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

Journal: Nature communications
PMID: 39622805

Abstract

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.

Authors

  • Annabel J Sorby-Adams
    Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Jennifer Guo
    Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Pablo Laso
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • John E Kirsch
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Julia Zabinska
    Department of Neurology, Center for Brain & Mind Health, Yale New Haven Hospital and Yale School of Medicine, New Haven, CT, USA.
  • Ana-Lucia Garcia Guarniz
    Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Pamela W Schaefer
    Department of Radiology, Division of Neuroradiology, Massachusetts General Hospital, Harvard Medical School, Room: GRB-273A, 55 Fruit Street, Boston, MA 02114, USA.
  • Seyedmehdi Payabvash
    Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
  • Adam de Havenon
    Department of Neurology, Yale School of Medicine, New Haven, CT.
  • Matthew S Rosen
    A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Kevin N Sheth
    Department of Neurology (G.J.F., E.P.K., R.B.N., K.R., J.A., K.N.S.), Yale School of Medicine, New Haven, CT.
  • Teresa Gomez-Isla
    Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • J Eugenio Iglesias
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • W Taylor Kimberly
    Division of Neurocritical Care and Center for Genomic Medicine, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.

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