Radiomics Study of Thyroid Ultrasound for Predicting <i>BRAF</i> Mutation in Papillary Thyroid Carcinoma: Preliminary Results

Abstract

BACKGROUND AND PURPOSE: ) mutation in papillary thyroid cancer. MATERIALS AND METHODS: mutation was positive in 48 nodules and negative in 48 nodules. For analysis, ROIs from the nodules were demarcated manually on both longitudinal and transverse sonographic images. We extracted a total of 86 radiomics features derived from histogram parameters, gray-level co-occurrence matrix, intensity size zone matrix, and shape features. These features were used to build 3 different classifier models, including logistic regression, support vector machine, and random forest using 5-fold cross-validation. The performance including accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve, of the different models was evaluated. RESULTS: mutation in papillary thyroid cancers with an area under the curve value of 0.651, accuracy of 64.3%, sensitivity of 66.8%, and specificity of 61.8%, on average, for the 3 models. CONCLUSIONS: mutation status of papillary thyroid carcinoma. Further studies will be needed to validate our results using various diagnostic methods.

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