? Effective molecular imaging research depends on successful kinetic modeling of dynamic image data. The need for optimal experimental design and data analysis tools will grow as molecular imaging research expands. These techniques will be used in oncology (and other diseases) for diagnosis, staging, and monitoring response to therapy. Our overall objective is to fulfill currently unmet needs of quantitative analysis of image data.
Our aims are to: 1) develop, 2) disseminate, and 3) support novel methods and new tools. The proposed methods and software will facilitate rapid, reliable quantification for in vivo characterization of molecular and cellular events. Integration of kinetic, molecular, and anatomic information will be key. ? ? We have already developed and implemented the core functionality for new methods in quantitative dynamic image analysis which we have named COMKAT: Compartment Model Kinetic Analysis Tool. COMKAT currently includes construction, simulation, and fitting user-specified models to kinetic data. We will expand its functionality and features by including co-registration, fusion and visualization of multi-modality data; region of interest specification and time-activity curve creation; generation of parametric images; optimal experiment design; and a library of examples. Moreover, we will develop new analysis and experiment design methods and assess their performance with simulations based on the developed software. Findings will be published to guide others in selecting analysis methods. In total, these developments serve as a necessary platform for future research and investigation. ? ? To maximize the value of this work, we will disseminate and support the software so that the cellular, molecular and general imaging communities may benefit from it. Specifically, we will expand the current web site from which COMKAT is distributed in source-code form. We will refine and expand the documentation; implement web-based version control for maintaining source code, documentation and web pages; implement web-based bug reporting and tracking; and create an online discussion forum. We will instruct people in use of the software; create an interactive, on-line course; develop new functionality in response to user requests; assist advanced modelers in expanding the software; and assist users in pre-study design of experiments and post-study analysis of data. We will establish an advisory panel composed of individuals experienced in quantitative analysis of images to guide and prioritize our development, dissemination and support processes. Many of these people will be associated with institutions that have NIH-supported In Vivo Cellular and Molecular Imaging Centers (ICMICs) or pre-ICMICs. NIH support to create quality analytical tools demanded by research is necessary since commercial product development is not economically feasible since the market for such software is small and specialized. ? ?

National Institute of Health (NIH)
National Cancer Institute (NCI)
Exploratory/Developmental Grants Phase II (R33)
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Special Emphasis Panel (ZCA1-SRRB-9 (J1))
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Croft, Barbara
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Case Western Reserve University
Schools of Medicine
United States
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Fang, Yu-Hua Dean; Asthana, Pravesh; Salinas, Cristian et al. (2010) Integrated software environment based on COMKAT for analyzing tracer pharmacokinetics with molecular imaging. J Nucl Med 51:77-84
Fang, Yu-Hua Dean; Muzic Jr, Raymond F (2008) Spillover and partial-volume correction for image-derived input functions for small-animal 18F-FDG PET studies. J Nucl Med 49:606-14
Salinas, Cristian A; Muzic Jr, Raymond F; Saidel, Gerald M (2007) Validity of model approximations for receptor-ligand kinetics in nuclear medicine. Med Phys 34:1693-703
Salinas, Cristian; Muzic Jr, Raymond F; Ernsberger, Paul et al. (2007) Robust experiment design for estimating myocardial beta adrenergic receptor concentration using PET. Med Phys 34:151-65
Muzic Jr, Raymond F; Christian, Bradley T (2006) Evaluation of objective functions for estimation of kinetic parameters. Med Phys 33:342-53