Diagnostic performance based on MRI for preoperative of vessels encapsulating tumor clusters in hepatocellular carcinoma: a systematic review and meta-analysis.

IF 4.8 1区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Miaomiao Wang, Yinzhong Wang, Liang Cao, Qian Wang, Ya Shen, Xiaoxue Tian, Junqiang Lei
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引用次数: 0

Abstract

Objective: Vessels encapsulating tumor clusters (VETC) pattern is a unique pattern of vascular invasion that has been shown to be a poor prognostic factor for hepatocellular carcinoma (HCC). The purpose of this review and meta-analysis was to explore diagnostic performance between non-radiomics and radiomics model based on MRI for preoperative of vessels encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC).

Methods: All included articles were obtained from PubMed, Embase, Web of Science and Cochrane library as of September 30, 2024. The QUADAS-2 tool was used to assess methodological quality of eligible studies. The pooled data was using a mixed effects model within a 95% confidence interval (CI). Diagnostic performance was represented by summary receiver-operating characteristic curves and the area under the curve (AUC).

Results: A total of 14 studies (10 non-radiomics and 6 radiomics) with 2961 HCC patients were included in this study. The pooled sensitivity and specificity of non radiomics model were 0.80 (95%CI:0.76-0.83) and 0.74(95%CI:0.69-0.78), with AUC of 0.84 (95%CI:0.80-0.87); whereas that of radiomics model was 0.88 (95%CI:0.83- 0.91) and 0.86 (95%CI:0.81-0.90) with AUC of 0.93 (95%CI:0.91-0.95).

Conclusions: Radiomics model performed better than non-radiomics model based on MRI in preoperative prediction of VETC-positive HCC, but there was heterogeneity between studies, which needs to be interpreted with caution.

基于MRI对肝细胞癌术前血管包覆肿瘤簇的诊断效果:系统回顾和荟萃分析。
目的:血管包裹肿瘤簇(VETC)模式是一种独特的血管侵犯模式,已被证明是肝细胞癌(HCC)预后不良的因素。本综述和荟萃分析的目的是探讨基于MRI的非放射组学模型和放射组学模型在肝细胞癌(HCC)血管包膜肿瘤簇(VETC)术前的诊断性能。方法:所有纳入的文章均于2024年9月30日从PubMed、Embase、Web of Science和Cochrane图书馆获取。使用QUADAS-2工具评估符合条件的研究的方法学质量。合并数据采用95%置信区间(CI)内的混合效应模型。诊断效能由患者工作特征曲线和曲线下面积(AUC)表示。结果:本研究共纳入14项研究(10项非放射组学研究和6项放射组学研究),共2961例HCC患者。非放射组学模型的合并敏感性和特异性分别为0.80 (95%CI:0.76-0.83)和0.74(95%CI:0.69-0.78), AUC为0.84 (95%CI:0.80-0.87);放射组学模型的AUC分别为0.88 (95%CI:0.83 ~ 0.91)和0.86 (95%CI:0.81 ~ 0.90), AUC为0.93 (95%CI:0.91 ~ 0.95)。结论:放射组学模型对vetc阳性HCC的术前预测优于基于MRI的非放射组学模型,但各研究之间存在异质性,需谨慎解读。
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
Radiologia Medica
Radiologia Medica 医学-核医学
CiteScore
14.10
自引率
7.90%
发文量
133
审稿时长
4-8 weeks
期刊介绍: Felice Perussia founded La radiologia medica in 1914. It is a peer-reviewed journal and serves as the official journal of the Italian Society of Medical and Interventional Radiology (SIRM). The primary purpose of the journal is to disseminate information related to Radiology, especially advancements in diagnostic imaging and related disciplines. La radiologia medica welcomes original research on both fundamental and clinical aspects of modern radiology, with a particular focus on diagnostic and interventional imaging techniques. It also covers topics such as radiotherapy, nuclear medicine, radiobiology, health physics, and artificial intelligence in the context of clinical implications. The journal includes various types of contributions such as original articles, review articles, editorials, short reports, and letters to the editor. With an esteemed Editorial Board and a selection of insightful reports, the journal is an indispensable resource for radiologists and professionals in related fields. Ultimately, La radiologia medica aims to serve as a platform for international collaboration and knowledge sharing within the radiological community.
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