The goal of this proposal is to improve cancer clinical trials by enhancing the effectiveness of quantitative PET/CT imaging of tumor response. This has three distinct and linked components;(1) measuring and reducing the bias and variance of multi-center quantitative PET/CT imaging measurements, (2) devising optimal PET image analysis methods appropriate for quantitative PET/CT imaging in clinical trials, and (3) developing and testing guidelines for incorporating quantitative PET/CT imaging as a biomarker and measure of response in cancer clinical trial design. Underlying themes include optimizing the clinical and biologic data that can be gleaned from imaging in the setting of cancer therapy clinical trials, matching the design of the imaging components to the phase and complexity of the cancer clinical therapy trial, and matching the imaging approach to the type of tumor and the therapeutic agent. The mechanism used in the proposal is the development and testing of methods in tandem with existing clinical cancer trials that include PET imaging. This includes imaging studies performed locally at the University of Washington, in small multi-center trials as part of a regional network directed by our cancer center, and as a participant in national multi-center trials. The focus is on early drug trials (Phase I and II studies) and imaging biomarker studies;however, the methods investigated and tools developed will be equally applicable to larger (Phase III) trials and imaging as a surrogate endpoint. The combined results from all three aims will enable clinical investigators, cooperative cancer trial groups, and pharma, to optimize the use of PET imaging in cancer clinical trials and to include considerations for quantitative PET imaging markers in choosing a study design and sample size.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA148131-04
Application #
8462925
Study Section
Special Emphasis Panel (ZCA1-SRLB-9 (J1))
Program Officer
Nordstrom, Robert J
Project Start
2010-04-15
Project End
2015-03-31
Budget Start
2013-05-28
Budget End
2014-03-31
Support Year
4
Fiscal Year
2013
Total Cost
$532,690
Indirect Cost
$150,264
Name
University of Washington
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
O'Sullivan, Finbarr; O'Sullivan, Janet N; Huang, Jian et al. (2018) Assessment of a statistical AIF extraction method for dynamic PET studies with 15O water and 18F fluorodeoxyglucose in locally advanced breast cancer patients. J Med Imaging (Bellingham) 5:011010
Zuki?, Dženan; Byrd, Darrin W; Kinahan, Paul E et al. (2018) Calibration Software for Quantitative PET/CT Imaging Using Pocket Phantoms. Tomography 4:148-158
Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura et al. (2018) Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies. J Med Imaging (Bellingham) 5:011006
Byrd, Darrin; Christopfel, Rebecca; Arabasz, Grae et al. (2018) Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network. J Med Imaging (Bellingham) 5:011016
Newitt, David C; Malyarenko, Dariya; Chenevert, Thomas L et al. (2018) Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network. J Med Imaging (Bellingham) 5:011003
Linden, Hannah M; Peterson, Lanell M; Fowler, Amy M (2018) Clinical Potential of Estrogen and Progesterone Receptor Imaging. PET Clin 13:415-422
Kinahan, Paul E; Byrd, Darrin W; Helba, Brian et al. (2018) Simultaneous Estimation of Bias and Resolution in PET Images With a Long-Lived ""Pocket"" Phantom System. Tomography 4:33-41
Kurland, Brenda F; Peterson, Lanell M; Lee, Jean H et al. (2017) Estrogen Receptor Binding (18F-FES PET) and Glycolytic Activity (18F-FDG PET) Predict Progression-Free Survival on Endocrine Therapy in Patients with ER+ Breast Cancer. Clin Cancer Res 23:407-415
Wangerin, Kristen A; Muzi, Mark; Peterson, Lanell M et al. (2017) A virtual clinical trial comparing static versus dynamic PET imaging in measuring response to breast cancer therapy. Phys Med Biol 62:3639-3655
Beichel, Reinhard R; Smith, Brian J; Bauer, Christian et al. (2017) Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data. Med Phys 44:479-496

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