The work proposed under this continuation proposal is designed to support the development, optimization and implementation of quantitative MR imaging markers for assessing response to treatment for primary breast cancer. In the initial project period, we developed a breast MRI method that employs a three-time point analysis of contrast kinetics, the signal enhancement ratio (SER), to assess tumor vasculature, while providing high spatial resolution to assess lesion morphology. We evaluated the effectiveness of the SER method for breast cancer staging and also applied the technique to assess the response of primary breast cancers to pre-operative, or neoadjuvant chemotherapy. Preliminary results from the neoadjuvant MRI studies suggested that the accuracy of MRI for staging tumor extent and measuring size changes in response to treatment resulted in better prediction of recurrence-free survival. Based upon these results, the multi-center ACRIN trial 6657, evaluating CE-MRI for assessment of patients undergoing neoadjuvant chemotherapy for locally-advanced breast cancer, opened in May 2002 and is nearing its accrual target of 244 subjects. ACRIN 6657 is an observational trial evaluating MRI's ability to identify patient subgroups with statistically-significant differences in survival outcome, that could not be identified on the basis of standard clinical and radiographic assessment alone. If this can be demonstrated, it may be possible that subsequent neoadjuvant trial designs can introduce patient triaging based upon MRI measurements. The goal of this continuation proposal is to further improve and evaluate the effectiveness of quantitative MRI measures for assessing primary breast tumors, to support their use as in-vivo predictive markers that can be used to guide treatment. The three aims address the data acquisition protocol (Aim 1), the optimization of individual predictor variables (Aim 2), and the development of predictive models to optimize linear combinations of imaging markers (Aim 3). These developments are proposed in concert with the separate development of a multi-center clinical trial protocol in which these techniques will be tested for their ability to measure early tumor changes in response to treatment and predict overall treatment response.
Under Aim 1, the image acquisition protocol will be advanced to use current state-of-the art technology to maximize the combined morphologic/functional characterization of breast tumors. Three additional functional measurements, tumor ADC measured by diffusion-weighted MRI, tumor choline concentrations [tCho] measured by 1H single voxel MR spectroscopy, and tumor perfusion measured by arterial spin labeling (ASL) MRI, will be added to the breast MR exam.
Aim 2 will use existing data from the UCSF pilot study and ACRIN 6657 to optimize individual predictor variables by investigating the effect of threshold settings on predictive performance.
Aim 3 will apply new statistical approaches for optimally combining markers in a predictive model. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA069587-11
Application #
7414530
Study Section
Special Emphasis Panel (ZRG1-SBIB-S (02))
Program Officer
Zhang, Huiming
Project Start
1997-01-15
Project End
2011-02-28
Budget Start
2008-04-08
Budget End
2009-02-28
Support Year
11
Fiscal Year
2008
Total Cost
$434,608
Indirect Cost
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
Li, Wen; Arasu, Vignesh; Newitt, David C et al. (2016) Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL. Tomography 2:378-387
Hylton, Nola M; Gatsonis, Constantine A; Rosen, Mark A et al. (2016) Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence-free Survival-Results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL. Radiology 279:44-55
McLaughlin, Rebekah L; Newitt, David C; Wilmes, Lisa J et al. (2014) High resolution in vivo characterization of apparent diffusion coefficient at the tumor-stromal boundary of breast carcinomas: a pilot study to assess treatment response using proximity-dependent diffusion-weighted imaging. J Magn Reson Imaging 39:1308-13
Jafri, Nazia F; Newitt, David C; Kornak, John et al. (2014) Optimized breast MRI functional tumor volume as a biomarker of recurrence-free survival following neoadjuvant chemotherapy. J Magn Reson Imaging 40:476-82
Wilmes, Lisa J; McLaughlin, Rebekah L; Newitt, David C et al. (2013) High-resolution diffusion-weighted imaging for monitoring breast cancer treatment response. Acad Radiol 20:581-9
Lehman, Constance D; Blume, Jeffrey D; DeMartini, Wendy B et al. (2013) Accuracy and interpretation time of computer-aided detection among novice and experienced breast MRI readers. AJR Am J Roentgenol 200:W683-9
Jones, Ella F; Sinha, Sumedha P; Newitt, David C et al. (2013) MRI enhancement in stromal tissue surrounding breast tumors: association with recurrence free survival following neoadjuvant chemotherapy. PLoS One 8:e61969
Singer, Lisa; Wilmes, Lisa J; Saritas, Emine U et al. (2012) High-resolution diffusion-weighted magnetic resonance imaging in patients with locally advanced breast cancer. Acad Radiol 19:526-34
Partridge, Savannah C; Singer, Lisa; Sun, Ryan et al. (2011) Diffusion-weighted MRI: influence of intravoxel fat signal and breast density on breast tumor conspicuity and apparent diffusion coefficient measurements. Magn Reson Imaging 29:1215-21
McLaughlin, Rebekah; Hylton, Nola (2011) MRI in breast cancer therapy monitoring. NMR Biomed 24:712-20

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