The overarching goal of this program project grant application is to change current clinical paradigms through the support of accurate, early detection and measurement of breast cancer response to chemotherapy (Projects 1, 3), and presurgical motor and temporal language cortex evaluation of brain function (Project 2) through the development, application and testing of robust and sophisticated registration and related signal processing tools. Project 1 investigates the efficacy of early-assessment and measurement of response to neoadjuvant chemo or hormonal therapy for patients with breast cancer obtained through the use of volumetric, diffusion and dynamic contrast enhancement MRI. The hypothesis is that nonlinear registration of interval breast exams increases the sensitivity and specificity of functional diffusion mapping (fDM) as well as the accuracy of dynamic contrast enhancement (DCE). Developing low noise, unbiased tools for assessing lesion response to therapy is currently an important topic. Project 2 extends previously completed work on registration-based fMRI motion by examining the benefits of combining our unique motion correction method with different fMRI acquisition protocols, e.g. clustered acquisition, to improve communication with the patient and response monitoring. Project 3 addresses the fundamental ambiguity problem in dynamic MRI associated with imaging in general: for any given technique either we can obtain high spatial or temporal resolution imaging data, but not both. Generalized techniques that support controlling and optimizing these tradeoffs during dynamic imaging in MRI are very important.

Public Health Relevance

The hypothesis is that these tools will dramatically improve the management of breast cancer patients by individuating therapy based on early, more accurate information that the chosen therapy regimen is/isn't working and should be continued/changed, respectively. For breast cancer therapy patients there is no reason to risk anemia, depleted white cells and platelets, and lost time to continue a debilitating chemotherapy regimen with no benefits in tumor suppression. For brain cancer patients the hypothesis is that presurgical evaluation of language and motor cortex will dramatically effect presurgical planning possibly even to the extent of deciding that a tumor is inoperable based on deficits that would be induced by its removal. Additional risks associated with extended open cranium-durations from electro-stimulation studies can be avoided by an appropriate presurgical fMRI evaluation which specifically includes the language and motor cortex, while reserving surgery primarily for resection. For both sets of patients emotional and monetary costs as well as health risks could be significantly reduced.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Program Projects (P01)
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Special Emphasis Panel (ZCA1-GRB-P (O1))
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Nordstrom, Robert J
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University of Michigan Ann Arbor
Schools of Medicine
Ann Arbor
United States
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Muckley, Matthew J; Noll, Douglas C; Fessler, Jeffrey A (2015) Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA). IEEE Trans Med Imaging 34:578-88
Weller, Daniel S; Ramani, Sathish; Fessler, Jeffrey A (2014) Augmented Lagrangian with variable splitting for faster non-Cartesian L1-SPIRiT MR image reconstruction. IEEE Trans Med Imaging 33:351-61
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Allison, Michael J; Ramani, Sathish; Fessler, Jeffrey A (2013) Accelerated regularized estimation of MR coil sensitivities using augmented Lagrangian methods. IEEE Trans Med Imaging 32:556-64
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Sripada, Chandra Sekhar; Kessler, Daniel; Welsh, Robert et al. (2013) Distributed effects of methylphenidate on the network structure of the resting brain: a connectomic pattern classification analysis. Neuroimage 81:213-21
Chun, Se Young; Fessler, Jeffrey A (2013) Noise properties of motion-compensated tomographic image reconstruction methods. IEEE Trans Med Imaging 32:141-52
Matakos, Antonios; Ramani, Sathish; Fessler, Jeffrey A (2013) Accelerated edge-preserving image restoration without boundary artifacts. IEEE Trans Image Process 22:2019-29

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