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Abstract #2696

Portable ultra-low-field brain MRI: test-retest reliability and correspondence to high-field MRI

František Váša1, Carly Bennalick1, Niall J Bourke1, Francesco Padormo2, Paul Cawley3,4, Tomoki Arichi3,4, Tobias C Wood1, David J Lythgoe1, Flavio Dell'Acqua1,5, Levente Baljer1, Sean CL Deoni6, Ashwin V Venkataraman1,7, Rosalyn J Moran1, Robert Leech1, and Steven CR Williams1
1Department of Neuroimaging, King's College London, London, United Kingdom, 2Hyperfine, Inc., Guildford, CT, United States, 3Center for the Developing Brain, King's College London, London, United Kingdom, 4Medical Research Council Center for Neurodevelopmental Disorders, King's College London, London, United Kingdom, 5Department of Forensics and Neurodevelopmental Sciences, King's College London, London, United Kingdom, 6Bill and Melinda Gates Foundation, Seattle, WA, United States, 7Department of Old Age Psychiatry, King's College London, London, United Kingdom

Synopsis

Keywords: Gray Matter, Segmentation, Analysis/Processing, Brain, Data Acquisition, Validation

Motivation: Ultra-low-field MRI scanners offer a cost-effective and portable alternative to high-field neuroimaging.

Goal(s): To quantify between-scanner test-retest reliability of 64mT brain scans, and their correspondence to 3T MRI.

Approach: We scanned 23 healthy participants on two Hyperfine 64mT scanners and a GE 3T scanner using T1w and T2w scans at multiple resolutions. We segmented images into 98 structures and estimated their volumes.

Results: We demonstrate excellent reliability of volumetric estimates from ultra-low-field MRI, and high correspondence to high-field scans. The highest reliability and high-field correspondence was obtained using T2w ultra-low-field scans, super-resolved by combining three orthogonal acquisitions with low through-plane resolution.

Impact: Measures of brain volume from Hyperfine portable ultra-low-field MRI scans show excellent test-retest reliability across scanners, and excellent correspondence to similar estimates from high-field MRI. This enables quantitative analysis of cost-effective and portable neuroimaging in various contexts, including low-resource environments.

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Keywords