Fat-Water MR Elastography with Distributed Encoding for Accelerated Imaging of Brain and Skull Displacement

Motivation: There exists a need for a noninvasive method capable of capturing skull-brain dynamics in vivo to provide accurate input parameters for computational models of traumatic brain injury. Goal(s): We aimed to develop an accelerated fat-water imaging technique to quantify relative skull-brain displacement using magnetic resonance elastography (MRE). Approach: Elastography with distributed generalized encoding was used to accelerate our previously developed fat-water MRE sequence to enable more extensive data collection in a single imaging session. Results: This technique was able to simultaneously image skull and brain displacement with sufficient harmonic wave displacement to capture brain mechanical properties and bulk motion comparable to previous studies. Impact: Quantifying relative skull-brain motion with the proposed sequence will help researchers define the transfer of skull-to-brain force transmission for ultimately determining regional variation in tissue displacement throughout the brain and the influence of different directions and frequencies of applied motion.

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Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/0793
Primary Topic
Elasticity and Material Modeling
Type
article
Field-Weighted Citation Impact
0.00
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article

Fat-Water MR Elastography with Distributed Encoding for Accelerated Imaging of Brain and Skull Displacement

Dzung L. Pham, Alex Cerjanic, Mary Kramer, Olivia Bailey et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Elasticity and Material Modeling
article

Fat-Water MR Elastography with Distributed Encoding for Accelerated Imaging of Brain and Skull Displacement

Dzung L. Pham, Alex Cerjanic, Mary Kramer, Olivia Bailey, Alexa Diano, Curtis L. Johnson, Joy Mojumder
article en

Abstract

Motivation: There exists a need for a noninvasive method capable of capturing skull-brain dynamics in vivo to provide accurate input parameters for computational models of traumatic brain injury. Goal(s): We aimed to develop an accelerated fat-water imaging technique to quantify relative skull-brain displacement using magnetic resonance elastography (MRE). Approach: Elastography with distributed generalized encoding was used to accelerate our previously developed fat-water MRE sequence to enable more extensive data collection in a single imaging session. Results: This technique was able to simultaneously image skull and brain displacement with sufficient harmonic wave displacement to capture brain mechanical properties and bulk motion comparable to previous studies. Impact: Quantifying relative skull-brain motion with the proposed sequence will help researchers define the transfer of skull-to-brain force transmission for ultimately determining regional variation in tissue displacement throughout the brain and the influence of different directions and frequencies of applied motion.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 76%
Elasticity and Material Modeling
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Fat-Water MR Elastography with Distributed Encoding for Accelerated Imaging of Brain and Skull Displacement — Dzung L. Pham, Alex Cerjanic, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2025) | TGRS Research Map | TGRS