In previously published work by local coinvestigators a fundamental correlation between the increase in the quantitative MR apparent diffusion coefficient (ADC) measured over the pre- to early post-initiation therapy interval and the response of various brain tumors has been recently demonstrated. This work was demonstrated in the brains of both rats and humans and was based on a voxel-based analysis of change in the scatter plots of ADC values between rigidly registered pre- and post-therapeutic ADC MRI exams. The goal of this Project is to develop and refine registration techniques that not only demonstrate the same correlation exists in breast cancer as an early biomarker of cell death and potential surrogate for clinical outcome, but also increase the accuracy of such techniques by including perfusion-related computed parameters, and implementing accurate, automatic warping registration techniques. In addition to following the lead of the previous work which demonstrated the correlation using epidemiological methods, e.g. successful stratification of Kaplan-Meier plots based on ADC changes within volumes of interest defined by oncologists in both animals and humans, we will extend the approach to eliminate the need for multiple definition of gross volumes of interest by oncologists and improve the performance of the measure within heterogeneous tumors. Additionally for a subset of data we will carry histological results back to the in vivo images for correlation with histological truth.

Public Health Relevance

. The development of accurate and automatic registration of interval MRI diffusion breast exams will help individuate neoadjuvant chemotherapy for breast cancer patients by improving the accuracy of estimating tumors'early response (1-3 weeks) to therapy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA087634-10
Application #
8445392
Study Section
Special Emphasis Panel (ZCA1-GRB-P)
Project Start
Project End
2015-02-28
Budget Start
2013-03-01
Budget End
2014-02-28
Support Year
10
Fiscal Year
2013
Total Cost
$196,419
Indirect Cost
$64,966
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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
Zhao, Feng; Fessler, Jeffrey A; Wright, Steven M et al. (2014) Regularized estimation of magnitude and phase of multi-coil b1 field via Bloch-Siegert B1 mapping and coil combination optimizations. IEEE Trans Med Imaging 33:2020-30
Weller, Daniel S; Ramani, Sathish; Nielsen, Jon-Fredrik et al. (2014) Monte Carlo SURE-based parameter selection for parallel magnetic resonance imaging reconstruction. Magn Reson Med 71:1760-70
Watanabe, Takanori; Kessler, Daniel; Scott, Clayton et al. (2014) Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine. Neuroimage 96:183-202
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
Ramani, Sathish; Weller, Daniel S; Nielsen, Jon-Fredrik et al. (2013) Non-cartesian MRI reconstruction with automatic regularization Via Monte-Carlo SURE. IEEE Trans Med Imaging 32:1411-22
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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