Multimodal radiomics model with triple -timepoint contrast-enhanced ultrasound for precise diagnosis of C-TIRADS 4 thyroid nodules

Our study developed a high-performance multimodal diagnostic model through the innovative integration of radiomic features from three critical CEUS timepoints combined with conventional ultrasound and clinical data, establishing a novel decision-support tool for accurate noninvasive classification of C-TIRADS 4 thyroid nodules. The model's superior diagnostic performance (AUC 0.967) demonstrates the transformative potential of multimodal integration in overcoming single-modality limitations and enhancing clinical decision-making, positioning this approach as a promising solution to mitigate unnecessary diagnostic procedures and overtreatment.