Administrative Supplment ? Fast Functional MRI with Sparse Sampling and Model- Based Reconstruction This application is being submitted in response to NOT-EB-18-019, as an administrative supplement to facilitate dissemination of technology developed in the parent grant, 5 R01 EB023618, Fast Functional MRI with Sparse Sampling and Model-Based Reconstruction. The overarching goal of the parent grant is to develop a novel ultrafast whole-brain fMRI acquisition approach that expands the spatiotemporal resolution envelope by roughly 3-fold in comparison to the current leading methods. To distribute this new fMRI acquisition to other research sites, we propose to further develop a novel framework for vendor-independent pulse programming developed by our group in collaboration with University Medical Center Freiburg, Germany, and the group of Sairam Geethanath (co-I). Our framework allows the sequence to be designed in, e.g., Matlab and exported via a vendor-independent file format to the MR scanner for direct execution. In preliminary work, we demonstrated that an identical sequence can be played out on both GE and Siemens scanners without the need for the operator to manually specify any aspect of the sequence. This guarantees identicalexecution of all RF and gradient waveforms on both vendor platforms, and eliminates time-consuming and error-prone vendor-specific pulse programming. We therefore believe this framework is ideal for quickly disseminating new MR acquisitions and specifically, those proposed in the parent R01. A major applications domain focus of the parent R01 is to improve low- and high-frequency resting- state functional connectivity measures using the proposed high-speed imaging methods. The proposed supplement project will also validate the reproducibility (test-retest reliability) of resting-state maps across sites and vendors.

Public Health Relevance

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Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
3R01EB023618-02S1
Application #
9750331
Study Section
Program Officer
Liu, Guoying
Project Start
2018-09-24
Project End
2020-12-31
Budget Start
2018-09-24
Budget End
2018-12-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Olafsson, Valur T; Noll, Douglas C; Fessler, Jeffrey A (2018) Fast Spatial Resolution Analysis of Quadratic Penalized Least-Squares Image Reconstruction With Separate Real and Imaginary Roughness Penalty: Application to fMRI. IEEE Trans Med Imaging 37:604-614
Ravishankar, Saiprasad; Moore, Brian E; Nadakuditi, Raj Rao et al. (2017) Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging. IEEE Trans Med Imaging 36:1116-1128