BACKGROUND AND PURPOSE: Quantitative metrics of the dural sac such as the cross-sectional area are commonly used to evaluate central canal stenosis. The aim of this study was to analyze 2 new metrics to measure spinal stenosis on the basis of the ratio between the dural sac and disc cross-sectional areas (DDRCA) and the dural sac and disc anterior-posterior diameters (DDRDIA) and compare them with established quantitative metrics of the dural sac.MATERIALS AND METHODS: T2-weighted axial MR images (n ¼ 260 patients) were retrospectively evaluated, graded for central canal stenosis as normal (no stenosis), mild, moderate, or severe from L1/L2 through L5/S1 with 1 grade per spinal level and annotated to measure the DDRCA and DDRDIA. Thresholds were obtained using a decision tree classifier on a subset of patients (n ¼ 130) and evaluated on the remaining patients (n ¼ 130) for accuracy and consistency across demographics, anatomic variation, and clinical outcomes.RESULTS: DDRCA and DDRDIA had areas under the receiver operating characteristic curve of 98.6 (97.4-99.3) and 98.0 (96.7-98.9) compared with dural sac cross-sectional area at 96.5 (95.0-97.7) for binary classification. DDRDIA and DDRCA had k scores of 0.75 (0.71-0.79) and 0.80 (0.75-0.83) compared with dural sac cross-sectional area at 0.62 (0.57-0.66) for multigrade classification. No significant differences (P . .1) in the area under the receiver operating characteristic curve were observed for the DDRDIA across variations in the body mass index. The DDRDIA also had the highest area under the receiver operating characteristic curve among symptomatic patients (visual analog scale $ 7) or patients who underwent surgery.CONCLUSIONS: Ratio-based metrics (DDRDIA and DDRCA) are accurate and robust to anatomic and demographic variability compared with quantitative metrics of the dural sac and better correlated with symptomatology and surgical outcomes. ABBREVIATIONS: AUROC ¼ area under the receiver operating characteristic curve; BMI ¼ body mass index; DDRCA ¼ ratio between dural sac and disc cross-sectional areas; DDRDIA ¼ ratio between dural sac and disc anterior-posterior diameters; DSCA ¼ dural sac cross-sectional area; DSDIA ¼ dural sac anterior-posterior diameter; LSS ¼ lumbar spinal stenosis; VAS ¼ visual analog scale
Background Lumbar spinal stenosis (LSS) is a prevalent and disabling cause of low back and leg pain in elderly people and nerve root sedimentation sign (NRSS) has been demonstrated to have high sensitivity and specificity in diagnosing LSS in selected patients. The purpose of this study was to investigate the diagnosis of LSS and the predictive value of NRSS. Methods The clinical and imaging data of 176 patients diagnosed with LSS and 156 patients with non-specific low back pain (LBP) were analyzed retrospectively. Transverse magnetic resonance images (MRI) of the narrowest spinal canal in all patients were acquired and graded by two experienced doctors using the Braz classification, Schizas classification and Chen Jia classification. Receiver operating curve (ROC) was used to compare the diagnostic efficacy of the three classifications. Univariate and multivariate logistic regression models were established to predict the surgical indications of LSS patients. Result The diagnostic efficacy of Schizas classification (AUC:0.943; 95%CI:0.918,0.969) and Chen Jia classification (AUC:0.942; 95%CI:0.918,0.966) was significantly higher than that of Braz classification (AUC:0.853; 95%CI:0.808,0.898). Chen Jia classification had the highest correlation with the degree of dural sac cross-sectional area (DCSA) stenosis. In the multivariate analysis of LSS surgical indications, Chen Jia classification (odds ratio [OR], 2.127; 95%CI:1.596,2.835), DCSA (OR,0.398; 95%CI:0.169,0.802) and intermittent claudication (OR,9.481; 95%CI:3.439,26.142) were associated with surgical indications. Conclusion Among the three types, it is found that Chen Jia classification has better diagnostic efficacy in differentiating LSS from LBP. In addition, Chen Jia classification is simple to be implemented in clinical practice and has high clinical application value. Hence, Chen Jia classification can be used as an effective surgical treatment indicator for LSS patients.
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