The goal of this project is the improved integration of MRI-based quantitative imaging (Ql) for evaluating response to treatment in clinical trials of women receiving pre-operative (neoadjuvant) treatment for breast cancer. We will build on the existing ISPY clinical trials program, which encompasses a series of breast cancer trials focused in the neoadjuvant setting. ISPY-1 started in 2002 with correlative studies of imaging and tissue biomarkers in association with standard of care chemotherapy and has evolved toward individualized treatment with targeted therapies. ISPY-2, which opened in March 2010, follows an adaptive phase II design to evaluate multiple targeted therapies for breast cancer. Randomization to the multiple treatment arms adapts based in part on the MRI measurement of tumor volume as a result of preliminary findings from ACRIN 6657, the imaging component of ISPY-1. The proposed Quantitative Imaging Network (QIN) project will focus in three areas critical to maximizing the effectiveness and reliability of Ql for evaluating drug treatment strategies for breast cancer. Under the first aim, we will develop a quality assurance (QA) process that will be used to implement more objective criteria for initial site qualification, ongoing assessment of image quality and exam acceptance for quantitative analysis. Under the second aim, we will conduct a repeatability study in a patient cohort similar to ISPY-2 to obtain important information about the variability of quantitative measurements made from breast MRI that can be used to improve the interpretation of response results. Under the third aim, we will test several new imaging metrics for predicting treatment response in both ISPY and a phase II trial of neoadjuvant letrozole for treatment of post- menopausal ER+ DCIS. This project will be conducted in partnership with the American College of Radiology Imaging Network (ACRIN) Imaging Core and industrial partner Sentinelle Medical, Inc. In order to maximize the efficiency with which products of this QIN project can be translated into clinical practice, both the ACRIN TRIAD informatics system and the Sentinelle Aegis software system will communicate with the ISPY-2 TRANSCEND informatics system linking imaging with the caBIG supported ISPY-2 trial database.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA151235-03
Application #
8537122
Study Section
Special Emphasis Panel (ZCA1-SRLB-9 (J1))
Program Officer
Nordstrom, Robert J
Project Start
2011-09-26
Project End
2016-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
3
Fiscal Year
2013
Total Cost
$516,330
Indirect Cost
$134,701
Name
University of California San Francisco
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
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Hylton, Nola M (2018) Residual Disease after Neoadjuvant Therapy for Breast Cancer: Can MRI Help? Radiology 289:335-336
Olshen, Adam; Wolf, Denise; Jones, Ella F et al. (2018) Features of MRI stromal enhancement with neoadjuvant chemotherapy: a subgroup analysis of the ACRIN 6657/I-SPY TRIAL. J Med Imaging (Bellingham) 5:011014
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Bane, Octavia; Hectors, Stefanie J; Wagner, Mathilde et al. (2018) Accuracy, repeatability, and interplatform reproducibility of T1 quantification methods used for DCE-MRI: Results from a multicenter phantom study. Magn Reson Med 79:2564-2575
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
Jones, Ella F; Ray, Kimberly M; Li, Wen et al. (2017) Dedicated Breast Positron Emission Tomography for the Evaluation of Early Response to Neoadjuvant Chemotherapy in Breast Cancer. Clin Breast Cancer 17:e155-e159
Yankeelov, Thomas E; Mankoff, David A; Schwartz, Lawrence H et al. (2016) Quantitative Imaging in Cancer Clinical Trials. Clin Cancer Res 22:284-90
Malyarenko, Dariya I; Newitt, David; J Wilmes, Lisa et al. (2016) Demonstration of nonlinearity bias in the measurement of the apparent diffusion coefficient in multicenter trials. Magn Reson Med 75:1312-23
Malyarenko, Dariya I; Wilmes, Lisa J; Arlinghaus, Lori R et al. (2016) QIN DAWG Validation of Gradient Nonlinearity Bias Correction Workflow for Quantitative Diffusion-Weighted Imaging in Multicenter Trials. Tomography 2:396-405

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