Recent large-scale studies have employed MRI to gain a deeper understanding of how our brain works in health and disease. Human Connectome Project (HCP) and UK Biobank initiatives use Echo Planar Imaging (EPI) to examine brain connectivity as revealed by functional (fMRI) and diffusion MRI (dMRI). Although EPI empowers neuroscience with the necessary fast encoding, it is plagued by distortion artifacts that severely affect regions with poor B0 field homogeneity, such as the temporal and frontal lobes. While Simultaneous MultiSlice (SMS) imaging is routinely used for more efficient sampling, high MultiBand (MB) factors leave little encoding power in existing acquisition methods for in-plane acceleration. This lets the image distortion remain unchecked to hamper brain regions that regulate decision-making, emotions and semantic memory. Further, neuroimaging protocols often employ inefficient structural imaging scans that consume a large portion of the allotted time, which could have been used for additional fMRI and dMRI sampling. We propose synergistic hardware, acquisition and reconstruction strategies to provide multiplicative gains in image distortion, while mitigating signal voids and T2*-related voxel blurring in EPI. We will design and build a 64-channel ?AC/DC? combined receive and shim brain array to provide >2 more uniform B0 field and improved parallel imaging capability. On the pulse sequence side, we will develop ?wave-CAIPI? trajectories for EPI and optimally utilize the encoding power of our AC/DC array to push the in-plane acceleration to 5-fold. This will combine multiplicatively with the gain from dynamic shimming to yield >10-fold distortion reduction, while retaining the ability to perform 2-fold SMS acceleration. Even at extreme MB factors (e.g. 8-fold), we will still allow for a >3 reduction in distortion to target hard-to-image regions with fast fMRI. We will also develop ?BUDA? acquisition to sample 2-shots of EPI with alternating phase encoding directions, and incorporate a B0 map in the reconstruction to eliminate distortion in high-resolution dMRI. We will build on these technologies and develop a suite of EPI-based quantitative structural imaging scans for whole-brain T1 and T2 parameter mapping with high geometric fidelity at 1mm isotropic resolution in 90 sec. These will empower longitudinal studies and leave more time for fMRI and dMRI acquisitions. Finally, we will validate the improvements in fMRI and dMRI by focusing on the ventromedial prefrontal cortex and the brain reward circuity, both placed in challenging regions due to their proximity to air/tissue interfaces. We will compare the developed rapid T1- and T2-weighted acquisitions against conventional T1- MPRAGE and T2-FSE scans by performing morphometric analysis. We will strive to disseminate our developments to fuel the next generation of neuroimaging projects, simply by plugging in our coil and installing our sequences.

Public Health Relevance

Functional and diffusion MRI are key contrast encoding strategies used to probe functional and structural information about the brain. These acquisitions typically use Echo Planar Imaging (EPI) for the necessary rapid sampling, but suffer from severe geometric distortions, T2*-related voxel blurring and signal dropouts. We will develop synergistic hardware design and image encoding strategies that can drastically reduce the artifacts of fast EPI to enable high quality functional and diffusion imaging of the entire brain, and finally allow EPI to be used for high-resolution T1- and T2-weighted acquisitions with high efficiency and geometric fidelity.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB028797-01
Application #
9864639
Study Section
Imaging Technology Development Study Section (ITD)
Program Officer
Wang, Shumin
Project Start
2020-02-01
Project End
2023-11-30
Budget Start
2020-02-01
Budget End
2020-11-30
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114