基于MRI的影像组学与PI-RADS v2.1比较预测临床显著性前列腺癌：双参数vs多参数MR

【作者】 陈彤； 张志远； 檀双秀； 张跃跃； 魏超刚； 王珊； 赵文露； 钱旭升； 周志勇； 沈钧康； 戴亚康； 胡冀苏；

【机构】 苏州大学附属第二医院影像科； 徐州医科大学医学影像学院； 南京鼓楼医院超声科； 江苏江阴人民医院影像科； 中国科学院苏州生物医学工程技术研究所； 苏州大学生物医学工程学院生命科学与医学部； 苏州大学影像医学研究所；

【摘要】 目的:比较基于双参数磁共振成像(biparametric magnetic resonance imaging,bpMRI) vs多参数磁共振成像(multiparametric MRI,mpMRI)的影像组学与前列腺成像报告和数据系统(PI-RADS) v2.1评分系统在的临床显著性前列腺癌(csPCa)检测方面的价值。方法:收集2018年1月至2019年12月共204例经病理证实的患者,其中训练组142例,验证组62例。通过受试者操作特征(ROC)曲线分析,比较基于bpMRI和mpMRI的影像组学模型与PI-RADS v2.1诊断csPCa的效能分析。结果:基于bpMRI和mpMRI特征的影像组学模型预测价值较高,但两者之间无统计学差异(训练组AUC=0.975 vs 0.981,P=0.687;验证组为AUC=0.953 vs 0.968, P=0.287)。此外,无论是基于bpMRI(训练组AUC=0.975 vs.0.871, P=0.030;验证组AUC=0.953 vs.0.853,p=0.024)或mpMRI(训练组AUC=0.981vs.0.880,p=0.030;验证组AUC=0.968 vs.0.863, P=0.016)构建的预测模型,影像组学模型在csPCa诊断方面的表现均优于PI-RADS v2.1。结论:本研究表明,基于bpMRI和mpMRI的影像组学模型在诊断csPCa方面的性能并无显著差异,这表明在影像组学研究方法中省略DCE成像可以简化分析过程。此外,联合影像组学与PI-RADS v2.1可以提高PI-RADS v2.1预测csPCa的诊断效能。更多还原

【Abstract】 Objective To compare the performance of radiomics to that of the Prostate Imaging Reporting and Data System(PI-RADS) v2.1 scoring system in the detection of clinically significant prostate cancer(csPCa) based on biparametric magnetic resonance imaging(bpMRI) vs.multiparametric MRI(mpMRI).Methods A total of 204 patients with pathological results were enrolled between January 2018 and December 2019,with 142 patients in the training set and 62 patients in the testing set.The radiomics model was compared with the PI-RADS v2.1 for the diagnosis of csPCa based on bpMRI and mpMRI by using receiver operating characteristic(ROC) curve analysis.Results The radiomics model based on bpMRI and mpMRI signatures showed high predictive efficiency but with no significant differences(AUC = 0.975 vs 0.981,p=0.687 in the training cohort,and 0.953 vs 0.968,p=0.287 in the testing cohort,respectively).In addition,the radiomics model outperformed the PI-RADS v2.1 in the diagnosis of csPCa regardless of whether bpMRI(AUC = 0.975 vs.0.871,p= 0.030 for the training cohort and AUC = 0.953 vs.0.853,P =0.024 for the testing cohort) or mpMRI(AUC = 0.981 vs.0.880,p= 0.030 for the training cohort and AUC = 0.968vs.0.863,P = 0.016 for the testing cohort) was incorporated Conclusions Our study suggests the performance of bpMRIand mpMRI-based radiomics models show no significant difference,which indicates that omitting DCE imaging in radiomics can simplify the process of analysis.Adding radiomics to PI-RADS v2.1 may improve the performance to predict csPCa.更多还原