目的 探讨联合X线及MRI影像学特征构建的列线图预测早期非创伤性股骨头坏死（NONFH）塌陷风险的价值。 方法 收集苏州大学附属第一医院（中心1）和上海交通大学医学院苏州九龙医院（中心2）早期NONFH 149例患者（237髋）的临床、X线及MRI数据，分为训练集与验证集。采用单因素和多因素Cox回归分析，筛选坏死股骨头塌陷的独立危险因素，并构建3年和5年的单一因素模型和多因素联合模型，使用AUC值评估各模型效能，C指数评估各模型一致性，选择效能最佳模型构建列线图，使用训练集数据内部验证，使用验证集数据进行外部验证。 结果 中心1共纳入159髋，中心2共纳入78髋，多因素Cox回归分析显示，股骨头塌陷的独立危险因素为JIC分型（HR = 37.78，95%CI：4.631 ~ 308.15，P < 0.001）、关节积液（HR = 1.613，95%CI：1.037 ~ 2.509，P = 0.034）、坏死指数（HR = 1.016，95%CI：1.003 ~ 1.028，P = 0.012）。内部及外部验证集数据显示3年和5年的联合模型均具有更好的预测效能、更佳的准确性和更高的净收益，校准曲线显示列线图预测的风险概率与实际观测结果一致性良好。 结论 基于X线及MRI影像学特征所构建的列线图，能够有效预测早期NONFH患者的股骨头塌陷风险，为制定个体化临床干预策略提供重要参考。

Objective To explore the value of constructing a nomogram based on the combined X-ray and MRI imaging characteristics for predicting the risk of early non-traumatic osteonecrosis of the femoral head （NONFH） collapse. Methods Clinical， X-ray， and MRI data from 149 early-stage NONFH patients （237 hips） at two medical centers were collected and then divided into training and validation cohorts. Univariate and multivariate Cox regression analyses were carried out to pinpoint independent predictors of femoral head collapse. Single-factor and multi-factor predictive models for 3-year and 5-year outcomes were developed. The performance of the models was evaluated using the area under the curve （AUC）， and the consistency of the models was assessed using the concordance index （C-index）. The optimal model was chosen for nomogram construction. Internal validation was carried out with the training cohort， and external validation was performed using the validation cohort. Results A total of 159 hips from center 1 and 78 hips from center 2 were incorporated into the study. Multivariate Cox regression analysis pinpointed the JIC classification （HR = 37.78， 95%CI： 4.631 - 308.15， P < 0.001）， joint effusion （HR = 1.613， 95%CI： 1.037 - 2.509， P = 0.034）， and necrosis index （HR = 1.016， 95%CI： 1.003 - 1.028， P = 0.012） as independent predictors of femoral head collapse. Both internal and external validations verified that the combined model for 3-year and 5-year prediction displayed superior performance， enhanced accuracy， and increased net benefit. Calibration curves revealed a good concordance between the risk probabilities predicted by the nomogram and the actual observed outcomes. Conclusion The nomogram constructed on the basis of X-ray and MRI imaging features can effectively predict the risk of femoral head collapse in patients with NONFH， offering crucial guidance for the formulation of individualized clinical intervention strategies.