lawrence O; Gatenby, Robert A; Gillies, Robert J

    2014-01-01

    We study the reproducibility of quantitative imaging features that are used to describe tumor shape, size, and texture from computed tomography (CT) scans of non-small cell lung cancer (NSCLC). CT images are dependent on various scanning factors. We focus on characterizing image features that are reproducible in the presence of variations due to patient factors and segmentation methods. Thirty-two NSCLC nonenhanced lung CT scans were obtained from the Reference Image Database to Evaluate Response data set. The tumors were segmented using both manual (radiologist expert) and ensemble (software-automated) methods. A set of features (219 three-dimensional and 110 two-dimensional) was computed, and quantitative image features were statistically filtered to identify a subset of reproducible and nonredundant features. The variability in the repeated experiment was measured by the test-retest concordance correlation coefficient (CCCTreT). The natural range in the features, normalized to variance, was measured by the dynamic range (DR). In this study, there were 29 features across segmentation methods found with CCCTreT and DR ≥ 0.9 and R2Bet ≥ 0.95. These reproducible features were tested for predicting radiologist prognostic score; some texture features (run-length and Laws kernels) had an area under the curve of 0.9. The representative features were tested for their prognostic capabilities using an independent NSCLC data set (59 lung adenocarcinomas), where one of the texture features, run-length gray-level nonuniformity, was statistically significant in separating the samples into survival groups (P ≤ .046). PMID:24772210

  20. Real time quantitative imaging for semiconductor crystal growth, control and characterization

    NASA Technical Reports Server (NTRS)

    Wargo, Michael J.

    1991-01-01

    A quantitative real time image processing system has been developed which can be software-reconfigured for semiconductor processing and characterization tasks. In thermal imager mode, 2D temperature distributions of semiconductor melt surfaces (900-1600 C) can be obtained with temperature and spatial resolutions better than 0.5 C and 0.5 mm, respectively, as demonstrated by analysis of melt surface thermal distributions. Temporal and spatial image processing techniques and multitasking computational capabilities convert such thermal imaging into a multimode sensor for crystal growth control. A second configuration of the image processing engine in conjunction with bright and dark field transmission optics is used to nonintrusively determine the microdistribution of free charge carriers and submicron sized crystalline defects in semiconductors. The IR absorption characteristics of wafers are determined with 10-micron spatial resolution and, after calibration, are converted into charge carrier density.

  1. Local and Systemic Inflammatory Biomarkers of Diabetic Retinopathy: An Integrative Approach.

    PubMed

    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.

  2. Quantitatively in Situ Imaging Silver Nanowire Hollowing Kinetics

    DOE PAGES

    Yu, Le; Yan, Zhongying; Cai, Zhonghou; ...

    2016-09-28

    We report the in-situ investigation of the morphological evolution of silver nanowires to hollow silver oxide nanotubes using transmission x-ray microscopy (TXM). Complex silver diffusion kinetics and hollowing process via the Kirkendall effect have been captured in real time. Further quantitative x-ray absorption analysis reveals the difference between the longitudinal and radial diffusions. In conclusion, the diffusion coefficient of silver in its oxide nanoshell is, for the first time, calculated to be 1.2 × 10 -13 cm 2/s from the geometrical parameters extracted from the TXM images.

  3. Quantitative live-cell imaging of human immunodeficiency virus (HIV-1) assembly.

    PubMed

    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.

  4. Quantitative Live-Cell Imaging of Human Immunodeficiency Virus (HIV-1) Assembly

    PubMed Central

    Baumgärtel, Viola; Müller, Barbara; Lamb, Don C.

    2012-01-01

    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. PMID:22754649

  5. Combined fluorescence and reflectance spectroscopy for in vivo quantification of cancer biomarkers in low- and high-grade glioma surgery

    PubMed Central

    Valdés, Pablo A.; Kim, Anthony; Leblond, Frederic; Conde, Olga M.; Harris, Brent T.; Paulsen, Keith D.; Wilson, Brian C.; Roberts, David W.

    2011-01-01

    Biomarkers are indicators of biological processes and hold promise for the diagnosis and treatment of disease. Gliomas represent a heterogeneous group of brain tumors with marked intra- and inter-tumor variability. The extent of surgical resection is a significant factor influencing post-surgical recurrence and prognosis. Here, we used fluorescence and reflectance spectral signatures for in vivo quantification of multiple biomarkers during glioma surgery, with fluorescence contrast provided by exogenously-induced protoporphyrin IX (PpIX) following administration of 5-aminolevulinic acid. We performed light-transport modeling to quantify multiple biomarkers indicative of tumor biological processes, including the local concentration of PpIX and associated photoproducts, total hemoglobin concentration, oxygen saturation, and optical scattering parameters. We developed a diagnostic algorithm for intra-operative tissue delineation that accounts for the combined tumor-specific predictive capabilities of these quantitative biomarkers. Tumor tissue delineation achieved accuracies of up to 94% (specificity = 94%, sensitivity = 94%) across a range of glioma histologies beyond current state-of-the-art optical approaches, including state-of-the-art fluorescence image guidance. This multiple biomarker strategy opens the door to optical methods for surgical guidance that use quantification of well-established neoplastic processes. Future work would seek to validate the predictive power of this proof-of-concept study in a separate larger cohort of patients. PMID:22112112

  6. Atrophied Brain Lesion Volume: A New Imaging Biomarker in Multiple Sclerosis.

    PubMed

    Dwyer, Michael G; Bergsland, Niels; Ramasamy, Deepa P; Jakimovski, Dejan; Weinstock-Guttman, Bianca; Zivadinov, Robert

    2018-06-01

    Lesion accrual in multiple sclerosis (MS) is an important and clinically relevant measure, used extensively as an imaging trial endpoint. However, lesions may also shrink or disappear entirely due to atrophy. Although generally ignored or treated as a nuisance, this phenomenon may actually be an important stand-alone imaging biomarker. Therefore, we investigated the rate of brain lesion loss due to atrophy (atrophied lesion volume) in MS subtypes compared to baseline lesion volume and to new and enlarging lesion volumes, and evaluated the independent predictive value of this phenomenon for clinical disability. A total of 192 patients (18 clinically isolated syndrome, 126 relapsing-remitting MS, and 48 progressive) received 3T magnetic resonance imaging at baseline and 5 years. Lesions were quantified at baseline, and new/enlarging lesion volumes were calculated over the study interval. Atrophied lesion volume was calculated by combining baseline lesion masks with follow-up SIENAX-derived cerebrospinal fluid partial volume maps. Measures were compared between disease subgroups, and correlations with disability change (Expanded Disability Status Scale [EDSS]) were evaluated. Hierarchical regression was employed to determine the unique additive value of atrophied lesion volume. Atrophied lesion volume was different between MS subtypes (P = .02), and exceeded new lesion volume accumulation in progressive MS (298.1 vs. 75.5 mm 3 ). Atrophied lesion volume was the only significant correlate of EDSS change (r = .192 relapsing, r = .317 progressive, P < .05), and explained significant additional variance when controlling for brain atrophy and new/enlarging lesion volume (R 2 .092 vs. .045, P = .003). Atrophied lesion volume is a unique and clinically relevant imaging marker in MS, with particular promise in progressive MS. Copyright © 2018 by the American Society of Neuroimaging.

  7. Ptychography: use of quantitative phase information for high-contrast label free time-lapse imaging of living cells

    NASA Astrophysics Data System (ADS)

    Suman, Rakesh; O'Toole, Peter

    2014-03-01

    Here we report a novel label free, high contrast and quantitative method for imaging live cells. The technique reconstructs an image from overlapping diffraction patterns using a ptychographical algorithm. The algorithm utilises both amplitude and phase data from the sample to report on quantitative changes related to the refractive index (RI) and thickness of the specimen. We report the ability of this technique to generate high contrast images, to visualise neurite elongation in neuronal cells, and to provide measure of cell proliferation.

  8. Computer system for definition of the quantitative geometry of musculature from CT images.

    PubMed

    Daniel, Matej; Iglic, Ales; Kralj-Iglic, Veronika; Konvicková, Svatava

    2005-02-01

    The computer system for quantitative determination of musculoskeletal geometry from computer tomography (CT) images has been developed. The computer system processes series of CT images to obtain three-dimensional (3D) model of bony structures where the effective muscle fibres can be interactively defined. Presented computer system has flexible modular structure and is suitable also for educational purposes.

  9. Quantitative chemical imaging with background-free multiplex coherent anti-Stokes Raman scattering by dual-soliton Stokes pulses

    PubMed Central

    Chen, Kun; Wu, Tao; Wei, Haoyun; Zhou, Tian; Li, Yan

    2016-01-01

    Coherent anti-Stokes Raman microscopy (CARS) is a quantitative, chemically specific, and label-free optical imaging technique for studying inhomogeneous systems. However, the complicating influence of the nonresonant response on the CARS signal severely limits its sensitivity and specificity and especially limits the extent to which CARS microscopy has been used as a fully quantitative imaging technique. On the basis of spectral focusing mechanism, we establish a dual-soliton Stokes based CARS microspectroscopy and microscopy scheme capable of quantifying the spatial information of densities and chemical composition within inhomogeneous samples, using a single fiber laser. Dual-soliton Stokes scheme not only removes the nonresonant background but also allows robust acquisition of multiple characteristic vibrational frequencies. This all-fiber based laser source can cover the entire fingerprint (800-2200 cm−1) region with a spectral resolution of 15 cm−1. We demonstrate that quantitative degree determination of lipid-chain unsaturation in the fatty acids mixture can be achieved by the characterization of C = C stretching and CH2 deformation vibrations. For microscopy purposes, we show that the spatially inhomogeneous distribution of lipid droplets can be further quantitatively visualized using this quantified degree of lipid unsaturation in the acyl chain for contrast in the hyperspectral CARS images. The combination of compact excitation source and background-free capability to facilitate extraction of quantitative composition information with multiplex spectral peaks will enable wider applications of quantitative chemical imaging in studying biological and material systems. PMID:27867704

  10. An approach for quantitative image quality analysis for CT

    NASA Astrophysics Data System (ADS)

    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.

  11. A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods

    PubMed Central

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

    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

  12. A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods.

    PubMed

    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

  13. CT Perfusion Imaging as an Early Biomarker of Differential Response to Stereotactic Radiosurgery in C6 Rat Gliomas

    PubMed Central

    Yeung, Timothy Pok Chi; Kurdi, Maher; Wang, Yong; Al-Khazraji, Baraa; Morrison, Laura; Hoffman, Lisa; Jackson, Dwayne; Crukley, Cathie; Lee, Ting-Yim; Bauman, Glenn; Yartsev, Slav

    2014-01-01

    Background The therapeutic efficacy of stereotactic radiosurgery for glioblastoma is not well understood, and there needs to be an effective biomarker to identify patients who might benefit from this treatment. This study investigated the efficacy of computed tomography (CT) perfusion imaging as an early imaging biomarker of response to stereotactic radiosurgery in a malignant rat glioma model. Methods Rats with orthotopic C6 glioma tumors received either mock irradiation (controls, N = 8) or stereotactic radiosurgery (N = 25, 12 Gy in one fraction) delivered by Helical Tomotherapy. Twelve irradiated animals were sacrificed four days after stereotactic radiosurgery to assess acute CT perfusion and histological changes, and 13 irradiated animals were used to study survival. Irradiated animals with survival >15 days were designated as responders while those with survival ≤15 days were non-responders. Longitudinal CT perfusion imaging was performed at baseline and regularly for eight weeks post-baseline. Results Early signs of radiation-induced injury were observed on histology. There was an overall survival benefit following stereotactic radiosurgery when compared to the controls (log-rank P<0.04). Responders to stereotactic radiosurgery showed lower relative blood volume (rBV), and permeability-surface area (PS) product on day 7 post-stereotactic radiosurgery when compared to controls and non-responders (P<0.05). rBV and PS on day 7 showed correlations with overall survival (P<0.05), and were predictive of survival with 92% accuracy. Conclusions Response to stereotactic radiosurgery was heterogeneous, and early selection of responders and non-responders was possible using CT perfusion imaging. Validation of CT perfusion indices for response assessment is necessary before clinical implementation. PMID:25329655

  14. A unified material decomposition framework for quantitative dual- and triple-energy CT imaging.

    PubMed

    Zhao, Wei; Vernekohl, Don; Han, Fei; Han, Bin; Peng, Hao; Yang, Yong; Xing, Lei; Min, James K

    2018-04-21

    Many clinical applications depend critically on the accurate differentiation and classification of different types of materials in patient anatomy. This work introduces a unified framework for accurate nonlinear material decomposition and applies it, for the first time, in the concept of triple-energy CT (TECT) for enhanced material differentiation and classification as well as dual-energy CT (DECT). We express polychromatic projection into a linear combination of line integrals of material-selective images. The material decomposition is then turned into a problem of minimizing the least-squares difference between measured and estimated CT projections. The optimization problem is solved iteratively by updating the line integrals. The proposed technique is evaluated by using several numerical phantom measurements under different scanning protocols. The triple-energy data acquisition is implemented at the scales of micro-CT and clinical CT imaging with commercial "TwinBeam" dual-source DECT configuration and a fast kV switching DECT configuration. Material decomposition and quantitative comparison with a photon counting detector and with the presence of a bow-tie filter are also performed. The proposed method provides quantitative material- and energy-selective images examining realistic configurations for both DECT and TECT measurements. Compared to the polychromatic kV CT images, virtual monochromatic images show superior image quality. For the mouse phantom, quantitative measurements show that the differences between gadodiamide and iodine concentrations obtained using TECT and idealized photon counting CT (PCCT) are smaller than 8 and 1 mg/mL, respectively. TECT outperforms DECT for multicontrast CT imaging and is robust with respect to spectrum estimation. For the thorax phantom, the differences between the concentrations of the contrast map and the corresponding true reference values are smaller than 7 mg/mL for all of the realistic configurations. A unified

  15. Measurements of morphology and refractive indexes on human downy hairs using three-dimensional quantitative phase imaging.

    PubMed

    Lee, SangYun; Kim, Kyoohyun; Lee, Yuhyun; Park, Sungjin; Shin, Heejae; Yang, Jongwon; Ko, Kwanhong; Park, HyunJoo; Park, YongKeun

    2015-01-01

    We present optical measurements of morphology and refractive indexes (RIs) of human downy arm hairs using three-dimensional (3-D) quantitative phase imaging techniques. 3-D RI tomograms and high-resolution two-dimensional synthetic aperture images of individual downy arm hairs were measured using a Mach–Zehnder laser interferometric microscopy equipped with a two-axis galvanometer mirror. From the measured quantitative images, the RIs and morphological parameters of downy hairs were noninvasively quantified including the mean RI, volume, cylinder, and effective radius of individual hairs. In addition, the effects of hydrogen peroxide on individual downy hairs were investigated.

  16. Clinical applications of advanced magnetic resonance imaging techniques for arthritis evaluation

    PubMed Central

    Martín Noguerol, Teodoro; Luna, Antonio; Gómez Cabrera, Marta; Riofrio, Alexie D

    2017-01-01

    Magnetic resonance imaging (MRI) has allowed a comprehensive evaluation of articular disease, increasing the detection of early cartilage involvement, bone erosions, and edema in soft tissue and bone marrow compared to other imaging techniques. In the era of functional imaging, new advanced MRI sequences are being successfully applied for articular evaluation in cases of inflammatory, infectious, and degenerative arthropathies. Diffusion weighted imaging, new fat suppression techniques such as DIXON, dynamic contrast enhanced-MRI, and specific T2 mapping cartilage sequences allow a better understanding of the physiopathological processes that underlie these different arthropathies. They provide valuable quantitative information that aids in their differentiation and can be used as potential biomarkers of articular disease course and treatment response. PMID:28979849

  17. Promote quantitative ischemia imaging via myocardial perfusion CT iterative reconstruction with tensor total generalized variation regularization

    NASA Astrophysics Data System (ADS)

    Gu, Chengwei; Zeng, Dong; Lin, Jiahui; Li, Sui; He, Ji; Zhang, Hao; Bian, Zhaoying; Niu, Shanzhou; Zhang, Zhang; Huang, Jing; Chen, Bo; Zhao, Dazhe; Chen, Wufan; Ma, Jianhua

    2018-06-01

    Myocardial perfusion computed tomography (MPCT) imaging is commonly used to detect myocardial ischemia quantitatively. A limitation in MPCT is that an additional radiation dose is required compared to unenhanced CT due to its repeated dynamic data acquisition. Meanwhile, noise and streak artifacts in low-dose cases are the main factors that degrade the accuracy of quantifying myocardial ischemia and hamper the diagnostic utility of the filtered backprojection reconstructed MPCT images. Moreover, it is noted that the MPCT images are composed of a series of 2/3D images, which can be naturally regarded as a 3/4-order tensor, and the MPCT images are globally correlated along time and are sparse across space. To obtain higher fidelity ischemia from low-dose MPCT acquisitions quantitatively, we propose a robust statistical iterative MPCT image reconstruction algorithm by incorporating tensor total generalized variation (TTGV) regularization into a penalized weighted least-squares framework. Specifically, the TTGV regularization fuses the spatial correlation of the myocardial structure and the temporal continuation of the contrast agent intake during the perfusion. Then, an efficient iterative strategy is developed for the objective function optimization. Comprehensive evaluations have been conducted on a digital XCAT phantom and a preclinical porcine dataset regarding the accuracy of the reconstructed MPCT images, the quantitative differentiation of ischemia and the algorithm’s robustness and efficiency.

  18. Biomarkers in Prodromal Parkinson Disease: a Qualitative Review.

    PubMed

    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).

  19. Relative quantification of biomarkers using mixed-isotope labeling coupled with MS

    PubMed Central

    Chapman, Heidi M; Schutt, Katherine L; Dieter, Emily M; Lamos, Shane M

    2013-01-01

    The identification and quantification of important biomarkers is a critical first step in the elucidation of biological systems. Biomarkers take many forms as cellular responses to stimuli and can be manifested during transcription, translation, and/or metabolic processing. Increasingly, researchers have relied upon mixed-isotope labeling (MIL) coupled with MS to perform relative quantification of biomarkers between two or more biological samples. MIL effectively tags biomarkers of interest for ease of identification and quantification within the mass spectrometer by using isotopic labels that introduce a heavy and light form of the tag. In addition to MIL coupled with MS, a number of other approaches have been used to quantify biomarkers including protein gel staining, enzymatic labeling, metabolic labeling, and several label-free approaches that generate quantitative data from the MS signal response. This review focuses on MIL techniques coupled with MS for the quantification of protein and small-molecule biomarkers. PMID:23157360

  20. Effects of finite spatial resolution on quantitative CBF images from dynamic PET

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Phelps, M.E.; Huang, S.C.; Mahoney, D.K.

    1985-05-01

    The finite spatial resolution of PET causes the time-activity responses on pixels around the boundaries between gray and white matter regions to contain kinetic components from tissues of different CBF's. CBF values estimated from kinetics of such mixtures are underestimated because of the nonlinear relationship between the time-activity response and the estimated CBF. Computer simulation is used to investigate these effects on phantoms of circular structures and realistic brain slice in terms of object size and quantitative CBF values. The CBF image calculated is compared to the case of having resolution loss alone. Results show that the size of amore » high flow region in the CBF image is decreased while that of a low flow region is increased. For brain phantoms, the qualitative appearance of CBF images is not seriously affected, but the estimated CBF's are underestimated by 11 to 16 percent in local gray matter regions (of size 1 cm/sup 2/) with about 14 percent reduction in global CBF over the whole slice. It is concluded that the combined effect of finite spatial resolution and the nonlinearity in estimating CBF from dynamic PET is quite significant and must be considered in processing and interpreting quantitative CBF images.« less