磁共振结合临床指标对优化O-RADS MRI 4分肿块风险分层的价值  

Value of MRI combining with clinical indicators in optimizing the risk stratification of O-RADS MRI Score 4

作　　者：李彩红 李易[1] 刘柳[1] 周印 杨雅莹 毛芸[1] LI Caihong;LI Yi;LIU Liu;ZHOU Yin;YANG Yaying;MAO Yun(Department of Radiology,the First Hospital of Chongqing Medical University,Chongqing 400016,China;Department of Pathology,Faculty of Basic Medicine,Chongqing Medical University,Chongqing 400016,China;Pathology Diagnostic Center,Chongqing Medical University,Chongqing 400016,China;Clinical Pathology Research Laboratory,Chongqing Medical University,Chongqing 400016,China;Department of Pathology,the First Hospital of Chongqing Medical University,Chongqing 400016,China)

机构地区：[1]重庆医科大学附属第一医院放射科,重庆400016 [2]重庆医科大学基础医学院病理学教研室,重庆400016 [3]重庆医科大学病理诊断中心,重庆400016 [4]重庆医科大学临床病理研究室,重庆400016 [5]重庆医科大学附属第一医院病理科,重庆400016

出　　处：《磁共振成像》2024年第11期103-109,共7页Chinese Journal of Magnetic Resonance Imaging

摘　　要：目的探讨MRI特征联合临床指标[糖类抗原125(carbohydrate antigen 125,CA125)、绝经状态、年龄]对优化卵巢-附件影像报告和数据系统(Ovarian-Adnexal Reporting and Data System,O-RADS)MRI评分4分肿块风险分层的价值,并评估能否提高O-RADS MRI评分系统诊断性能。材料与方法回顾性纳入57例进行术前盆腔MRI增强检查并经组织病理学证实的卵巢-附件肿块患者的影像及临床资料,所有肿块的O-RADS MRI评分均为4分,由两名经验丰富的放射科医师评估得出,结果不一致时协商决定。以病理结果为金标准,对O-RADS MRI 4分肿块良、恶性组的MRI和临床指标进行差异性分析,将有差异统计学意义的指标利用分类与回归决策树(classification and regression tree,CART)构建模型,用于进一步细分4分肿块。绘制受试者工作特征(receiver operating characteristic,ROC)曲线评价决策树模型的预测准确性。分别评估优化4分肿块前后O-RADS MRI评分系统的诊断性能,并比较两者的曲线下面积(area under the curve,AUC)。计算不同经验水平阅片者之间优化后预测结果的一致性。结果(1)57例O-RADS MRI 4分肿块中,良性22例,恶性35例。实性组织T2WI低信号常见于良性肿块(P<0.001)。乳头状突起和不规则增厚的囊壁/分隔常见于恶性肿块(P<0.001,P=0.008)。CA125>35 U/mL多见于恶性肿块(P<0.05)。决策树模型预测4分肿块良恶性的AUC为0.984(95%CI:0.908~1.000),敏感度97.1%、特异度90.9%、准确度94.7%。(2)应用决策树模型对4分肿块优化后,在整个人群中,O-RADS MRI评分系统的AUC从0.838提升至0.945(P<0.001);在绝经前妇女中,AUC从0.818提升至0.934(P<0.001);在绝经后妇女中,AUC从0.871提升至0.962(P=0.008)。不同经验水平医师之间的优化后预测结果一致性极好(Kappa值分别为0.887、0.869)。结论在本研究中,基于实性组织MRI特征联合临床指标CA125开发的预测模型有助于优化O-RADS MRI 4分肿块风险分层,并�Objective:To investigate the value of MRI characteristics combined with clinical indicators[carbohydrate antigen 125(CA125),menopausal status,age]in optimizing the Ovarian-Adnexal Reporting and Data System(O-RADS)MRI score 4 mass risk stratification and whether it can improve the diagnostic performance of the O-RADS MRI scoring system.Materials and Methods:Totally 57 ovarian adnexal masses scored 4 according to O-RADS MRI were retrospectively analyzed.All masses underwent preoperative pelvic MRI enhancement imaging and were confirmed by histopathology.They were evaluated by two experienced radiologists and determined through consultation when the results were inconsistent.The pathological results were used as the gold standard to analyze the differences of MRI and clinical indicators in the O-RADS MRI score 4 group of benign and malignant masses.The classification and regression tree(CART)was employed to construct a model for statistically significant indicators for the further subdivision of the O-RADS MRI 4 mass.Receiver operating characteristic(ROC)analysis was used to evaluate the prediction accuracy of the decision tree model.To evaluate the diagnostic effect of O-RADS MRI scoring system before and after O-RADS MRI score 4 mass optimization,and compare the difference of area under the curve(AUC).The consistency of the optimized prediction results among different viewers was calculated.Results:(1)Among 57 O-RADS MRI score 4 masses,22 masses were benign,and 35 masses were malignant.Solid tissue showed hypointense on T2WI was more common in benign mass well(P<0.001).Papillary projections and irregularly thickened cyst wall or septations were more frequent in malignant mass(P<0.001,P=0.008).The CA125 level in malignant mass was often greater than 35 U/mL(P<0.05).The AUC of the decision tree model for predicting benign and malignant tumors was 0.984(95%CI:0.908-1.000),with a sensitivity of 97.1%,specificity of 90.9%and accuracy of 94.7%.(2)The AUC of the O-RADS MRI scoring system increased from 0.838 to 0.945(P<0

关 键 词：卵巢-附件肿块 卵巢-附件报告和数据系统 良恶性病变 鉴别诊断 磁共振成像 

分 类 号：R445.2[医药卫生—影像医学与核医学] R737.31[医药卫生—诊断学]