Despite recent development of various new approaches to therapy, breast cancer remains the second leading cause of cancer death in women. Treatment with anti-angiogenic drugs combined with conventional cytotoxic drugs or immunotherapy is a promising means of treating aggressive cancer. Anti-angiogenic drugs are thought to temporarily normalize abnormal vasculature and paradoxically increase blood flow and hence delivery of drug and effector immune cells to tumors. However, a substantial proportion of patients do not respond to this combination therapy and it is unclear whether the failure is due to failure of the anti-angiogenic to normalize the vasculature or failure of the cytotoxic drugs or immune cells to kill cancer cells. It is therefore necessary to assess both blood flow and cell death to elucidate the mechanism and to optimize the combination treatments. In this proposal we investigate a single MRI acquisition and analysis that will allow assessment of both. Dynamic contrast enhanced (DCE) MRI has been widely used as an important part of most clinical MRI exams for diagnosis of cancer, and it holds high potential as a single MRI method to estimate both perfusion parameters (such as, flow, F, vascular volume fraction, vp, and vascular permeability-surface area product, PS) and cellular parameters (such as, interstitial volume fraction, ve, and intracellular water life time, ?i). Recently, we developed a novel data acquisition method, namely active contrast encoding (ACE)-MRI, which measures dynamic data together with pre-contrast T1 and B1 that are critical for measurement of perfusion and cellular parameters. ACE-MRI is also implemented with a fast 3D imaging method to acquire high-spatial and high- temporal resolution data using a 3D golden-angle ultra-short echo-time (UTE) sequence and an image reconstruction method to combine both compressed sensing and parallel imaging, also known as GRASP (Golden-angle RAdial Sparsity and Parallel). In this study, we plan to further develop ACE-MRI for accurate estimation of contrast agent concentration in vascular plasma and tissue using a direct blood sampling method (Aim 1), and to assess the association of ?i with tumor metabolic rate and treatment response in comparison with 18F-FDG-PET and pathology (Aim 2). Overall, the ACE-MRI parameters will be used to assess treatment response and metastatic potential (Aim 3). This study will be conducted with murine and human breast cancer models at a 7T small animal MRI scanner. However, the methods developed in this study can be easily translated to clinical applications as it is used on a UTE sequence readily available on most clinical scanners.

Public Health Relevance

Assessment of cancer treatment requires an effective non-invasive method of measuring both the vascular and cellular changes induced by the therapies. Our underlying hypotheses is that a single dynamic contrast enhanced MRI measurement using the Active Contrast Encoding MRI method can provide a fast and quantitative means to assess both anti-angiogenic and cytotoxic responses to the therapy. The research in this proposal will establish an innovative method of assessing chemotherapy that will significantly improve drug discovery and patient management in a variety of cancers including breast cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
7R01CA160620-08
Application #
10322546
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Zhang, Huiming
Project Start
2012-03-01
Project End
2024-01-31
Budget Start
2021-02-01
Budget End
2022-01-31
Support Year
8
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Weill Medical College of Cornell University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
060217502
City
New York
State
NY
Country
United States
Zip Code
10065
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Winters, Kerryanne V; Reynaud, Olivier; Novikov, Dmitry S et al. (2018) Quantifying myofiber integrity using diffusion MRI and random permeable barrier modeling in skeletal muscle growth and Duchenne muscular dystrophy model in mice. Magn Reson Med 80:2094-2108
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Kim, Sungheon Gene; Friedman, Kent; Patel, Sohil et al. (2016) Potential Role of PET/MRI for Imaging Metastatic Lymph Nodes in Head and Neck Cancer. AJR Am J Roentgenol 207:248-56
Freed, Melanie; Storey, Pippa; Lewin, Alana Amarosa et al. (2016) Evaluation of Breast Lipid Composition in Patients with Benign Tissue and Cancer by Using Multiple Gradient-Echo MR Imaging. Radiology 281:43-53
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