CD31-associated vascular phenotyping using Doppler ultrasound and dual-energy CT for recurrence risk stratification in papillary thyroid cancer

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Authors: Yan Zhou, Feng Xu, Yu Hu, Xiao Li, Yan Si, Guoyi Su, Wu, Feiyun, Xu, Xiaoquan
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Abstract

Abstract Background Angiogenesis plays a pivotal role in PTC aggressiveness and recurrence. CD31, an endothelial marker, provides a histological correlate of tumor vascularity. This study aimed to establish a multimodal imaging framework using Doppler ultrasound (US) and dual-energy CT (DECT) to capture CD31-associated vascular phenotypes for recurrence risk stratification. Methods A total of 414 PTC patients (training set, 151; test set 1, 137; test set 2, 126) were included. Clinical and radiographic features, including demographics, tumor morphology, Doppler US grade, US grayscale values, and DECT parameters, were analyzed. CD31 expression was assessed by immunohistochemistry in the training set and served as a reference for vascular phenotyping. Logistic regression was applied to identify imaging-derived vascular signatures linked to CD31 expression. Recurrence-free survival (RFS) was analyzed across all datasets to evaluate prognostic value. Results High CD31 expression correlated with advanced tumor stage (p = 0.003), lymph node metastasis (p = 0.001), extrathyroidal extension (p < 0.001), and recurrence (p < 0.001). The vascular phenotype model integrating Doppler US grade, unenhanced electron density (ED), arterial-phase iodine concentration (IC), and venous-phase IC/ED ratio achieved an AUC of 0.815 (95% CI: 0.744–0.874) for discriminating CD31 expression in the training set. This imaging-derived phenotype was significantly associated with RFS in the training set (p = 0.017), test set 1 (p = 0.006), and test set 2 (p = 0.002), effectively identifying patients at higher risk of recurrence. Conclusion Preoperative vascular phenotyping with Doppler US and DECT enables noninvasive assessment of CD31-associated angiogenic activity and enhances recurrence risk stratification in PTC.

Fields of Study & Subjects

Thyroid Cancer Diagnosis and Treatment Radiomics and Machine Learning in Medical Imaging Thyroid and Parathyroid Surgery

Publication details

Journal / source
Figshare
Publication date
1 January 2026