Feasibility Study of Texture Analysis Using Ultrasound Shear Wave Elastography to Predict Malignancy in Thyroid Nodules

Abstract

Textural analysis of ultrasound shear wave elastography (SWE) was evaluated to discriminate benign and malignant thyroid nodules. Sixteen papillary thyroid cancers and 89 benign hyperplastic nodules in 105 patients underwent SWE using four static pre-compression levels. Fifteen gray level co-occurrence matrix textural features and six absolute SWE indices were computed from SWE images. Diagnostic performances of each SWE index for malignancy were calculated and compared using the area under the receiver operating characteristic curve (AUC), and optimal models were generated at each pre-compression level. The optimal model comprised two SWE textural features at the highest pre-compression level, which attained AUC, sensitivity and specificity of 0.973, 97.5% and 90.0%, respectively. By comparison, absolute SWE indices attained AUC of 0.709 as well as 18.8% sensitivity and 95.8% specificity. These preliminary results suggest SWE textural analysis can distinguish benign and malignant thyroid nodules and SWE spatial heterogeneity is greater in malignant nodules.