Spinal cord demyelination predicts neurological deterioration in patients with mild degenerative cervical myelopathy.

IF 2.1 Q3 CLINICAL NEUROLOGY
BMJ Neurology Open Pub Date : 2025-01-31 eCollection Date: 2025-01-01 DOI:10.1136/bmjno-2024-000940
Abdul Al-Shawwa, Michael Craig, Kalum Ost, David Anderson, Steve Casha, W Bradley Jacobs, Nathan Evaniew, Saswati Tripathy, Jacques Bouchard, Peter Lewkonia, Fred Nicholls, Alex Soroceanu, Ganesh Swamy, Kenneth C Thomas, Stephan duPlessis, Michael Mh Yang, Julien Cohen-Adad, Nicholas Dea, Jefferson R Wilson, David W Cadotte
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Abstract

Background: Degenerative cervical myelopathy (DCM) is the most common form of atraumatic spinal cord injury globally. Clinical guidelines regarding surgery for patients with mild DCM and minimal symptoms remain uncertain. This study aims to identify imaging and clinical predictors of neurological deterioration in mild DCM and explore pathophysiological correlates to guide clinical decision-making.

Methods: Patients with mild DCM underwent advanced MRI scans that included T2-weighted, diffusion tensor imaging and magnetisation transfer (MT) sequences, along with clinical outcome measures at baseline and 6-month intervals after enrolment. Quantitative MRI (qMRI) metrics were derived above and below maximally compressed cervical levels (MCCLs). Various machine learning (ML) models were trained to predict 6 month neurological deterioration, followed by global and local model interpretation to assess feature importance.

Results: A total of 49 patients were followed for a maximum of 2 years, contributing 110 6-month data entries. Neurological deterioration occurred in 38% of cases. The best-performing ML model, combining clinical and qMRI metrics, achieved a balanced accuracy of 83%, and an area under curve-receiver operating characteristic of 0.87. Key predictors included MT ratio (demyelination) above the MCCL in the dorsal and ventral funiculi and moderate tingling in the arm, shoulder or hand. qMRI metrics significantly improved predictive performance compared to models using only clinical (bal. acc=68.1%) or imaging data (bal. acc=57.4%).

Conclusions: Reduced myelin content in the dorsal and ventral funiculi above the site of compression, combined with sensory deficits in the hands and gait/balance disturbances, predicts 6-month neurological deterioration in mild DCM and may warrant early surgical intervention.

脊髓脱髓鞘可预测轻度退行性颈椎病患者的神经功能衰退。
背景:退行性颈椎脊髓病(DCM)是全球最常见的外伤性脊髓损伤。关于对症状轻微的轻度 DCM 患者进行手术的临床指南仍不确定。本研究旨在确定轻度 DCM 神经功能恶化的影像学和临床预测因素,并探索病理生理学相关因素,为临床决策提供指导:方法:轻度 DCM 患者接受先进的 MRI 扫描,包括 T2 加权、弥散张量成像和磁化转移(MT)序列,并在入组后的基线和 6 个月间隔期进行临床结果测量。在最大压迫颈椎水平(MCCL)的上方和下方得出了定量 MRI(qMRI)指标。对各种机器学习(ML)模型进行了训练,以预测6个月的神经功能恶化情况,然后对整体和局部模型进行解释,以评估特征的重要性:共有 49 名患者接受了长达 2 年的随访,提供了 110 个 6 个月的数据条目。38%的病例出现了神经功能恶化。结合临床和 qMRI 指标,表现最佳的 ML 模型达到了 83% 的均衡准确率,曲线下面积-接收器工作特征为 0.87。与仅使用临床数据(平衡准确率=68.1%)或成像数据(平衡准确率=57.4%)的模型相比,qMRI指标显著提高了预测性能:结论:压迫部位上方的背侧和腹侧漏斗状突起中的髓鞘含量减少,再加上手部感觉障碍和步态/平衡障碍,可预测轻度 DCM 患者 6 个月后的神经功能恶化情况,因此有必要尽早进行手术干预。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMJ Neurology Open
BMJ Neurology Open Medicine-Neurology (clinical)
CiteScore
3.20
自引率
3.70%
发文量
46
审稿时长
13 weeks
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