Nomogram based on radiomics analysis of ultrasound images can improve preoperative BRAF mutation diagnosis for papillary thyroid microcarcinoma - Tang, Jiajia; Jiang, Shitao; Ma, Jiaojiao; Xi, Xuehua; Li, Huilin; Wang, Liangkai; Zhang, Bo (Frontiers in Endocrinology, 2022)
Background: The preoperative identification of BRAF mutation could assist to make appropriate treatment strategies for patients with papillary thyroid microcarcinoma (PTMC). This study aimed to establish an ultrasound (US) radiomics nomogram for assessment of BRAF status. Methods: A total of 328 PTMC patients at the China-Japan Friendship Hospital between February 2019 and November 2021 were enrolled in this study. They were randomly divided into training (n=232) and validation (n=96) cohorts. Radiomics features were extracted from US images. The least absolute shrinkage and selection operator (LASSO) regression were applied to select BRAF status-related features and calculate the radiomics score (Rad-score). Univariate and multivariate logistic regression analyses were subsequently performed to identify the independent factors among Rad-score and conventional US features. The US radiomics nomogram was established and its predictive performance was evaluated via discrimination, calibration, and clinical usefulness in the training and validation sets. Results: Multivariate analysis indicated that Rad-score, composition and aspect ratio were independent predictive factors of BRAF status. The US radiomics nomogram which incorporated three variables showed good calibration. The discrimination of the US radiomics nomogram showed better discriminative ability than conventional US model both in the training sets (AUC 0.685 vs 0.592) and validation sets (AUC 0.651 vs 0.622). Decision curve analysis indicated showed the superior clinical applicability of the nomogram than conventional US model. Conclusions: The US radiomics nomogram displayed better perfomance than the conventional US model in predicting BRAF mutation in patients with PTMC.