Thyroid Nodule Diagnosis in Dynamic Contrast-Enhanced Ultrasound via Microvessel Infiltration Awareness

Dynamic contrast-enhanced ultrasound (CEUS) video with microbubble contrast agents reflects the microvessel distribution and dynamic microvessel perfusion, and may provide more discriminative information than conventional gray ultrasound (US). Thus, CEUS video has vital clinical value in differentiating between malignant and benign thyroid nodules. In particular, the CEUS video can show numerous neovascularisations around the nodule, which constantly infiltrate the surrounding tissues. Although the infiltrative of microvessel is ambiguous on CEUS video, it causes the tumor size and margin to be larger on CEUS video than on conventional gray US and may promote the diagnosis of thyroid nodules. In this paper, we propose a novel framework to diagnose thyroid nodules based on dynamic CEUS video by considering microvessel infiltration and via segmented confidence mapping assists diagnosis. Specifically, the Temporal Projection Attention (TPA) is proposed to complement and interact with the semantic information of microvessel perfusion from the time dimension of dynamic CEUS. In addition, we employ a group of confidence maps with a series of flexible Sigmoid Alpha Functions (SAF) to aware and describe the infiltrative area of microvessel for enhancing diagnosis. The experimental results on clinical CEUS video data indicate that our approach can attain an diagnostic accuracy of 88.79% for thyroid nodule and perform better than conventional methods. In addition, we also achieve an optimal dice of 85.54% compared to other classical segmentation methods. Therefore, consideration of dynamic microvessel perfusion and infiltrative expansion is helpful for CEUS-based diagnosis and segmentation of thyroid nodules. The datasets and codes will be available.