Keegan B Mark, Absinta Martina, Cohen-Adad Julien, Flanagan Eoin P, Henry Roland G, Klawiter Eric C, Kolind Shannon, Krieger Stephen, Laule Cornelia, Lincoln John A, Messina Steven, Oh Jiwon, Papinutto Nico, Smith Seth Aaron, Traboulsee Anthony
Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA.
Department of Neurology, Johns Hopkins University, Baltimore, MD 21218, USA.
Brain Commun. 2024 Nov 6;6(6):fcae395. doi: 10.1093/braincomms/fcae395. eCollection 2024.
Spinal cord disease is important in most people with multiple sclerosis, but assessment remains less emphasized in patient care, basic and clinical research and therapeutic trials. The North American Imaging in Multiple Sclerosis Spinal Cord Interest Group was formed to determine and present the contemporary landscape of multiple sclerosis spinal cord evaluation, further existing and advanced spinal cord imaging techniques, and foster collaborative work. Important themes arose: (i) multiple sclerosis spinal cord lesions (differential diagnosis, association with clinical course); (ii) spinal cord radiological-pathological associations; (iii) 'critical' spinal cord lesions; (iv) multiple sclerosis topographical model; (v) spinal cord atrophy; and (vi) automated and special imaging techniques. Distinguishing multiple sclerosis from other myelopathic aetiology is increasingly refined by imaging and serological studies. Post-mortem spinal cord findings and MRI pathological correlative studies demonstrate MRI's high sensitivity in detecting microstructural demyelination and axonal loss. Spinal leptomeninges include immune inflammatory infiltrates, some in B-cell lymphoid-like structures. 'Critical' demyelinating lesions along spinal cord corticospinal tracts are anatomically consistent with and may be disproportionately associated with motor progression. Multiple sclerosis topographical model implicates the spinal cord as an area where threshold impairment associates with multiple sclerosis disability. Progressive spinal cord atrophy and 'silent' multiple sclerosis progression may be emerging as an important multiple sclerosis prognostic biomarker. Manual atrophy assessment is complicated by rater bias, while automation (e.g. Spinal Cord Toolbox), and artificial intelligence may reduce this. Collaborative research by the North American Imaging in Multiple Sclerosis and similar groups with experts combining distinct strengths is key to advancing assessment and treatment of people with multiple sclerosis spinal cord disease.
