Multimodal ultrasound: a non-invasive method for identifying dedifferentiation of papillary thyroid carcinoma during active surveillance - Dou, Qian-Yi; Guo, Huan-Ling; Qiu, Wan-Bing; Xu, Ming; Chen, Shu-Ling; Zhang, Xiao-Er; Xie, Xiao-Yan; Liang, Jin-Yu (Frontiers in Oncology, 2025)
ObjectivesTo assess the diagnostic accuracy of multimodal ultrasound in differentiating anaplastic thyroid carcinoma (ATC) from papillary thyroid carcinoma (PTC) and to evaluate its capability in detecting thyroid carcinoma (TC) aggressiveness.MethodsSixty nude mice were randomly assigned to ATC and PTC groups and injected subcutaneously with KHM-5M and TPC-1 cell lines, respectively. Tumors were analyzed using B-mode ultrasound (B-US), Color Doppler flow imaging (CDFI), elastography, and contrast-enhanced ultrasound (CEUS). A logistic model integrating multimodal ultrasound data was constructed, and Ki-67 and CD31 expressions in tumor tissues were analyzed immunohistochemically. Correlations between ultrasound features and aggressiveness markers were investigated.ResultsThe ATC group exhibited significantly higher strain-elastography scores (p=0.009) and Adler grades in CDFI (p=0.045). CEUS revealed a higher frequency of heterogeneous enhancement (95.2% vs. 48.1%, p<0.001) and perfusion defects (90.5% vs. 63.0%, p<0.001) in ATC. Model area under the curve (AUC) values for distinguishing ATC from PTC were 0.963 for (B-US + CEUS), 0.926 for CEUS, 0.729 for elastography, 0.663 for CDFI, and 0.675 for B-US. The multimodal ultrasound model demonstrated significant correlations with Ki-67 (p<0.001) and microvessel density (MVD) (p<0.001).ConclusionsMultimodal ultrasound showing high efficacy with an AUC of 0.963 for B-US and CEUS combined in distinguishing ATC from PTC and exhibited strong associations with Ki-67 and MVD. Incorporating multimodal ultrasound, with an emphasis on CEUS, into active surveillance strategies for PTC is recommended. By providing detailed insights into tumor vascularity and aggressiveness, multimodal ultrasound could play a crucial role in early detection and treatment decision-making, improving patient outcomes.