Predicting cervical lymph node metastasis in papillary thyroid carcinoma using capsule disruption length measured by 3D-US.

Liu, Ruyu; Jiang, Yuxin; Lai, Xingjian; Wang, Ying; Gao, Luying; Zhao, Ruina; Xi, Xuehua; Zhang, Bo · Eur Radiol · 2026

prospective_cohort · Level II

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Abstract

Papillary thyroid carcinoma (PTC) is a prevalent endocrine malignancy with a propensity for lymph node metastasis (LNM). Extrathyroidal extension (ETE) is a key factor in preoperative LNM prediction. The criteria for ultrasound diagnosis of ETE remain controversial. The aim is to determine if the length of capsule disruption (LCD) on three-dimensional ultrasound (3D-US) can predict cervical LNM in PTC patients. A prospective cohort of 168 patients from Peking Union Medical College Hospital was examined by 3D-US. The LCD was measured using the omniview mode of 3D-US. Statistical analyses included Chi-square tests, T-tests, Mann-Whitney tests, ROC curve analysis, and logistic regression analysis. Of the 126 patients included, 71 had LNM. Younger age, male gender, larger malignant nodules, LCD, echogenic foci, and thyroid capsule invasion were significantly associated with LNM. LCD ≥ 0.42 cm increases LNM risk by 4.097 (p < 0.001). A nomogram was constructed incorporating gender, age, maximum diameter of the largest malignant nodule (MDLM), and LCD to estimate the risk of LNM. The accuracy and AUC of the nomogram were 73.0% and 0.795 (0.718-0.873). LCD on 3D-US is a significant predictor of cervical LNM in PTC patients. This study's nomogram, based on easily measurable parameters, can help in the preoperative assessment of LNM risk, potentially guiding surgical management. Question Can the LCD measured by 3D-US predict cervical LNM in PTC? Findings LCD ≥ 0.42 cm on 3D-US increase LNM risk by 4.097-fold. The nomogram with LCD, gender, age, and nodule size shows good predictive ability (AUC = 0.795). Clinical relevance LCD is a promising predictor of LNM, an alternative to ultrasound thyroid capsule invasion evaluation. The nomogram enables risk-adapted surgery, reducing unnecessary dissection or missed metastases to improve patient outcomes.

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