# Advanced Neuroimaging through Novel Encoding Strategies and Hardware Design

> **NIH NIH R01** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $570,894

## Abstract

Project Summary/Abstract
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.

## Key facts

- **NIH application ID:** 10304118
- **Project number:** 5R01EB028797-03
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Berkin Bilgic
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $570,894
- **Award type:** 5
- **Project period:** 2020-02-01 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10304118

## Citation

> US National Institutes of Health, RePORTER application 10304118, Advanced Neuroimaging through Novel Encoding Strategies and Hardware Design (5R01EB028797-03). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10304118. Licensed CC0.

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