We propose to develop integrated high field (3T) magnetic resonance imaging (MRI) and positron emission tomography (PET) methods for assessing the effects of molecularly targeted anti-angiogenesis and cytoxic treatments in breast cancer clinical trials. Our goal is to provide the breast cancer community with practical data acquisition and analysis protocols that facilitate the translation of advanced imaging technologies into patient management and clinical trials. Dynamic contrast enhanced MRI (DCE-MRI) and diffusion weighted MRI (DW-MRI) can report on vascular status, tissue volume fractions, and cellularity, while fluorodeoxythymidine PET (FLT-PET) can report on cell proliferation. We propose to combine these MRI and PET data to provide anatomical, physiological, and molecular assessments of the response of breast tumors to novel anti-angiogenic and cytoxic treatments in clinical trials. To accomplish these goals we will pursue the following specific aims: 1. We will develop high field breast MRI protocols that measure tissue cellularity and vascularity. We will then develop methods for the rigorous registration of these MRI measures with quantitative PET characterization of cell proliferation. We will develop the algorithms and software architecture necessary for synthesizing the imaging data with (traditional) clinical data to assisting in clinical decision making. 2. In an ongoing Phase II study we will employ DCE-MRI, DW-MRI, and FLT-PET to assess the degree of tumor response after one and two cycles of Carboplatin and nab-Paclitaxel with or without Vorinostat in HER2-negative primary operable breast cancer. 3. In our planned Phase II study we will employ DCE-MRI, DW-MRI, and FLT-PET to assess the degree of tumor response after one and two cycles of neoadjuvant cisplatin, paclitaxel and the TOI inhibitor everolimus in patients with triple negative breast tumors. As the anti-cancer agents employed in these clinical trials are implicated in apoptosis and/or inhibition of cellular proliferation and/or inhibition of angiogenesis, we hypothesize that changes in metrics of cellular proliferation and vascularity, when merged with traditional clinical biomarkers, will provide significantly more accurate predictions on patient response than traditional methods of tumor response including RECIST.
We propose to develop integrated magnetic resonance imaging (MRI) and positron emission tomography (PET) methods for assessing the effects of molecularly targeted treatments in breast cancer clinical trials. We hypothesize that the synthesis of imaging metrics reporting on vascularity, cellularity, and cell proliferation will provide predictive measurements of tumor response to treatment in appropriately selected clinical trials. Our goal is to provide the breast cancer community with practical data acquisition and analysis protocols that facilitate the translation of advanced imaging technologies into patient management and clinical trials.
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|Virostko, John; Hainline, Allison; Kang, Hakmook et al. (2018) Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted magnetic resonance imaging for predicting the response of locally advanced breast cancer to neoadjuvant therapy: a meta-analysis. J Med Imaging (Bellingham) 5:011011|
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|McKenna, Matthew T; Weis, Jared A; Quaranta, Vito et al. (2018) Variable Cell Line Pharmacokinetics Contribute to Non-Linear Treatment Response in Heterogeneous Cell Populations. Ann Biomed Eng 46:899-911|
|Woodall, Ryan T; Barnes, Stephanie L; Hormuth 2nd, David A et al. (2018) The effects of intravoxel contrast agent diffusion on the analysis of DCE-MRI data in realistic tissue domains. Magn Reson Med 80:330-340|
|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|
|Sorace, Anna G; Wu, Chengyue; Barnes, Stephanie L et al. (2018) Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting. J Magn Reson Imaging :|
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