Spinal cord metabolism in multiple sclerosis: a decade of missed opportunities and future directions

Abstract

<h3>Background</h3><p>Despite spinal cord pathology driving progressive disability in multiple sclerosis (MS), research has disproportionately focused on brain imaging. The clinical manifestations most relevant to MS patients—mobility impairment, fatigue, and autonomic dysfunction—derive primarily from spinal cord involvement, yet spinal cord metabolism remains virtually unexplored.</p><h3>Objective</h3><p>To quantify the research gap in spinal cord metabolic imaging and evaluate scientific rationale, technological readiness, and implementation potential for establishing this approach as a cornerstone of MS research.</p><h3>Methods</h3><p>I conducted a structured literature analysis of MS imaging publications (2014–2024) using defined PubMed searches, analyzed clinical trial registries for metabolic endpoints, and reviewed technological advances supporting clinical implementation.</p><h3>Results</h3><p>The analysis revealed a striking 949:1 publication ratio between brain and spinal cord metabolic imaging studies, with only three spinal cord metabolic investigations versus 2847 brain imaging studies. Our 2014 study using ¹⁸F-FDG PET during walking exercise demonstrated significantly reduced glucose uptake in MS patients’ thoracic and lumbar spinal cord regions, correlating strongly with functional disability. Despite these promising findings and subsequent validation that spinal cord atrophy predicts disability progression better than brain measures, this research direction remained largely unexplored. Analysis of 387 MS clinical trials since 2014 revealed that while 73% include spinal cord structural measures, none incorporated metabolic assessments. Technological advances including total-body PET systems and AI-enhanced processing have addressed historical limitations.</p><h3>Conclusions</h3><p>Spinal cord metabolic imaging represents a transformative but neglected research opportunity that could revolutionize MS biomarker development and precision medicine approaches.</p>