Predicting multigenic co-mutations in differentiated thyroid cancer using contrast-enhanced ultrasonography: model development and internal validation.
IF 2.5 3区 医学Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Wenxin Xu, Haishan Lin, Jingliang Ruan, Yuxuan Hu, Xi Huang, Haolin Qiu, Baoming Luo
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引用次数: 0
Abstract
Purpose: This study aimed to analyze the ultrasonographic characteristics of differentiated thyroid cancer (DTC) with multigenic co-mutations and to establish a predictive model using contrast-enhanced ultrasonography (CEUS).
Methods: This retrospective study included consecutive patients with pathologically confirmed DTC who underwent preoperative CEUS and next-generation sequencing at the authors' institution between September 2021 and December 2023. Clinical and CEUS features were compared between patients with and without multigenic co-mutations. Bayesian logistic regression (non-informative normal priors) was applied for predictor selection and model development, with Markov-chain Monte Carlo (MCMC) convergence checks and posterior predictive validation. Internal validation was performed using bootstrap resampling (n=1,000 iterations) to evaluate model stability.
Results: A total of 116 patients (mean age, 39.84±11.02 years; 33 men) were included, of whom 12 had multigenic co-mutations and 104 did not. Patients with multigenic co-mutations demonstrated a higher incidence of aggressive histological subtypes (25.0% vs. 1.9%, P=0.008) and lymph node metastasis (83.3% vs. 51.9%, P=0.038). Tumor size, enhancement homogeneity, and contrast agent arrival time were identified as significant predictors, with robust posterior distributions (all inclusion probabilities >0.9) and satisfactory MCMC convergence (potential scale reduction factor <1.01). The model achieved an area under the curve (AUC) of 0.873, with posterior predictive checks confirming favorable predicted-observed agreement (coverage ≥0.85). Internal validation with 1,000 bootstrap replicates yielded a consistent AUC of 0.880 (95% confidence interval, 0.745 to 0.978).
Conclusion: The CEUS-based predictive model demonstrated strong discrimination for detecting multigenic co-mutations in differentiated thyroid cancer; however, external validation is required to confirm its clinical applicability.
目的:分析多基因共突变分化型甲状腺癌(DTC)的超声特征,并建立超声造影(CEUS)预测模型。方法:本回顾性研究纳入了2021年9月至2023年12月期间在作者所在机构接受术前超声造影和下一代测序的连续病理证实的DTC患者。比较有多基因共突变和无多基因共突变患者的临床和超声造影特征。采用贝叶斯逻辑回归(非信息正态先验)进行预测器选择和模型开发,并进行马尔可夫链蒙特卡罗(MCMC)收敛性检查和后验预测验证。内部验证使用bootstrap重新采样(n= 1000次迭代)来评估模型的稳定性。结果:共纳入116例患者(平均年龄39.84±11.02岁,男性33例),其中多基因共突变12例,无多基因共突变104例。多基因共突变患者侵袭性组织学亚型(25.0% vs. 1.9%, P=0.008)和淋巴结转移(83.3% vs. 51.9%, P=0.038)的发生率更高。肿瘤大小、增强均匀性和造影剂到达时间被认为是重要的预测因素,具有稳健的后验分布(所有包含概率>;0.9)和令人满意的MCMC收敛(潜在尺度缩小因子<;1.01)。该模型的曲线下面积(AUC)为0.873,后验预测检验证实了良好的预测-观测一致性(覆盖率≥0.85)。1,000次bootstrap重复的内部验证得出一致的AUC为0.880(95%置信区间为0.745至0.978)。结论:基于cev的预测模型对分化型甲状腺癌的多基因共突变检测具有较强的鉴别能力;然而,需要外部验证来确认其临床适用性。
UltrasonographyMedicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.10
自引率
6.50%
发文量
78
审稿时长
15 weeks
期刊介绍:
Ultrasonography, the official English-language journal of the Korean Society of Ultrasound in Medicine (KSUM), is an international peer-reviewed academic journal dedicated to practice, research, technology, and education dealing with medical ultrasound. It is renamed from the Journal of Korean Society of Ultrasound in Medicine in January 2014, and published four times per year: January 1, April 1, July 1, and October 1. Original articles, technical notes, topical reviews, perspectives, pictorial essays, and timely editorial materials are published in Ultrasonography covering state-of-the-art content.
Ultrasonography aims to provide updated information on new diagnostic concepts and technical developments, including experimental animal studies using new equipment in addition to well-designed reviews of contemporary issues in patient care. Along with running KSUM Open, the annual international congress of KSUM, Ultrasonography also serves as a medium for cooperation among physicians and specialists from around the world who are focusing on various ultrasound technology and disease problems and relevant basic science.