通过决策树分析建立一种非侵入性的肝内肿瘤形成型胆管癌(IMCC)的诊断系统。共有1008例病人纳入回顾性研究，包括504例病理学上证实的IMCC、肝细胞癌(HCC)和混合型肝细胞性胆管癌(cHCC-CC)（内部队列n=700，外部队列n=308）。应用单变量和多变量逻辑回归分析评估IMCC的独立临床和MRI预测因子，并将选定的特征用于开发基于决策树的诊断系统。通过接收者操作特性曲线分析计算建立的系统在内部训练-测试队列和外部验证队列中的诊断效能，以及≤3cm的小病变。多变量分析显示，女性、无慢性肝病或肝硬化、升高的19-9糖类抗原（CA19-9）水平、正常的α-胎蛋白（AFP）水平、分叶状肿瘤形态、逐渐增强或持续增强模式、无强化的肿瘤包膜、目标样表现和肝表面内缩对IMCC诊断有利于HCC或cHCC-CC (患病比=3.273-25.00，p <0.001至p = 0.021)。其中增强模式的权重最高为0.816。“诊断系统”结合上述重要特征在内部训练（曲线下面积(AUC) 0.971）、内部测试（AUC 0.956）和外部验证（AUC 0.945）队列以及≤3cm的小病变（AUC 0.956）中表现出极佳的性能。考虑到多中心的普遍适用性和临床效能，提出的诊断系统可能作为一个非侵入性、可靠和易操作的工具在IMCC诊断中发挥作用，为区分IMCC与其他含有HCC的原发性肝癌提供了一种高效的方法。本研究建立了一种非侵入性、易于操作和可解释的基于决策树的肝内肿瘤形成型胆管癌诊断系统，为临床决策提供了重要信息。• 区分肝内肿瘤形成型胆管癌(IMCC)与其他原发性肝癌对于治疗计划和预后预测非常重要。• 基于MRI的诊断系统在IMCC的诊断和鉴别上表现出出色的性能。• 该诊断系统可能作为一种非侵入性、易于操作和可解释的工具，在IMCC的诊断和风险分层中发挥作用。© 2023.作者(们)独家许可欧洲放射学学会。

To establish a non-invasive diagnostic system for intrahepatic mass-forming cholangiocarcinoma (IMCC) via decision tree analysis.Totally 1008 patients with 504 pathologically confirmed IMCCs and proportional hepatocellular carcinomas (HCC) and combined hepatocellular cholangiocarcinomas (cHCC-CC) from multi-centers were retrospectively included (internal cohort n = 700, external cohort n = 308). Univariate and multivariate logistic regression analyses were applied to evaluate the independent clinical and MRI predictors for IMCC, and the selected features were used to develop a decision tree-based diagnostic system. Diagnostic efficacy of the established system was calculated by the receiver operating characteristic curve analysis in the internal training-testing and external validation cohorts, and also in small lesions  ≤ 3 cm.Multivariate analysis revealed that female, no chronic liver disease or cirrhosis, elevated carbohydrate antigen 19-9 (CA19-9) level, normal alpha-fetoprotein (AFP) level, lobulated tumor shape, progressive or persistent enhancement pattern, no enhancing tumor capsule, targetoid appearance, and liver surface retraction were independent characteristics favoring the diagnosis of IMCC over HCC or cHCC-CC (odds ratio = 3.273-25.00, p < 0.001 to p = 0.021). Among which enhancement pattern had the highest weight of 0.816. The diagnostic system incorporating significant characteristics above showed excellent performance in the internal training (area under the curve (AUC) 0.971), internal testing (AUC 0.956), and external validation (AUC 0.945) cohorts, as well as in small lesions  ≤ 3 cm (AUC 0.956).In consideration of the great generalizability and clinical efficacy in multi-centers, the proposed diagnostic system may serve as a non-invasive, reliable, and easy-to-operate tool in IMCC diagnosis, providing an efficient approach to discriminate IMCC from other HCC-containing primary liver cancers.This study established a non-invasive, easy-to-operate, and explainable decision tree-based diagnostic system for intrahepatic mass-forming cholangiocarcinoma, which may provide essential information for clinical decision-making.• Distinguishing intrahepatic mass-forming cholangiocarcinoma (IMCC) from other primary liver cancers is important for both treatment planning and outcome prediction. • The MRI-based diagnostic system showed great performance with satisfying generalization ability in the diagnosis and discrimination of IMCC. • The diagnostic system may serve as a non-invasive, easy-to-operate, and explainable tool in the diagnosis and risk stratification for IMCC.© 2023. The Author(s), under exclusive licence to European Society of Radiology.