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Updated: May 9, 2025
High-Resolution Ultrasonography for the Analysis of Orthotopic ATC Tumors in a Genetically Engineered Mouse Model
Published on: October 11, 2022
Preoperative prediction of Ki-67 expression in medullary thyroid carcinoma based on ultrasonographic features: a
Qianru Zhang1, Yan Hu1, Xiaoyan Chen2
1Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Purpose:
To identify ultrasonographic features that help distinguish Ki-67 expression levels in patients with medullary thyroid carcinoma (MTC).
Materials And Methods:
A total of 210 patients (245 nodules) with pathological diagnosis of MTC were included in this retrospective study between January 2013 and April 2024. Based on preoperative clinical and ultrasonographic features, univariate analysis and multivariate logistic regression analysis were performed to determine the risk factors associated with Ki-67 ≥ 5 %. A prediction model was subsequently established to evaluate the differential diagnostic performance of Ki-67 by the area under the curve (AUC).
Results:
Among the 210 MTC patients (245 nodules), 35 patients (41 nodules) exhibited high Ki-67 expression (Ki-67 ≥ 5 %), while 175 patients (204 nodules) had low Ki-67 expression (Ki-67 < 5 %). There were no significant differences in age, sex, body mass index (BMI), preoperative calcitonin and preoperative CEA levels between the two groups (P > 0.05). Multivariate analysis of the nodules in the two groups revealed that the ultrasound features, including location in the upper or middle region, tumor size > 2.15 cm, and markedly hypoechoic were independent risk factors for high Ki-67 expression. A prediction model was established with the AUC of 0.812 (95 % CI 0.743-0.882).
Conclusions:
Compared to the low Ki-67 expression group, Ki-67 ≥ 5 % group were more likely to exhibit the ultrasound characteristics of location in the upper or middle region, tumor size > 2.15 cm, and markedly hypoechoic. The prediction model demonstrated preferable diagnostic value.
