Multiparametric MRI radiomics predicts overall survival in hepatocellular carcinoma.

IF 1.1 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Tong Zhang, Jialiang Ren, Hui Wu, Yang Gao, He Hu, Yushan Jia, Wenjia Wang
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引用次数: 0

Abstract

BackgroundThe prognosis for hepatocellular carcinoma (HCC) is unfavorable, primarily attributable to the high incidence of recurrence.PurposeTo assess the prognostic value of multiparametric magnetic resonance imaging (mp-MRI) based on radiomic features for overall survival (OS) in patients with HCC.Material and MethodsPatients who underwent abdominal mp-MRI examination before hepatectomy in our hospital between January 2016 and December 2019 were retrospectively collected and divided into a training group and a verification group at a ratio of 7:3. The patients' images, clinical parameters, and semantic features were collected. A three-dimensional volume of interest was delineated and radiomics features were screened. Independent predictors of clinical imaging were screened and combined with radiomics features to construct a combinatorial model and draw a nomogram. The predictive efficacy of the model was evaluated.ResultsThe Harrell's C-index values were 0.737 and 0.711 for the clinical imaging model and 0.705 and 0.704 for the full sequence model in the training group and validation group, respectively. The combinatorial model had higher efficiency, and the C-index values in the training group and the validation group were 0.779 and 0.756, respectively. The survival curve showed that the low-risk group defined by the radiomics signature had significantly better OS than the high-risk group (3-year OS: 61.54% vs. 30.77%; P < 0.05).ConclusionThe combined model can predict the OS of patients with HCC non-invasively before surgical resection and can be used as a clinical tool to guide individualized treatment.

多参数MRI放射组学预测肝细胞癌的总生存期。
背景:肝细胞癌(HCC)预后不良,主要是由于其高复发率。目的探讨基于放射学特征的多参数磁共振成像(mp-MRI)对HCC患者总生存期(OS)的预后价值。材料与方法回顾性收集2016年1月至2019年12月在我院肝切除术前行腹部mp-MRI检查的患者,按7:3的比例分为训练组和验证组。收集患者的图像、临床参数和语义特征。勾画出感兴趣的三维体积,并筛选放射组学特征。筛选独立的临床影像学预测因子并结合放射组学特征构建组合模型并绘制nomogram。评估模型的预测效果。结果训练组和验证组临床影像学模型的Harrell’s C-index值分别为0.737和0.711,全序列模型的Harrell’s C-index值分别为0.705和0.704。组合模型效率更高,训练组和验证组的c指数值分别为0.779和0.756。生存曲线显示,放射组学特征定义的低危组的OS明显优于高危组(3年OS: 61.54% vs. 30.77%;P
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
Acta radiologica
Acta radiologica 医学-核医学
CiteScore
2.70
自引率
0.00%
发文量
170
审稿时长
3-8 weeks
期刊介绍: Acta Radiologica publishes articles on all aspects of radiology, from clinical radiology to experimental work. It is known for articles based on experimental work and contrast media research, giving priority to scientific original papers. The distinguished international editorial board also invite review articles, short communications and technical and instrumental notes.
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