基于CT观察退变性腰椎滑脱症与关节突关节角及关节椎弓根角的关系

doi:10.3969/j.issn.1006-6233.2024.02.023

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摘要 目的: 基于CT观察探讨退变性腰椎滑脱(DLS)与关节突关节角和关节椎弓根角的关系。方法: 回顾性收集2020年1月至2022年6月四川省骨科医院收治的169例DLS症患者纳为DLS组,另选取同期于我院体检并伴有腰腿疼痛但未腰椎滑脱的169例年龄匹配患者作为健康组;对比DLS组和健康组的临床资料,单因素以及多因素logistic回归分析影响DLS的危险因素;通过平滑曲线拟合分析关节突关节角和关节椎弓根角与DLS的曲线关系,构建贝叶斯网络模型并对其预测效能进行验证。结果: 单因素分析结果显示DLS组在BMI、椎间盘退变、全身关节松弛、腰椎结构及曲度发生改变、韧带松弛、骨质疏松、脱钙、腰椎小关节突病变、合并糖尿病方面均高于健康组(P<0.05);DLS组的关节突关节角与健康组相比减小,关节突关节角不对称以及退变程度为1、2级的人数比例上升,椎弓根角显著增大(P<0.05);多因素分析结果表明BMI增加、椎间盘退变、腰椎结构及曲度发生改变、韧带松弛、骨质疏松、脱钙、全身关节松弛、腰椎小关节突病变、合并糖尿病、关节突关节角减小、关节突关节角不对称、关节突关节的退变以及椎弓根角的增加都是导致DLS发生的危险因素(OR值>1,P<0.05);平滑曲线拟合结果显示,在一定范围内,关节椎弓根角与DLS呈正相关,而关节突关节角和与DLS呈负相关;贝叶斯网络模型及预测推理显示:BMI指数增加、关节突关节角减小、关节突关节角不对称以及椎弓根角的增加与DLS直接相关,当患者关节突关节角减小、关节突关节角不对称以及椎弓根角的增加的概率降为0时,患者DLS发生率由50%降低为37.2%;经过模型验证证明贝叶斯网络预测模型具有良好的区分度、准确度和有效性。结论: 基于CT观察可以对DLS有更准确的诊断,且在一定范围内关节突关节角和关节椎弓根角与DLS具有一定的相关性。

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关键词 ：退变性腰椎滑脱, 计算机断层扫描, 关节突关节角, 关节椎弓根角, 相关性, 贝叶斯网络模型

Abstract：Objective: To explore the relationship between degenerative lumbar spondylolisthesis (DLS) and facet joint angles and zygapophyseal articular process root angles based on CT observation. Methods: A retrospective analysis was conducted on 169 patients diagnosed with DLS at Sichuan Provincial Orthopedic Hospital from January 2020 to June 2022 (DLS group). Additionally, 169 age-matched patients with lumbar and leg pain but without lumbar spondylolisthesis, who underwent physical examinations during the same period, were selected as the healthy control group. Clinical data were compared between the two groups, and both univariate and multivariate logistic regression analyses were performed to identify factors influencing DLS. Smooth curve fitting was used to analyze the curve relationship between facet joint angles, zygapophyseal articular process root angles, and DLS. A Bayesian network model was constructed, and its predictive performance was validated. Results: Univariate analysis revealed that BMI, intervertebral disc degeneration, systemic joint laxity, changes in lumbar spine structure and curvature, ligament laxity, osteoporosis, decalcification, lumbar facet joint lesions, and comorbid diabetes were higher in the DLS group than in the healthy group (P<0.05). The facet joint angles in the DLS group were smaller than those in the healthy group, and the proportion of individuals with asymmetrical facet joint angles and degeneration degrees of 1 and 2 increased, while the zygapophyseal articular process root angle significantly increased (P<0.05). Multivariate analysis indicated that an increase in BMI, intervertebral disc degeneration, changes in lumbar spine structure and curvature, ligament laxity, osteoporosis, decalcification, systemic joint laxity, lumbar facet joint lesions, comorbid diabetes, decrease in facet joint angles, asymmetry of facet joint angles, degeneration of facet joint angles, and an increase in zygapophyseal articular process root angles were all risk factors for DLS (OR>1, P<0.05). Smooth curve fitting results demonstrated a positive correlation between zygapophyseal articular process root angles and DLS within a certain range, while facet joint angles showed a negative correlation with DLS. The Bayesian network model and predictive reasoning revealed that an increase in BMI, decrease in facet joint angles, asymmetry of facet joint angles, and an increase in zygapophyseal articular process root angles were directly associated with DLS. When the probability of decreased facet joint angles, asymmetry of facet joint angles, and an increase in zygapophyseal articular process root angles reached zero, the occurrence rate of DLS decreased from 50% to 37.2%. Model validation confirmed the good discriminability, accuracy, and effectiveness of the Bayesian network predictive model. Conclusion: CT observation provides a more accurate diagnosis of DLS, and within a certain range, facet joint angles and zygapophyseal articular process root angles are correlated with DLS.

Key words： Degenerative lumbar spondylolisthesis Computer tomography Angles of zygapophysial joints Pedicle facet angle Correlation Bayesian network model

基金资助:四川省中医药管理局科研课题,(编号:2020LC0174)

引用本文:

李兰, 殷小丹, 李旭雪, 张滔, 刘愉勤. 基于CT观察退变性腰椎滑脱症与关节突关节角及关节椎弓根角的关系[J]. 河北医学, 2024, 30(2): 290-296.
LI Lan, et al. Relationship between Degenerative Lumbar Spondylolisthesis and Facet Joint Angles and Zygapophyseal Articular Process Root Angles Based on CT Observation. HeBei Med, 2024, 30(2): 290-296.

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http://www.hbyxzzs.cn/CN/10.3969/j.issn.1006-6233.2024.02.023 或 http://www.hbyxzzs.cn/CN/Y2024/V30/I2/290

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