This project seeks to deliver unprecedented speed and imaging performance to low-field MRI to demonstrate that low-cost, lightweight implementations of MRI can be developed to allow robust, transportable imaging well suited to diagnose time-sensitive injuries such as head trauma and stroke. Current experimental mobile-sized systems are far too slow and low-resolution for such real-world applications. By innovating upon an already state of the art low-field 6.5 mT MR imaging system through a series of advanced hardware upgrades and pulse sequence optimizations, we expect to achieve 30-fold improvement in imaging speed and thus acquire moderately high-resolution 3D image datasets in about 10 seconds.
Our specific aims are 1) to optimize the design of and install the upgraded gradient hardware, which would provide greater flexibility push our pulse sequences to far higher speeds, and 2) to validate the clinical utility of the optimized system in normal and Traumatic Brain Injury patients and evaluate the low-field system in comparison with gold standard 3T scanning, which will enable us to further optimize our low-field sequences. The technical advances of this low-field project, which are more efficiently developed within an existing larger test-bed system, will be readily translatable into future miniaturized MR systems.

Public Health Relevance

This project is of relevance to public health in that it seeks to develop technology to enable portable MRI scanners that can be operated in mobile environments such as ambulances to rapidly image and diagnose time-sensitive injuries such as head trauma or stroke, where immediate knowledge of the internal state of injury is critical to successful early intervention and improved patient outcomes. This project also pushes forward the movement of low-cost, 'low-field' MR imaging, which may ultimately result in clinically less expensive MRI scanning for many disease types.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
1F32EB022390-01
Application #
9122654
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Erim, Zeynep
Project Start
2016-09-01
Project End
2018-08-31
Budget Start
2016-09-01
Budget End
2017-08-31
Support Year
1
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
Cohen, Ouri; Zhu, Bo; Rosen, Matthew S (2018) MR fingerprinting Deep RecOnstruction NEtwork (DRONE). Magn Reson Med 80:885-894