ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2025
Multimodal MRI-based clinical radiomics model for predicting postoperative anemia in patients with spinal metastases.
Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSpinal metastasis surgery frequently results in anemia, affecting patient recovery, yet lacks a quantitative method for assessing the risk of postoperative anemia. PURPOSE: This study investigates the potential of MRI-based radiomics models to predict postoperative anemia, aiding in personalized treatment and improved outcomes.
methods247 patients diagnosed with spinal metastases pathologically and underwent surgery from December 2012 to December 2023 were enrolled and divided into postoperative anemia (n = 158) and non-anemia (n = 89) groups. Radiomics features were extracted from regions of interest on sagittal T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and fat-suppressed (FS)-T2WI sequences of preoperative MRI scans. Then, seven radiomics models were developed using logistic regression analysis, supported by a five-fold cross-validation technique. The Radscore, originating from the model with the highest predictive accuracy, was chosen for nomogram development. After variable selection via stepwise logistic regression analyses, clinical variables and the Radscore were included in the clinical and combined clinical and Radscore models. Ultimately, three models—clinical, Radscore, and combined clinical and Radscore models—were developed. Receiver operating characteristic analyses, Brier score, calibration curves, and decision curve analyses were used for model performance evaluation.
resultsAmong the radiomics models, the one with feature integration based on T1WI and FS-T2WI sequences performed the best, with area under the curve (AUC) values of 0.844 (95% confidence interval [CI]: 0.789-0.9) and 0.819 (95% CI: 0.692–0.947), respectively in the training and test sets. The combined clinical and Radscore model (AUC: 0.747, 95% CI: 0.603–0.891) performs slightly better than the clinical model (AUC: 0.646, 95% CI: 0.474–0.817) (P = 0.148) and the Radscore model (AUC: 0.734, 95% CI: 0.584–0.844) (P = 0.759).
conclusionsThe combined clinical and Radscore nomogram could facilitate clinical decision-making for patients undergoing spinal metastasis surgery.
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