A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma

列线图 医学 肝内胆管癌 无线电技术 放射科 内科学 肿瘤科
作者
Xianling Qian,Xin Lu,Xijuan Ma,Ying Zhang,Changwu Zhou,Fang Wang,Yibing Shi,Mengsu Zeng
出处
期刊:Frontiers in Oncology [Frontiers Media]
卷期号:12: 838701-838701 被引量:30
标识
DOI:10.3389/fonc.2022.838701
摘要

Background Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer with increasing incidence in the last decades. Microvascular invasion (MVI) is a poor prognostic factor for patients with ICC, which correlates early recurrence and poor prognosis, and it can affect the selection of personalized therapeutic regime. Purpose This study aimed to develop and validate a radiomics-based nomogram for predicting MVI in ICC patients preoperatively. Methods A total of 163 pathologically confirmed ICC patients (training cohort: n = 130; validation cohort: n = 33) with postoperative Ga-DTPA-enhanced MR examination were enrolled, and a time-independent test cohort ( n = 24) was collected for external validation. Univariate and multivariate analyses were used to determine the independent predictors of MVI status, which were then incorporated into the MVI prediction nomogram. Least absolute shrinkage and selection operator logistic regression was performed to select optimal features and construct radiomics models. The prediction performances of models were assessed by receiver operating characteristic (ROC) curve analysis. The performance of the MVI prediction nomogram was evaluated by its calibration, discrimination, and clinical utility. Results Larger tumor size ( p = 0.003) and intrahepatic duct dilatation ( p = 0.002) are independent predictors of MVI. The final radiomics model shows desirable and stable prediction performance in the training cohort (AUC = 0.950), validation cohort (AUC = 0.883), and test cohort (AUC = 0.812). The MVI prediction nomogram incorporates tumor size, intrahepatic duct dilatation, and the final radiomics model and achieves excellent predictive efficacy in training cohort (AUC = 0.953), validation cohort (AUC = 0.861), and test cohort (AUC = 0.819), fitting well in calibration curves ( p > 0.05). Decision curve and clinical impact curve further confirm the clinical usefulness of the nomogram. Conclusion The nomogram incorporating tumor size, intrahepatic duct dilatation, and the final radiomics model is a potential biomarker for preoperative prediction of the MVI status in ICC patients.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
2秒前
Jasper应助zzzzza采纳,获得10
2秒前
gy完成签到,获得积分20
3秒前
沭阳检验医师完成签到,获得积分0
5秒前
海猫食堂发布了新的文献求助10
5秒前
高贵的乐枫完成签到,获得积分10
5秒前
5秒前
6秒前
6秒前
6秒前
等待的茉莉完成签到,获得积分10
6秒前
tsd完成签到,获得积分10
7秒前
王佳鑫完成签到,获得积分10
7秒前
Jenny完成签到 ,获得积分10
7秒前
10秒前
10秒前
10秒前
佰斯特威完成签到,获得积分10
10秒前
11秒前
momo发布了新的文献求助10
11秒前
kokoro完成签到,获得积分10
12秒前
wang完成签到,获得积分10
12秒前
ranranran发布了新的文献求助10
13秒前
Akim应助岁月轻狂采纳,获得10
13秒前
XIAO关注了科研通微信公众号
13秒前
13秒前
Jianwen发布了新的文献求助10
15秒前
15秒前
NexusExplorer应助SHENYANG采纳,获得10
17秒前
wilapple发布了新的文献求助10
17秒前
愉快的真发布了新的文献求助10
17秒前
19秒前
jiang发布了新的文献求助10
20秒前
多情嫣然发布了新的文献求助10
21秒前
哭泣忆文完成签到,获得积分10
22秒前
22秒前
丘比特应助芙芙采纳,获得10
24秒前
优雅冰淇淋完成签到,获得积分10
25秒前
高言完成签到,获得积分10
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Introducing the Learning Sciences 600
Resiliency Scale for Adolescents--Chinese Version 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7321958
求助须知:如何正确求助?哪些是违规求助? 8937420
关于积分的说明 18948273
捐赠科研通 6979861
什么是DOI,文献DOI怎么找? 3214847
关于科研通互助平台的介绍 2382446
邀请新用户注册赠送积分活动 2194115