This project will benefit public health by ushering in a new technology to reduce MRI scan times. FRONSAC adds nonlinear gradients of modest amplitude in dynamic waveforms to standard Cartesian MRI protocols. This small perturbation to the standard Cartesian MRI scan allows for greater undersampling of data, and faster acquisition times. This proposal is innovative because it marries the reliability of Cartesian imaging with a small amount of nonlinear gradient encoding to greatly enhance parallel imaging acceleration. The proposal is significant because it will demonstrate that a single well-characterized nonlinear gradient waveform can improve undersampled imaging for a broad range of clinical sequences and scan prescriptions, potentially doubling overall scan throughput for busy clinical sites.
The aims will demonstrate that, for many scan prescriptions, and even in the presence of common experimental imperfections or other parallel imaging strategies, FRONSAC further multiplies acceleration by an additional 2-4x. 1) Sequence development and optimization. a) Develop a FRONSAC waveform, with 3 NLG channels, for a GRE sequence that maximizes clinically acceptable acceleration. b) Using this FRONSAC waveform, develop a set of widely used clinical sequences implementing FRONSAC acceleration: 3D MP-RAGE, bSSFP, TSE and T2w-FLAIR. 2) Demonstrate FRONSAC imaging in vivo. a) Acquire human brain images and compare contrast with conventional encoding. b) Compare undersampling performance between FRONSAC and Cartesian encoding. 3) Show that undersampled images acquired using a FRONSAC gradient optimized for a single geometry shows persistent improvements over Cartesian encoding for human brain imaging (for different geometries and under various common experimental imperfections), and retains compatibility with other acceleration approaches. a) Test for undersampling artifacts when changing FOV, resolution, and slice orientation. b) Test sequences with known (introduced) imperfections: gradient timing errors, imperfect shim, or off-resonance spins. c) Demonstrate compatibility with both kz undersampling and multislice CAIPIRINHA.

Public Health Relevance

Highly undersampled MRI scans have great potential to reduce costs, enable new kinds of image contrast, and improve dynamic experiments, but clinical applications been limited by concern over undersampling artifacts. (1-7,54) FRONSAC (Fast Rotary Nonlinear Spatial ACquisition) is a highly promising nonlinear gradient method (11-25) which uses a small nonlinear perturbation to dramatically reduce undersampling artifacts (26,27), while maintaining many desirable features of Cartesian encoding. The aims of this proposal will demonstrate the versatility of a single FRONSAC gradient by (i) incorporating an optimized FRONSAC gradient into many different sequences (ii) testing in human brain to show contrast is that of a Cartesian scan but with undersampling artifacts reduced (iii) demonstrating improved undersampling even with changing geometry, experimental imperfections, and in conjunction with other tools of parallel imaging.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB022030-02
Application #
9572562
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Liu, Guoying
Project Start
2017-09-30
Project End
2021-06-30
Budget Start
2018-07-01
Budget End
2019-06-30
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Yale University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code