Keywords: Neuroinflammation, Multiple Sclerosis, Ex vivo; Ultra-high-resolution; Postmortem
Motivation: Cortical lesions in multiple sclerosis are clinically relevant but cannot be detected reliably using conventional MRI. Ex vivo ultra-high-resolution MRI is reliable in cortical lesion detection.
Goal(s): Identify cortical lesions on ex vivo 7T MRI in comparison to postmortem in situ conventional 3T MRI.
Approach: Retrospective visual assessment of cortical lesions on conventional MRI.
Results: 3T T1-weighted MPRAGE showed the highest sensitivity (66%), followed by T2-weighted SPACE (52%), and 3D FLAIR (48%) for detection of cortical lesions. Purely cortical lesions were less visible on in situ MRIs. Some leukocortical lesions appeared juxtacortical white matter lesions on conventional MRI.
Impact: Ultra-high-resolution MRI provides a platform to investigate substrates of cortical pathology in multiple sclerosis by bridging the gap between macroscopic conventional MRI and pathology.
1. Geurts JJ, Calabrese M, Fisher E, Rudick RA. Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet neurology 2012;11:1082-1092.
2. Schmierer K, Parkes HG, So PW, et al. High field (9.4 Tesla) magnetic resonance imaging of cortical grey matter lesions in multiple sclerosis. Brain : a journal of neurology 2010;133:858-867.
3. Dutta R, Mahajan KR, Nakamura K, et al. Comprehensive Autopsy Program for Individuals with Multiple Sclerosis. Journal of visualized experiments : JoVE 2019:e59511.
4. Kim S, Sakaie K, Blümcke I, Jones S, Lowe MJ. Whole-brain, ultra-high spatial resolution ex vivo MRI with off-the-shelf components. Magnetic Resonance Imaging 2021;76:39-48.
5. Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. Journal of computer assisted tomography 1994;18:192-205.
6. Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation. International Conference on Medical image computing and computer-assisted intervention; 2015: Springer: 234-241.
7. Avants BB, Epstein CL, Grossman M, Gee JC. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical image analysis 2008;12:26-41.
Figure 1: An example of purely cortical lesion that did not involve white matter. Panels (a) shows ultra-high-resolution FLASH and (b) corresponding 3T postmortem in situ conventional MRI, and (c) axial, coronal, and sagittal planes of the same lesion on 7T FLASH, 3T MPRAGE, 3T T2-weighted SPACE, and 3T 3D FLAIR. The lesion was not visible on T1-weighted or T2-weighted images and subtly visible on FLAIR. Note overall amount of lesion load in both white matter and cortex.
Figure 2: Purely cortical lesion not involving white matter is not visible on all 3 modalities: Panels (a) shows ultra-high-resolution FLASH and (b) corresponding 3T postmortem in situ conventional MRI, and (c) axial, coronal, and sagittal planes of the same lesion on 7T FLASH, 3T MPRAGE, 3T T2-weighted SPACE, and 3T 3D FLAIR. The lesion was not visible on T1-weighted or T2-weighted images and subtly visible on FLAIR. Note overall amount of lesion load in both white matter and cortex.
Figure 3: An example of leukocortical lesion that has small cortical involvement. Black hole and T2 hyperintensity are observed. FLAIR showed a black hole on a portion likely due to the inversion timing. Panels (a) shows ultra-high-resolution FLASH and (b) corresponding 3T postmortem in situ conventional MRI, and (c) axial, coronal, and sagittal planes of the same lesion on 7T FLASH, 3T MPRAGE, 3T T2-weighted SPACE, and 3T 3D FLAIR. The lesion was not visible on T1-weighted or T2-weighted images and subtly visible on FLAIR.