Spine Care Institute, Hospital for Special Surgery, Weill Cornell Medicine, 535 East 70th Street, New York City, NY, 10021, USA.
Center for Musculoskeletal Surgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
Eur Spine J. 2022 Nov;31(11):3109-3118. doi: 10.1007/s00586-022-07351-3. Epub 2022 Aug 29.
To investigate whether (1) there is a difference between patients with normal or sagittal spinal and spinopelvic malalignment in terms of their paraspinal muscle composition and (2) if sagittal malalignment can be predicted using muscle parameters.
A retrospective review of patients undergoing posterior lumbar fusion surgery was conducted. A MRI-based muscle measurement technique was used to assess the cross-sectional area, the functional cross-sectional area, the intramuscular fat and fat infiltration (FI) for the psoas and the posterior paraspinal muscles (PPM). Intervertebral disc degeneration was graded for levels L1 to S1. Sagittal vertical axis (SVA; ≥ 50 mm defined as spinal malalignment), pelvic incidence (PI) and lumbar lordosis (LL) were measured, and PI-LL mismatch (PI-LL; ≥ 10° defined as spinopelvic malalignment) was calculated. A receiver operating characteristic (ROC) analysis was conducted to determine the specificity and sensitivity of the FI for predicting sagittal malalignment.
One hundred and fifty patients were analysed. The PI-LL and SVA malalignment groups were found to have a significantly higher FI (PI-LL:47.0 vs. 42.1%; p = 0.019; SVA: 47.7 vs. 41.8%; p = 0.040). ROC analysis predicted sagittal spinal malalignment using FI (cut-off value 42.69%) with a sensitivity of 73.4% and a specificity of 54.1% with an area under the curve of 0.662.
Significant differences in the muscle composition between normal and malalignment groups with respect to FI in both sagittal spinal and spinopelvic alignment were found. This work underlines the imminent impact of the paraspinal musculature on the sagittal alignment.
研究脊柱矢状位和脊柱骨盆失平衡患者的椎旁肌组成是否存在差异（1），以及矢状位失平衡是否可以通过肌肉参数来预测（2）。
对接受后路腰椎融合术的患者进行回顾性研究。采用基于 MRI 的肌肉测量技术评估腰大肌和多裂肌的横截面积、功能横截面积、肌内脂肪和脂肪浸润（FI）。对 L1 至 S1 水平的椎间盘退变进行分级。测量矢状垂直轴（SVA；≥50mm 定义为脊柱失平衡）、骨盆入射角（PI）和腰椎前凸（LL），并计算 PI-LL 不匹配（PI-LL；≥10°定义为脊柱骨盆失平衡）。进行接收者操作特征（ROC）分析，以确定 FI 预测矢状位失平衡的特异性和敏感性。
共分析了 150 例患者。发现 PI-LL 和 SVA 失平衡组的 FI 明显更高（PI-LL：47.0%比 42.1%；p=0.019；SVA：47.7%比 41.8%；p=0.040）。ROC 分析预测矢状位脊柱失平衡时，FI 的截断值为 42.69%，灵敏度为 73.4%，特异性为 54.1%，曲线下面积为 0.662。
在脊柱矢状位和脊柱骨盆失平衡的情况下，FI 显示正常组和失平衡组的椎旁肌组成存在显著差异。这项工作强调了椎旁肌对矢状位排列的直接影响。
