评估基于CT的放射组学模型用于鉴别恶性胰管内乳头状黏液性肿瘤（IPMN），并与2017年国际共识指南（ICGs）进行比较。我们回顾性纳入了2008年1月至2020年12月期间接受胰腺IPMN手术切除的连续194名患者。外科组织病理学是诊断恶性的参考标准。利用术前增强CT的放射组学特征，通过五折交叉验证使用最小绝对收缩和选择算子建立了放射组学模型。CT和MR影像根据2017年ICGs由两名腹部放射科医师独立评估，并比较了2017年ICGs和放射组学模型的表现。使用DeLong方法比较了两者的曲线下面积（AUC）。共有194例胰腺IPMN患者（良性83例[43%]；恶性111例[57%]），按年代分为训练组（n=141；年龄65±8.6岁；男性88名）和验证组（n=53；年龄66±9.7岁；男性31名）。 CT和MRI的2017年ICGs无显著差异（AUC为0.71 vs. 0.71；p=0.93），并具有较好的介模式一致性（K为0.86）。在验证组中，CT放射组学模型的AUC（0.85 vs. 0.71；p=0.038）、特异度（84.6% vs. 61.5%；p=0.041）和阳性预测值（84.0% vs. 66.7%；p=0.044）均优于2017年ICGs。CT放射组学模型在分类恶性IPMN方面的诊断性能优于2017年ICGs。相比基于2017年国际共识指南的放射科医师评估，CT放射组学模型在分类恶性胰管内乳头状黏液性肿瘤方面表现出更好的诊断性能。2017年国际共识指南（ICGs）与放射组学模型在恶性胰管内乳头状黏液性肿瘤（IPMNs）方面进行的比较研究还较为匮乏。本研究中开发的CT放射组学模型在分类恶性IPMNs方面表现出更好的诊断性能。放射组学模型可能作为一种有价值的辅助工具，能够更加定量地评估IPMNs。©2023. 作者(们)独家授权欧洲放射学会使用。

To evaluate a CT-based radiomics model for identifying malignant pancreatic intraductal papillary mucinous neoplasms (IPMNs) and compare its performance with the 2017 international consensus guidelines (ICGs).We retrospectively included 194 consecutive patients who underwent surgical resection of pancreatic IPMNs between January 2008 and December 2020. Surgical histopathology was the reference standard for diagnosing malignancy. Using radiomics features from preoperative contrast-enhanced CT, a radiomics model was built with the least absolute shrinkage and selection operator by a five-fold cross-validation. CT and MR images were independently reviewed based on the 2017 ICGs by two abdominal radiologists, and the performances of the 2017 ICGs and radiomics model were compared. The areas under the curve (AUCs) were compared using the DeLong method.A total of 194 patients with pancreatic IPMNs (benign, 83 [43%]; malignant, 111 [57%]) were chronologically divided into training (n = 141; age, 65 ± 8.6 years; 88 males) and validation sets (n = 53; age, 66 ± 9.7 years; 31 males). There was no statistically significant difference in the diagnostic performance of the 2017 ICGs between CT and MRI (AUC, 0.71 vs. 0.71; p = 0.93) with excellent intermodality agreement (k = 0.86). In the validation set, the CT radiomics model had higher AUC (0.85 vs. 0.71; p = 0.038), specificity (84.6% vs. 61.5%; p = 0.041), and positive predictive value (84.0% vs. 66.7%; p = 0.044) than the 2017 ICGs.The CT radiomics model exhibited better diagnostic performance than the 2017 ICGs in classifying malignant IPMNs.Compared with the radiologists' evaluation based on the 2017 international consensus guidelines, the CT radiomics model exhibited better diagnostic performance in classifying malignant intraductal papillary mucinous neoplasms.• There is a paucity of comparisons between the 2017 international consensus guidelines (ICGs) and radiomics models for malignant intraductal papillary mucinous neoplasms (IPMNs). • The CT radiomics model developed in this study exhibited better diagnostic performance than the 2017 ICGs in classifying malignant IPMNs. • The radiomics model may serve as a valuable complementary tool to the 2017 ICGs, potentially allowing a more quantitative assessment of IPMNs.© 2023. The Author(s), under exclusive licence to European Society of Radiology.