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• Clinical Article •
Identification of triangular fibrocartilage complex injury based on MRI radiomics model
TENG Peihong  ZHANG Butian  YANG Huimin  REN Lingling  LI Xiaojing  BAI Yingjie  LIU Guifeng 

Cite this article as: Teng PH, Zhang BT, Yang HM, et al. Identification of triangular fibrocartilage complex injury based on MRI radiomics model[J]. Chin J Magn Reson Imaging, 2022, 13(9): 58-62. DOI:10.12015/issn.1674-8034.2022.09.011.


[Abstract] Objective To develop a MRI-based radiomics model to evaluate the diagnostic efficiency of the injury of triangular fibrocartilage complex (TFCC).Materials and Methods In this retrospective study, 100 cases (injury/non-injury: 50/50) were enrolled from China-Japan Union Hospital of Jilin University within January 2019 to December 2021. All patients had high resolution 3.0 T MRI examination of the wrist. Radiomics features of each patient were extracted from T2-weighted coronal imaging by manual segmentation. The Mann-Whitney U test and least absolute shrinkage and selection operator (LASSO) algorithm were used to eliminate irrelevant and redundant features, to additionally choose the significant features. The most significant parameters were used to build the prediction model by support vector machine (SVM) classifier. Predictive performance of the model was validated using the area under the receiver operating characteristics (ROC) curve (AUC), accuracy, sensitivity and specificity.Results A total of 88 initial radiomics features were extracted from each image. Twelve relevant radiomic features were selected based on the Mann-Whitney U test and LASSO algorithm. The classifier constructed with SVM achieved an AUC of 0.88 based on the most significant features, the accuracy, sensitivity and specificity were 90%, 92% and 100% respectively. The radiomics model exhibited good performance in predicting the injury of TFCC.Conclusions The MRI-based radiomics model could provide a non-invasive tool to identify the injury of TFCC and improve the detection rate of it.
[Keywords] wrist joint；triangular fibrocartilage complex；radiomics；magnetic resonance imaging；least absolute shrinkage and selection operator；support vector machine

TENG Peihong   ZHANG Butian   YANG Huimin   REN Lingling   LI Xiaojing   BAI Yingjie   LIU Guifeng*  

Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun 130000, China

*Liu GF, E-mail: gfliu@jlu.edu.cn

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China Youth Science Fund (No. 82001880); State Key Laboratory of Electroanalytical Chemistry Open Project Fund (No. SKLEAC202101); Special Fund for Clinical Research of Wu Jieping Medical Foundation (No. 320.6750.19089-38).
Received  2022-06-03
Accepted  2022-09-14
DOI: 10.12015/issn.1674-8034.2022.09.011
Cite this article as: Teng PH, Zhang BT, Yang HM, et al. Identification of triangular fibrocartilage complex injury based on MRI radiomics model[J]. Chin J Magn Reson Imaging, 2022, 13(9): 58-62. DOI:10.12015/issn.1674-8034.2022.09.011.

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