• Yunsheng Wang, Ning Song, Jiali Zhang, Jia Li, Ruoyu Li, and Linfeng Wang.
• Department of Orthopaedic Surgery, Third Hospital of Hebei Medical University, Qiaoxi District, 139 Ziqiang Road, Shijiazhuang, 050051, China.
• Eur Spine J. 2024 Aug 1; 33 (8): 326132673261-3267.

PurposeThis study aimed to evaluate and compare the predictive value of vertebral bone quality (VBQ) score for low BMD and osteoporosis. Furthermore, we sought to enhance diagnostic effectiveness by integrating VBQ with easily accessible patient-specific factors.MethodsWe retrospectively analyzed data from 180 patients. VBQ was obtained by preoperative MRI. Low BMD was classified as meeting the standards for either osteopenia or osteoporosis. The receiver operating characteristic curve analysis and multivariate logistic regression were used to detect the ability of variables to assess BMD. The z-test was used to compare the area under the curves of different variables.ResultsVBQ was more effective in identifying low BMD than osteoporosis (AUC, 0.768 vs. 0.613, p = 0.02). Elevated VBQ (OR 6.912, 95% CI 2.72-17.6) and low BMI (0.858, 0.76-0.97) were risk factors for low BMD, while the risk factor for osteoporosis was age (1.067, 1.02-1.12), not VBQ. ROC analysis showed that AUCs were 0.613 for VBQ and 0.665 for age when screening for osteoporosis. The combined variable of VBQ, sex, age, and BMI obtained by logistic regression significantly improved the efficacy of BMD screening, with an AUC of 0.824 for low BMD and 0.733 for osteoporosis.ConclusionVBQ is better at detecting low BMD than identifying osteoporosis. The ability of VBQ to predict osteoporosis is limited, and a similar diagnostic efficacy can be achieved with age. Incorporating VBQ alongside demographic data enhances the efficiency of BMD assessment. With the development of artificial intelligence in medicine, this simple method is promising.© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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