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Background <p>Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord impairment worldwide, yet conventional magnetic resonance imaging metrics of canal stenosis fail to explain the remarkable heterogeneity in patient outcomes.</p> Methods <p>We applied automated deep-learning segmentation to map the topography of intramedullary lesions in 73 patients and determine their tract-specific functional impact. Functional measures included the modified Japanese Orthopaedic Association score, comprising upper- and lower-body motor dysfunction, sensory function, and sphincter function domains; the Nine-Hole Peg Test for dexterity; and the Standing Balance Test.</p> Results <p>Here we show presence of T2-hyperintense lesions in 45% of the cohort, defining a biologically distinct phenotype associated with greater neurological disability. Spatially, lesion density peaked at C4, rostral to the site of maximal compression (C5), implicating venous congestion and ascending degeneration as key pathophysiological drivers. Multivariate modeling revealed that balance impairment represents a systems-level failure, predicted independently by combined damage to the dorsal columns (<i>P</i> = 0.032) and lateral reticulospinal tract (<i>P</i> = 0.011). In contrast, dexterity deficits were not attributable to any single tract, suggesting reliance on global cord integrity. Importantly, we found that unlike in traumatic spinal cord injury, residual tissue bridges (spared tissue) did not universally predict function; they conferred protective benefit for balance (<i>P</i> = 0.044) only when reticulospinal tract integrity was accounted for.</p> Conclusions <p>These findings establish tract-specific lesion profiling as a mechanistic biomarker, shifting the clinical framework from measuring global compression to characterizing biological vulnerability.</p>

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Rostral lesion shift and tract-specific degeneration drive functional heterogeneity in degenerative cervical myelopathy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月5日

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  • Fauziyya Muhammad,
  • Dario Pfyffer,
  • Nicholas Dobson,
  • Todd Parrish,
  • Serena S. Hu,
  • John Ratliff,
  • Nathaniel D. Stetson,
  • Yasin Dhaher,
  • Andrew C Smith,
  • Kenneth A. Weber II,
  • Zachary A. Smith

摘要

Background

Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord impairment worldwide, yet conventional magnetic resonance imaging metrics of canal stenosis fail to explain the remarkable heterogeneity in patient outcomes.

Methods

We applied automated deep-learning segmentation to map the topography of intramedullary lesions in 73 patients and determine their tract-specific functional impact. Functional measures included the modified Japanese Orthopaedic Association score, comprising upper- and lower-body motor dysfunction, sensory function, and sphincter function domains; the Nine-Hole Peg Test for dexterity; and the Standing Balance Test.

Results

Here we show presence of T2-hyperintense lesions in 45% of the cohort, defining a biologically distinct phenotype associated with greater neurological disability. Spatially, lesion density peaked at C4, rostral to the site of maximal compression (C5), implicating venous congestion and ascending degeneration as key pathophysiological drivers. Multivariate modeling revealed that balance impairment represents a systems-level failure, predicted independently by combined damage to the dorsal columns (P = 0.032) and lateral reticulospinal tract (P = 0.011). In contrast, dexterity deficits were not attributable to any single tract, suggesting reliance on global cord integrity. Importantly, we found that unlike in traumatic spinal cord injury, residual tissue bridges (spared tissue) did not universally predict function; they conferred protective benefit for balance (P = 0.044) only when reticulospinal tract integrity was accounted for.

Conclusions

These findings establish tract-specific lesion profiling as a mechanistic biomarker, shifting the clinical framework from measuring global compression to characterizing biological vulnerability.