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Abstract #4452

Myelin water imaging from an 8 minute scan at 64mT via image reconstruction and multicomponent T2 fitting in a low-rank space

Neale Wiley1, Sharada Balaji1, Megan Poorman2, Rui Teixeira3, Francesco Padormo3, Hanwen Liu1, Adam Dvorak1, Anthony Traboulsee1, Steve Williams4, Sean Deoni5, Alex Mackay1, and Shannon Kolind1
1University of British Columbia, Vancouver, BC, Canada, 2Hyperfine, Guilford, CT, United States, 3Hyperfine, Brentford, United Kingdom, 4King's College London, London, United Kingdom, 5Bill and Melinda Gates Foundation, Seattle, WA, United States

Synopsis

Keywords: Sparse & Low-Rank Models, Low-Field MRI, Myelin, Relaxometry

Motivation: Ultra-low field (ULF) MRI scanners are proliferating and their use to measure brain health through myelin content would benefit clinical applications and research.

Goal(s): To leverage low-rank algorithms to achieve quantitative measurements of brain myelin content at ULF.

Approach: Following low-rank reconstruction of 3D multi-spin-echo data, sets of 20 characteristic T2 decay curves were projected into the same low-rank space. A regularized non-negative least squares fit of these low-rank T2 vectors provided a T2 distribution; T2<40ms were assigned as myelin water.

Results: Maps of short T2 components reflected historical myelin water fraction values and corresponded to a myelin water fraction atlas.

Impact: Reconstruction and multi-component fitting in a low-rank space allows myelin water fraction mapping at 64mT, permitting quantitative ultra low-field measurements of brain development in infants and children and demyelination during the course of diseases like multiple sclerosis.

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Keywords