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多模式CT用于预测单独cHCC-CCA中的微血管入侵:双中心外部验证

Wu-Yuan Liu¹, Yu-Chen Wei², Qiao-Fang Chen³

¹Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China (W.-Y.L.,Y.-C.W., Q.-F.C., Y.-F.T., L.C., J.-Y.L.); Department of Radiology, People's Hospital of Luchuan, Yulin, Guangxi, China (W.-Y.L.).

Academic radiology

|February 21, 2026

概括

一个新的多式CT模型准确地预测了手术前在联合肝细胞胆管癌 (cHCC-CCA) 中的微血管入侵 (MVI). 该模型结合了定量和语义CT特征,显示了改善患者风险分层的希望.

科学领域:

放射学和成像学放射学和成像学
在瘤学瘤学.
肝胆道手术肝胆道手术

背景情况:

在联合肝细胞胆管癌 (cHCC-CCA) 中进行微血管侵袭 (MVI) 的术前预测是具有挑战性的.
在cHCC-CCA中用于MVI预测的基于外部验证的计算机断层扫描 (CT) 工具很少.

研究的目的:

开发和外部验证用于单独cHCC-CCA中MVI预测的多模式CT模型.
为了比较MVI预测的内,周和联合细分策略.

主要方法:

在184名单独cHCC-CCA.患者的回顾性双中心研究中.
使用门静脉相定量CT特征和多相CT语义特征开发多模式模型.
使用单独的队列进行外部验证,通过AUC,校准和SHAP分析评估性能.

主要成果:

多模式CT模型在外部验证中实现了跨细分策略的中度和一致的歧视 (AUC,0.761-0.800).
10毫米周围瘤细分策略显示了数值上最高的AUC (0.800) 和高灵敏度.
SHAP分析确定了边缘动脉阶段超增强和扩大周边增强作为MVI的关键预测因子.

结论:

多模式CT方法为单独的cHCC-CCA提供外部验证的手术前MVI风险估计.
周围瘤建模在MVI预测方面表现出适度的优势,尽管在统计学上并不优越.
建议进行未来的多中心验证,以确认该模型作为决策支持工具的实用性.

关键词:

这就是CHCC-CCA.深度学习是一种深度学习.微血管侵袭是一种微血管侵袭.周口细分是指周口细分.无线电学 (Radiomics) 是一种辐射学.

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