High SNR Functional Brain Imaging using Oscillating Steady State MRI Functional brain imaging using MRI (functional MRI or fMRI) has grown rapidly over the past 25 years and is widely used for basic cognitive neuroscience research and for presurgical planning. It is increasingly being used for developing biomarkers for neurological and psychiatric disorders and for population based studies of, for example, normal and abnormal development and aging. There have also been developments in imaging hardware and methods as well as processing methods to correct for artifacts and analyze functional activity. The overarching goal of this project is to develop a novel whole-brain fMRI acquisition approach that improves the SNR by 2- to 3-fold in comparison to the current leading methods. Such a boost is roughly equivalent to the SNR gain one achieves in going from 3T to 7T, but without the additional costs. Our goal is to provide rapid, high SNR, sub-millimeter resolution images with very good temporal resolution. Our approach is fundamentally different that nearly all standard fMRI methods in that is uses a newly discovered source of signal for fMRI that is based on an oscillating steady state approach which reuses magnetization and thus, improves the signal strength. This signal is shown to have contrast weighting that is similar to standard fMRI methods. The oscillations are very reproducible, which will allow the use of model based reconstructions, for example low-rank (LR) methods. A novel LR tensor and acquisition approach based on with a golden-angle rotated variable density acquisition is proposed that, in preliminary data, show a 17-fold speed-up with very low error rates. Together, these methods promise to dramatically improve the signal-to-noise ratio (SNR) of fMRI and allow for higher spatial resolution. The project has four main aims: (1) Analyze and simulate the spin physics of the OSS signal to elucidate the nature of this signal and obtain optimally sensitive and robust acquisition parameters, (2) Develop optimal image acquisition and reconstruction methods for OSS fMRI acquisition. The acquisition and reconstruction strategies are necessarily linked and are unique to the OSS approach, (3) Develop and evaluate methods to address several well-recognized issues associated with fMRI acquisition, notably physiological noise and head motion, and (4) Evaluate the OSS fMRI approach in comparison to state-of-the-art simultaneous multislice (SMS) acquisition methods in phantoms and in human subjects using both task and resting state fMRI. The proposed technology will greatly improve the SNR and spatial resolution for a given set of hardware (main magnetic field strength, RF coils arrays). Higher SNR will allow for more robust fMRI in individual subject, while spatial resolution is important as the functional units (cortical columns) of the brain are 1-2mm and similarly, functionally distinct layers are sub-mm with the distances from input and output layers being about 1mm. Since the methods do not relay on any unique hardware, the method can be widely and quickly disseminated to the neuroimaging community.

Public Health Relevance

Functional magnetic resonance imaging (fMRI) is used to measure brain function, and has revolutionized our understanding of cognitive processes during the last 25 years and has also been used as a tool for presurgical mapping of language and other sensitive brain regions. More recently, fMRI is being used as a biomarker for the progression of neurologic and psychiatric diseases, for example, in Alzheimer's disease and major depression. In this project we will improve fMRI techniques by developing new methods that will reduce variability and noise and improve the sharpness of the images without increasing instrumentation costs.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01EB026977-02
Application #
9789877
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Wang, Shumin
Project Start
2018-09-30
Project End
2023-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
2
Fiscal Year
2019
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