高级检索
当前位置: 首页 > 详情页

Radiomics Based on Contrast-Enhanced MRI in Differentiation Between Fat-Poor Angiomyolipoma and Hepatocellular Carcinoma in Noncirrhotic Liver: A Multicenter Analysis

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE

机构: [1]Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China [2]Medical Imaging Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China [3]Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, China [4]AI Lab, Deepwise Healthcare, Beijing, China, 5 Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
出处:
ISSN:

关键词: hepatocellular carcinoma angiomyolipoma radiomics magnetic resonance imaging machine learning

摘要:
Objective This study aims to develop and externally validate a contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics-based model for preoperative differentiation between fat-poor angiomyolipoma (fp-AML) and hepatocellular carcinoma (HCC) in patients with noncirrhotic livers and to compare the diagnostic performance with that of two radiologists.</p> Methods This retrospective study was performed with 165 patients with noncirrhotic livers from three medical centers. The dataset was divided into a training cohort (n = 99), a time-independent internal validation cohort (n = 24) from one center, and an external validation cohort (n = 42) from the remaining two centers. The volumes of interest were contoured on the arterial phase (AP) images and then registered to the venous phase (VP) and delayed phase (DP), and a total of 3,396 radiomics features were extracted from the three phases. After the joint mutual information maximization feature selection procedure, four radiomics logistic regression classifiers, including the AP model, VP model, DP model, and combined model, were built. The area under the receiver operating characteristic curve (AUC), diagnostic accuracy, sensitivity, and specificity of each radiomics model and those of two radiologists were evaluated and compared.</p> Results The AUCs of the combined model reached 0.789 (95%CI, 0.579-0.999) in the internal validation cohort and 0.730 (95%CI, 0.563-0.896) in the external validation cohort, higher than the AP model (AUCs, 0.711 and 0.638) and significantly higher than the VP model (AUCs, 0.594 and 0.610) and the DP model (AUCs, 0.547 and 0.538). The diagnostic accuracy, sensitivity, and specificity of the combined model were 0.708, 0.625, and 0.750 in the internal validation cohort and 0.619, 0.786, and 0.536 in the external validation cohort, respectively. The AUCs for the two radiologists were 0.656 and 0.594 in the internal validation cohort and 0.643 and 0.500 in the external validation cohort. The AUCs of the combined model surpassed those of the two radiologists and were significantly higher than that of the junior one in both validation cohorts.</p> Conclusions The proposed radiomics model based on triple-phase CE-MRI images was proven to be useful for differentiating between fp-AML and HCC and yielded comparable or better performance than two radiologists in different centers, with different scanners and different scanning parameters.</p>

基金:
语种:
WOS:
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
JCR分区:
出版当年[2019]版:
Q2 ONCOLOGY
最新[2023]版:
Q2 ONCOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2019版] 出版当年五年平均 出版前一年[2018版] 出版后一年[2020版]

第一作者:
第一作者机构: [1]Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
共同第一作者:
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:2018 今日访问量:0 总访问量:645 更新日期:2024-07-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 广东省中医院 技术支持:重庆聚合科技有限公司 地址:广州市越秀区大德路111号