高级检索
当前位置: 首页 > 详情页

Preoperative Prediction of Microvascular Invasion in Patients With Hepatocellular Carcinoma Based on Radiomics Nomogram Using Contrast-Enhanced Ultrasound.

文献详情

资源类型:
Pubmed体系:
单位: [1]Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China, [2]Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, [3]Department of Artificial Intelligence, Julei Technology Company, Wuhan, China, [4]Department of Diagnostic Ultrasound, Xiang Ya Hospital, Central South University, Changsha, China, [5]Department of Internal Medicine, Hirslanden Clinic, Bern, Switzerland
出处:
ISSN:

关键词: microvascular invasion hepatocellular carcinoma contrast-enhanced ultrasound radiomics nomogram

摘要:
This study aimed to develop a radiomics nomogram based on contrast-enhanced ultrasound (CEUS) for preoperatively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.A retrospective dataset of 313 HCC patients who underwent CEUS between September 20, 2016 and March 20, 2020 was enrolled in our study. The study population was randomly grouped as a primary dataset of 192 patients and a validation dataset of 121 patients. Radiomics features were extracted from the B-mode (BM), artery phase (AP), portal venous phase (PVP), and delay phase (DP) images of preoperatively acquired CEUS of each patient. After feature selection, the BM, AP, PVP, and DP radiomics scores (Rad-score) were constructed from the primary dataset. The four radiomics scores and clinical factors were used for multivariate logistic regression analysis, and a radiomics nomogram was then developed. We also built a preoperative clinical prediction model for comparison. The performance of the radiomics nomogram was evaluated via calibration, discrimination, and clinical usefulness.Multivariate analysis indicated that the PVP and DP Rad-score, tumor size, and AFP (alpha-fetoprotein) level were independent risk predictors associated with MVI. The radiomics nomogram incorporating these four predictors revealed a superior discrimination to the clinical model (based on tumor size and AFP level) in the primary dataset (AUC: 0.849 vs. 0.690; p < 0.001) and validation dataset (AUC: 0.788 vs. 0.661; p = 0.008), with a good calibration. Decision curve analysis also confirmed that the radiomics nomogram was clinically useful. Furthermore, the significant improvement of net reclassification index (NRI) and integrated discriminatory improvement (IDI) implied that the PVP and DP radiomics signatures may be very useful biomarkers for MVI prediction in HCC.The CEUS-based radiomics nomogram showed a favorable predictive value for the preoperative identification of MVI in HCC patients and could guide a more appropriate surgical planning.Copyright © 2021 Zhang, Wei, Wu, Zhang, Lu, Lv, Liao, Cui, Ni and Dietrich.

语种:
PubmedID:
中科院(CAS)分区:
出版当年[2020]版:
大类 | 2 区 医学
小类 | 3 区 肿瘤学
最新[2025]版:
大类 | 3 区 医学
小类 | 4 区 肿瘤学
第一作者:
第一作者单位: [1]Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China,
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:426 今日访问量:0 总访问量:408 更新日期:2025-04-01 建议使用谷歌、火狐浏览器 常见问题

版权所有:重庆聚合科技有限公司 渝ICP备12007440号-3 地址:重庆市两江新区泰山大道西段8号坤恩国际商务中心16层(401121)