Intramedullary Lesions and Perilesional Tissue Bridges Predict Motor Recovery in Degenerative Cervical Myelopathy: A Multicenter Study
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Background and Objectives
Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord-related disability worldwide. T2-weighted (T2w) intramedullary hyperintensities are common MRI findings in DCM and may reflect irreversible pathology, namely intramedullary lesions. The prognostic value of both quantitative lesion characteristics and the integrity of surrounding spared spinal cord tissue—tissue bridges—remains unclear. Using automated quantification of intramedullary lesions and tissue bridges, this study aimed to determine whether these structures can serve as imaging biomarkers of clinical severity and predict functional recovery in DCM.
Methods
This retrospective, multicenter study included 94 patients with DCM from four tertiary centers. All underwent baseline MRI and clinical assessment, with 6-month follow-up in 48.9% (n=46) of patients at six months. We used SCIsegV2, an automated tool integrated in the Spinal Cord Toolbox, to segment T2w hyperintense lesions and midsagittal tissue bridges. Lesion characteristics (volume, length, width, maximal axial damage ratio) and tissue bridge widths were extracted. Clinical assessments included mJOA, Neck Disability Index (NDI), hand dexterity, and balance. We evaluated associations between imaging metrics and clinical outcomes by using correlation and multivariable linear regression models adjusted for baseline clinical score, age, sex, and surgical status.
Results
Intramedullary lesions were present in 45.7% (n=43) of patients and were associated with greater clinical severity. Lesion volume, length, and maximal axial damage ratio (MADR) correlated with dexterity and balance impairments, but not with mJOA or NDI. Wider tissue bridges were associated with better dexterity at both time points. Multivariable models showed lesion volume and MADR independently predicted poorer balance at follow-up, while tissue bridge width was positively linked to with dexterity improvements. In surgical patients, lesion magnitude and tissue bridge integrity explained up to 71% of the variance in follow-up outcomes.
Discussion
Automated quantification of intramedullary lesion extent and spared tissue bridges provide robust biomarkers for structural damage and preserved function in DCM. These features better predict recovery, particularly in dexterity and balance, than conventional metrics. Integrating these metrics into clinical workflows could enhance surgical decision-making and support personalized prognosis. Future studies should incorporate 3D segmentation and multimodal imaging to refine predictions of long-term outcomes prediction.
