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作 者:陈浩 薛鹏 席洪钟 何帅 孙光权[1] 刘锌[1] 杜斌[1] CHEN Hao;XUE Peng;XI Hongzhong(Department of Orthopedics,Affiliated Hospital of Nanjing University of Chinese Medicine,Nanjing,Jiangsu Province 210029,P.R.China)
出 处:《临床放射学杂志》2024年第7期1170-1175,共6页Journal of Clinical Radiology
基 金:国家自然科学基金面上项目(编号:82074471);江苏省研究生科研与实践创新计划项目(编号:SJCX24_0961)。
摘 要:目的探讨基于数字X线摄影(DR)的深度学习(DL)模型在预测非血管化腓骨移植术(NVFG)疗效中的价值。方法纳入2009年6月至2021年6月接受NVFG进行保髋的339例(432髋)股骨头坏死(ONFH)患者,以3∶1的比例划分为训练集(n=324)和测试集(n=108)。每侧髋术前均拍摄标准正位、蛙位DR且分布于同一个数据集中。根据术后2年的随访结果定义保髋成败。以ResNet-50作为骨干网络构建DL模型,在训练集中训练、优化模型,并在测试集中采用受试者工作特征曲线(ROC)曲线下面积(AUC)、准确率(Acc)、精确率(Pre)、召回率(Rec)和F1-score进行模型的预测性能评估。结果截至2023年6月,309髋随访结果优良,保髋成功率达71.52%。联合正位、蛙位DR图像构建的模型,对NVFG疗效的预测性能最佳(P<0.05),其AUC为0.780,Acc为0.789,Pre为0.787,Rec为0.960,F1-score为0.865。基于正位DR的模型AUC为0.660,Acc为0.662,Pre为0.703、Rec为0.900、F1-score为0.790;基于蛙位DR的模型AUC为0.710,Acc为0.761,Pre为0.762,Rec为0.960,F1-score为0.850。结论基于DR的DL模型能准确预测NVFG的保髋疗效,具有一定的临床应用价值。Objective To explore the value of deep learning(DL)models based on digital radiography(DR)in predicting the efficacy of non-vascularized fibular grafting(NVFG).Methods A total of 339 patients(432 hips)with osteonecrosis of the femoral head(ONFH)who underwent NVFG between June 2009 and June 2021 were included.They were divided into a training set(n=324)and a test set(n=108)in a ratio of 3∶1.Standard anteroposterior and frog-lateral DR images were taken before surgery for both hips and distributed within the same dataset.The success or failure of preservation was defined based on the follow-up results at 2 years postoperatively.A DL model was constructed using ResNet-50 as the backbone network.The model was trained and optimized in the training set,and its predictive performance was evaluated in the test set using metrics such as the area under the curve(AUC),accuracy(Acc),precision(Pre),recall(Rec),and F1-score.Results As of June 2023,a total of 309 hips had excellent follow-up results,with a success rate of 71.52% for preservation.The model constructed using combined anteroposterior and frog-lateral DR images showed the best predictive performance for NVFG efficacy(P<0.05),with an AUC of 0.780,Acc of 0.789,Pre of 0.787,Rec of 0.960,and F1-score of 0.865.The model based on anteroposterior DR had an AUC of 0.660,Acc of 0.662,Pre of 0.703,Rec of 0.900,and F1-score of 0.790.The model based on frog-lateral DR had an AUC of 0.710,Acc of 0.761,Pre of 0.762,Rec of 0.960,and F1-score of 0.850.Conclusion The DL model based on DR can accurately predict the efficacy of NVFG,which is worthy of application to clinical practice.
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