NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.
Centre Hospitalier de l'Université de Montréal, University of Montreal, Montreal, QC, Canada.
Sci Rep. 2023 Aug 19;13(1):13527. doi: 10.1038/s41598-023-40731-3.
Spinal cord cross-sectional area (CSA) is an important MRI biomarker to assess spinal cord atrophy in various neurodegenerative and traumatic spinal cord diseases. However, the conventional method of computing CSA based on vertebral levels is inherently flawed, as the prediction of spinal levels from vertebral levels lacks reliability, leading to considerable variability in CSA measurements. Computing CSA from an intrinsic neuroanatomical reference, the pontomedullary junction (PMJ), has been proposed in previous work to overcome limitations associated with using a vertebral reference. However, the validation of this alternative approach, along with its variability across and within participants under variable neck extensions, remains unexplored. The goal of this study was to determine if the variability of CSA across neck flexions/extensions is reduced when using the PMJ, compared to vertebral levels. Ten participants underwent a 3T MRI T2w isotropic scan at 0.6 mm for 3 neck positions: extension, neutral and flexion. Spinal cord segmentation, vertebral labeling, PMJ labeling, and CSA were computed automatically while spinal segments were labeled manually. Mean coefficient of variation for CSA across neck positions was 3.99 ± 2.96% for the PMJ method vs. 4.02 ± 3.01% for manual spinal segment method vs. 4.46 ± 3.10% for the disc method. These differences were not statistically significant. The PMJ method was slightly more reliable than the disc-based method to compute CSA at specific spinal segments, although the difference was not statistically significant. This suggests that the PMJ can serve as a valuable alternative and reliable method for estimating CSA when a disc-based approach is challenging or not feasible, such as in cases involving fused discs in individuals with spinal cord injuries.
脊髓横截面积(CSA)是评估各种神经退行性和外伤性脊髓疾病中脊髓萎缩的重要 MRI 生物标志物。然而,基于椎体水平计算 CSA 的传统方法存在固有缺陷,因为从椎体水平预测脊髓水平缺乏可靠性,导致 CSA 测量值存在相当大的变异性。以前的工作提出了从内在神经解剖参考 pontomedullary 交界处(PMJ)计算 CSA,以克服使用椎体参考的局限性。然而,这种替代方法的验证及其在不同颈部伸展时参与者之间和内部的可变性仍然未知。本研究的目的是确定与使用椎体水平相比,使用 PMJ 是否可以减少 CSA 在颈部屈伸时的变异性。十名参与者在 0.6 毫米的 3T MRI T2w 各向同性扫描下进行了 3 个颈部位置的扫描:伸展、中立和弯曲。脊髓分割、椎体标记、PMJ 标记和 CSA 是在自动计算的,而脊髓段是手动标记的。PMJ 方法的 CSA 在颈部位置的平均变异系数为 3.99±2.96%,而手动脊髓段方法为 4.02±3.01%,基于椎间盘的方法为 4.46±3.10%。这些差异没有统计学意义。PMJ 方法比基于椎间盘的方法略可靠,可用于计算特定脊髓段的 CSA,尽管差异没有统计学意义。这表明,当基于椎间盘的方法具有挑战性或不可行时,例如在脊髓损伤患者中存在融合椎间盘的情况下,PMJ 可以作为一种有价值的替代和可靠方法来估计 CSA。