Yunyan Zhang1, Laura Jonkman2, Antoine Klauser2, Frederik Barkhof3, V Wee Yong4, Luanne M Metz4, Jeroen Jg Geurts2. 1. Department of Radiology, University of Calgary, Calgary, AB, Canada/ Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada/ Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada yunyzhan@ucalgary.ca. 2. Department of Anatomy & Neurosciences, VU University Medical Center, Amsterdam, The Netherlands. 3. Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands. 4. Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada/ Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
Abstract
BACKGROUND: Lesions with different extents of myelin pathology are found at autopsy in multiple sclerosis (MS), but the differences are not discernible in magnetic resonance imaging (MRI). OBJECTIVE: To determine whether analysis of the local spectrum in MRI is sensitive to lesion differences in myelin integrity. METHODS: We imaged fresh brain slices from 21 MS patients using 1.5T scanners. White matter lesions were identified in T2-weighted MRI, matched to corresponding specimens, and then classified into five categories in histology: pre-active (intact myelin); active, chronic active, chronic inactive (complete demyelination); and remyelinated lesions. Voxel-based frequency spectrum was calculated using T2-weighted MRI to characterize lesion structure (image texture). RESULTS: MRI texture heterogeneity resulting from all spectral scales was greater in completely demyelinated lesions than in myelin-preserved lesions (p = 0.02) and normal-appearing white matter (p < 0.01). Moreover, the spectral distribution pattern over low-frequency scales differentiated demyelinated lesions from remyelinated and pre-active lesions (p < 0.01), where different lesion types also showed distinct texture scales. CONCLUSION: Using multi-scale spectral analysis, it may be possible for standard MRI to evaluate myelin integrity in MS lesions. This can be critical for monitoring disease activity and assessing remyelination therapies for MS patients.
BACKGROUND: Lesions with different extents of myelin pathology are found at autopsy in multiple sclerosis (MS), but the differences are not discernible in magnetic resonance imaging (MRI). OBJECTIVE: To determine whether analysis of the local spectrum in MRI is sensitive to lesion differences in myelin integrity. METHODS: We imaged fresh brain slices from 21 MS patients using 1.5T scanners. White matter lesions were identified in T2-weighted MRI, matched to corresponding specimens, and then classified into five categories in histology: pre-active (intact myelin); active, chronic active, chronic inactive (complete demyelination); and remyelinated lesions. Voxel-based frequency spectrum was calculated using T2-weighted MRI to characterize lesion structure (image texture). RESULTS: MRI texture heterogeneity resulting from all spectral scales was greater in completely demyelinated lesions than in myelin-preserved lesions (p = 0.02) and normal-appearing white matter (p < 0.01). Moreover, the spectral distribution pattern over low-frequency scales differentiated demyelinated lesions from remyelinated and pre-active lesions (p < 0.01), where different lesion types also showed distinct texture scales. CONCLUSION: Using multi-scale spectral analysis, it may be possible for standard MRI to evaluate myelin integrity in MS lesions. This can be critical for monitoring disease activity and assessing remyelination therapies for MS patients.
Authors: Maria-Eleni Dounavi; Audrey Low; Graciela Muniz-Terrera; Karen Ritchie; Craig W Ritchie; Li Su; Hugh S Markus; John T O'Brien Journal: Brain Commun Date: 2022-05-05
Authors: Rebekah L Petroff; Christopher Williams; Jian-Liang Li; James W MacDonald; Theo K Bammler; Todd Richards; Christopher N English; Audrey Baldessari; Sara Shum; Jing Jing; Nina Isoherranen; Brenda Crouthamel; Noelle McKain; Kimberly S Grant; Thomas M Burbacher; G Jean Harry Journal: Environ Health Perspect Date: 2022-09-14 Impact factor: 11.035
Authors: Elizabeth N York; Sarah-Jane Martin; Rozanna Meijboom; Michael J Thrippleton; Mark E Bastin; Edwin Carter; James Overell; Peter Connick; Siddharthan Chandran; Adam D Waldman; David P J Hunt Journal: Brain Commun Date: 2021-11-03