Chen Tian-Xin, Wu Jun-Ying, Yang Tong-Jie, Chen Gang, Li Yan, Zhang Lei
Department of Sports Medicine, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Department of Bone and Joint, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Sci Rep. 2025 May 4;15(1):15575. doi: 10.1038/s41598-025-99813-z.
Anterior talofibular ligament (ATFL) injuries are common ankle injuries that require accurate grading for effective treatment planning. However, conventional diagnostic methods, including manual MRI interpretation, often lack objectivity and reproducibility. Radiomics, a technique that extracts quantitative features from medical images, offers a promising solution for enhancing diagnostic precision. This study developed a radiomics model based on MRI fat-suppressed proton density-weighted turbo spin-echo images to grade ATFL injuries. A dataset of 467 arthroscopically confirmed cases (276 partial tears, 191 complete tears) was analyzed, and 28 key features were selected for model construction using machine learning classifiers. The support vector machine (SVM) model achieved the best performance, with an AUC of 0.955 (95% CI: 0.931-0.980) on the training set and 0.844 (95% CI: 0.781-0.906) on the validation set. Decision curve analysis and confusion matrix results demonstrated the model's strong predictive accuracy and clinical utility. This SVM-based radiomics model offers a reliable, non-invasive approach for precise ATFL injury diagnosis and grading, with significant potential for improving clinical decision-making and personalized treatment.
距腓前韧带（ATFL）损伤是常见的踝关节损伤，为了制定有效的治疗方案，需要进行准确分级。然而，包括手动解读MRI在内的传统诊断方法往往缺乏客观性和可重复性。放射组学是一种从医学图像中提取定量特征的技术，为提高诊断精度提供了一个有前景的解决方案。本研究基于MRI脂肪抑制质子密度加权快速自旋回波图像建立了一个放射组学模型，用于对ATFL损伤进行分级。分析了一个包含467例经关节镜证实的病例（276例部分撕裂，191例完全撕裂）的数据集，并使用机器学习分类器选择了28个关键特征用于模型构建。支持向量机（SVM）模型表现最佳，在训练集上的AUC为0.955（95%CI：0.931 - 0.980），在验证集上为0.844（95%CI：0.781 - 0.906）。决策曲线分析和混淆矩阵结果证明了该模型具有很强的预测准确性和临床实用性。这种基于SVM的放射组学模型为精确诊断和分级ATFL损伤提供了一种可靠的非侵入性方法，在改善临床决策和个性化治疗方面具有巨大潜力。
