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Accuracy of Radiomics in the Identification of Extrathyroidal Extension and BRAFV600E Mutations in Papillary Thyroid
Yan Liu1, Ling Xiang2, Fang-Yue Liu3
1Department of Radiology and Intervention, Hospital Pakar Kanak-Kanak (UKM Specialist Children's Hospital), Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, 56000, Kuala Lumpur, Malaysia (Y.L., F.Y.L., J.N.C., H.A.H., H.A.M.); Department of Ultrasound, Affiliated Hospital of Pan Zhihua University, Panzhihua, 61700, Sichuan Province, China (Y.L., L.X.); Tianfu Jincheng Laboratory, City of Future Medicine, Chengdu 641400, China (Y.L., Q.L.).
Rationale And Objectives:
Extrathyroidal extension (ETE) and BRAFV600E mutation in papillary thyroid cancer (PTC) increase mortality and recurrence risk. Preoperative identification presents considerable challenges. Although radiomics has emerged as a potential tool for identifying ETE and BRAFV600E mutation, systematic evidence supporting its effectiveness remains insufficient. Therefore, this paper aims to determine the effectiveness of radiomics in detecting ETE and BRAFV600E mutations in PTC.
Materials And Methods:
PubMed, Web of Science, Cochrane, and Embase databases were searched until May 7th, 2024. The Radiomics Quality Score tool assessed bias risk. Subgroup analyses based on radiomics and clinical characteristics were conducted.
Results:
Our systematic review included 19 studies, encompassing 5337 PTC cases. Among these, 12 articles focused on ETE and seven articles focused on BRAFV600E mutations. For the identification of ETE in the validation set, the summarized machine learning (ML) models demonstrated 0.80c-index (95%CI: 0.77-0.83), 0.77 sensitivity (95%CI: 0.72-0.81), and 0.78 specificity (95%CI: 0.73-0.82). Radiomics based on ultrasound demonstrated 0.82c-index (95%CI: 0.78-0.86), 0.77 sensitivity (95%CI: 0.68-0.84), and 0.84 specificity (95%CI: 0.75-0.91). For the identification of BRAFV600E mutations in the validation set, the summarized ML models showed 0.80c-index (95%CI: 0.72-0.87), 0.76 sensitivity (95%CI: 0.67-0.84), and 0.88 specificity (95%CI: 0.77-0.94). ML models based on ultrasound-guided radiomics had 0.81c-index (95%CI: 0.74-0.89), 0.79 sensitivity (95%CI: 0.71-0.86), and 0.87 specificity (95%CI: 0.74-0.94).
Conclusion:
Radiomics in identifying ETE and BRAFV600E mutation have high c-index, sensitivity, and specificity, especially images from ultrasound, demonstrating the potential for diagnosing ETE and BRAFV600E mutations in PTC.
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