肝内胆管癌 (ICC) 是一种发病率不断增加的侵袭性疾病，其基因改变可能成为全身治疗的目标。阐明从计算机断层扫描 (CT) 提取的放射组学是否可以非侵入性预测 ICC 基因改变。所有连续诊断的患者考虑了大规模形成的ICC（01/2016-06/2022）。纳入标准是可获得高质量对比增强 CT 以及通过 NGS 或 FISH 进行 FGFR2 融合/重排的分子分析。诊断时考虑了 CT 扫描。对手术标本（可切除的患者）或活检组织（不可切除的患者）进行遗传分析。使用 LifeX 软件提取放射组学特征。建立了最常见基因改变的多变量预测模型。在 90 名入组患者（58 名 NGS/32 名 FISH，中位年龄 65 岁）中，最常见的基因改变是 FGFR2 (20/90)、IDH1 (10/58) 和KRAS (9/58)。在内部验证中，组合的临床放射组学模型在预测 FGFR2 (AUC = 0.892) 和 IDH1 状态 (AUC = 0.819) 方面取得了最佳性能，优于纯临床和放射组学模型。用于预测 KRAS 突变的放射组学模型达到了 AUC = 0.767（相对于临床模型的 0.660），无需通过添加临床特征进行进一步改进。基于 CT 的放射组学为 ICC 遗传状态提供了可靠的非侵入性预测，具有重大影响治疗策略。版权所有 © 2024 Editrice Gastroenterologica Italiana S.r.l.由爱思唯尔有限公司出版。保留所有权利。

Intrahepatic cholangiocarcinoma (ICC) is an aggressive disease with increasing incidence and its genetic alterations could be the target of systemic therapies.To elucidate if radiomics extracted from computed tomography (CT) may non-invasively predict ICC genetic alterations.All consecutive patients with a diagnosis of a mass-forming ICC (01/2016-06/2022) were considered. Inclusion criteria were availability of a high-quality contrast-enhanced CT and molecular profiling by NGS or FISH for FGFR2 fusion/rearrangement. The CT scan at diagnosis was considered. Genetic analyses were performed on surgical specimens (resectable patients) or biopsies (unresectable ones). The radiomic features were extracted using the LifeX software. Multivariate predictive models of the commonest genetic alterations were built.In the 90 enrolled patients (58 NGS/32 FISH, median age 65 years), the most common genetic alterations were FGFR2 (20/90), IDH1 (10/58), and KRAS (9/58). At internal validation, the combined clinical-radiomic models achieved the best performance for the prediction of FGFR2 (AUC = 0.892) and IDH1 status (AUC = 0.819), outperforming the pure clinical and radiomic models. The radiomic model for predicting KRAS mutations achieved an AUC = 0.767 (vs. 0.660 of the clinical model) without further improvements with the addition of clinical features.CT-based radiomics provides a reliable non-invasive prediction of ICC genetic status with a major impact on therapeutic strategies.Copyright © 2024 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.