Application of MRI radiomics in classification diagnosis of anterior cruciate ligament injury
Objective To analyze the diagnostic value of MRI radiomics in the classification of anterior cruciate ligament(ACL)injury.Methods A total of 212 patients with abnormal signals of the ACL suggested by proton density weighted imaging in the Department of Radiology of the Affiliated Hospital of Binzhou Medical University from 2017 to 2022 were reviewed.The parents were divided into severe injury group(n=141)and mild injury group(n=71)based on arthroscopic findings,which was the gold standard in the classification of ACL injury.The radiomics features of the ACL images were extracted including shape features,first order features,texture features and wavelet features.The imbalance problem of data was solved by performing oversampling using SMOTE method.Consistency test was performed by intra-group and inter-group correlation coefficients.Patients were randomly divided into a training set and a test set at 7:3.The best radiomics features were selected by LASSO algorithm,and the radiomics model was established by Logistic regression.The radiomics model was established based on the radiomics features and the clinical model was established based on the clinical parameters of the two groups.The Nomogram model was established by the radiomics features and the clinical parameters as mentioned above.The diagnostic efficacy of the model was evaluated by ROC curves,sensitivity,specificity and accuracy in the training set and the test set.The difference between the model's predicted values and the actual observed values was evaluated by the calibration curve,and the clinical efficacy was evaluated by the clinical decision curve analysis.Results A total of 2553 features were obtained from proton density weighted imaging transverse,coronal and sagittal positions through feature extraction,and 12 feature parameters were retained through feature filtering and dimensionality reduction.The area under the curve(AUC)was 0.9105 for the training set of the radiomics model and 0.8561 for the test set.The best feature sets of diagnosing severe ACL injury were gender,joint instability,joint interlock and radiomics.In the clinical model,the AUC values of the training set was 0.6989 and the test set was 0.6415.In the Nonogram model,the AUC values of the training set was 0.9449 and the test set was 0.8661.The difference between the Nomogram model and the clinical model was statistically significant(P<0.05).The AUC of the Nomogram was higher than that of the radiomics model,but the difference was not statistically significant in the test set(P>0.05).Conclusion The radiomics method based on MRI images can provide a new diagnostic method in classification of ACL injury which can greatly improve the clinical diagnosis accuracy of ACL injury.Furthermore,the diagnostic efficiency of the Nomogram model is the best compared with the clinical model and the radiomics model.
万方数据
维普
