Dynamic Vascular Spatiotemporal Heterogeneity on Multiphase CT for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

IF 3.9 3区 医学 Q2 ONCOLOGY
Journal of Hepatocellular Carcinoma Pub Date : 2026-09-03 eCollection Date: 2026-01-01 DOI:10.2147/JHC.S632045
Shucheng Yang, Meng Liu, Yongjie Zhou, Jinhong Zhao, Yongming Tan, Weijia Wang
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引用次数: 0

Abstract

Purpose: Microvascular invasion (MVI) is an important determinant of postoperative recurrence in hepatocellular carcinoma (HCC) but is usually confirmed only after surgery. This study aimed to develop and externally validate a multiphase CT framework integrating dynamic vascular trajectory, spatial intratumoral heterogeneity, and deep imaging features for preoperative MVI prediction and exploratory prognostic stratification.

Patients and methods: This retrospective multicenter study included 405 patients with pathologically confirmed HCC: 198 in the development cohort and 207 in two independent external-validation cohorts. Clinical variables, static multiphase radiomics, Delta vascular trajectory features, three-dimensional intratumoral heterogeneity (3D-ITH)/habitat features, and Vision Transformer (ViT) features were extracted. All preprocessing, model fitting, and threshold selection were confined to the development cohort. A capacity-constrained multimodal Transformer was compared with clinical, single-modality, simple concatenation, and tree-based models.

Results: The cohort included 148 MVI-positive and 257 MVI-negative patients according to the locked blinded multireviewer reference standard. In pooled external validation, Transformer fusion achieved an area under the curve of 0.941 (95% CI, 0.906-0.969), sensitivity of 0.951, specificity of 0.754, accuracy of 0.831, negative predictive value of 0.960, and Brier score of 0.113. Corresponding AUCs were 0.957 and 0.934 in the two external cohorts. Delta-only and clinical models achieved pooled external AUCs of 0.793 and 0.675, respectively. High fusion-risk patients had poorer composite RFS/PFS than low-risk patients (hazard ratio, 2.05; 95% CI, 1.36-3.08; P < 0.001).

Conclusion: The proposed dynamic vascular heterogeneity-centered framework demonstrated high external discrimination for preoperative MVI prediction in HCC and provided exploratory stratification of the available composite RFS/PFS endpoint. Prospective validation and recalibration are required before clinical implementation.

多期CT动态血管时空异质性对肝细胞癌微血管侵袭的术前预测。
目的:微血管侵犯(MVI)是肝细胞癌(HCC)术后复发的重要决定因素,但通常只有在手术后才能证实。本研究旨在开发并外部验证一个整合动态血管轨迹、肿瘤内空间异质性和深部成像特征的多期CT框架,用于术前MVI预测和探索性预后分层。患者和方法:这项回顾性多中心研究包括405例病理证实的HCC患者:198例在发展队列中,207例在两个独立的外部验证队列中。提取临床变量、静态多相放射组学、三角洲血管轨迹特征、三维肿瘤内异质性(3D-ITH)/栖息地特征和视觉变形(ViT)特征。所有的预处理、模型拟合和阈值选择都局限于发展队列。将容量受限的多模态变压器与临床、单模态、简单串联和基于树的模型进行比较。结果:纳入mvi阳性患者148例,mvi阴性患者257例。在外部联合验证中,Transformer融合的曲线下面积为0.941 (95% CI, 0.906-0.969),敏感性为0.951,特异性为0.754,准确性为0.831,阴性预测值为0.960,Brier评分为0.113。两个外部队列对应的auc分别为0.957和0.934。仅delta模型和临床模型的合并外部auc分别为0.793和0.675。高融合风险患者的综合RFS/PFS较低风险患者差(风险比2.05;95% CI, 1.36-3.08; P < 0.001)。结论:提出的以动态血管异质性为中心的框架对HCC术前MVI预测具有较高的外部辨别力,并提供了可用的RFS/PFS复合终点的探索性分层。在临床应用前需要进行前瞻性验证和重新校准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.50
自引率
2.40%
发文量
108
审稿时长
16 weeks
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