Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease.

Autor: Sorby-Adams, Annabel J., Guo, Jennifer, Laso, Pablo, Kirsch, John E., Zabinska, Julia, Garcia Guarniz, Ana-Lucia, Schaefer, Pamela W., Payabvash, Seyedmehdi, de Havenon, Adam, Rosen, Matthew S., Sheth, Kevin N., Gomez-Isla, Teresa, Iglesias, J. Eugenio, Kimberly, W. Taylor
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Zdroj: Nature Communications; 12/2/2024, Vol. 15 Issue 1, p1-12, 12p
Abstrakt: Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot. However, image quality is limited by a lower signal-to-noise ratio. Here, we optimize LF-MRI acquisition and develop a freely available machine learning pipeline to quantify brain morphometry and white matter hyperintensities (WMH). We validate the pipeline and apply it to outpatients presenting with mild cognitive impairment or dementia due to AD. We find hippocampal volumes from ≤ 3 mm isotropic LF-MRI scans have agreement with conventional MRI and are more accurate than anisotropic counterparts. We also show WMH volume has agreement between manual segmentation and the automated pipeline. The increased availability and reduced cost of LF-MRI, in combination with our machine learning pipeline, has the potential to increase access to neuroimaging for dementia. Portable, low-field MRI of the brain may facilitate assessment of patients with Alzheimer's disease. Here, the authors present and validate an end-to-end pipeline to quantify brain morphometry using LF-MRI in patients with dementia. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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