Approximately 13%–40% of patients with Crohn's disease (CD) show a primary loss of response to infliximab (IFX) therapy. Therefore, differentiating potential responders from primary nonresponders is clinically important. In this double-center study, we developed and validated a computed tomography enterography (CTE)-based radiomic signature (RS) for identification of CD patients at high risk of primary nonresponse (PNR) to IFX therapy, and demonstrated its incremental value to the clinical model. A total of 244 patients (training cohort, n = 119; test cohort 1, n = 51; test cohort 2, n = 74) were retrospectively recruited. Their clinical data and pretreatment CTE were retrieved and analyzed. All patients underwent IFX induction therapy. Reliability of clinical factors and radiomic-based features were assessed with the area under the receiver operating characteristic curve (AUC). In all, 1130 radiomic features were extracted from the whole inflamed gut in CTE images. In training cohort and test cohorts 1 and 2, the RS that discriminated PNR to IFX therapy yielded AUCs of 0.848, 0.789, and 0.789, respectively (all p < 0.05). By combining the clinical predictors (C-reactive protein, albumin, and body mass index) and RS, the radiomic-clinical model showed an increase in predicting performance (AUCs: 0.864, 0.794, and 0.791, respectively; all p < 0.05). Decision curve analysis and net reclassification improvement demonstrated the clinical usefulness of the radiomic-clinical model. In this study, the proposed RS showed potential as a clinical aid for the accurate identification of CD patients at high risk of PNR to IFX therapy before treatment. A combination of the RS and existing clinical factors might enable a step forward precise medicine.

中文翻译：

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使用放射组学-临床模型识别对英夫利昔单抗原发性无反应的高风险克罗恩病患者

大约 13%–40% 的克罗恩病 (CD) 患者表现出对英夫利昔单抗 (IFX) 治疗的主要反应丧失。因此，区分潜在反应者和原发性无反应者在临床上很重要。在这项双中心研究中，我们开发并验证了一种基于计算机断层扫描小肠造影术 (CTE) 的放射组学特征 (RS)，用于识别对 IFX 治疗处于原发性无反应 (PNR) 高风险的 CD 患者，并证明了其对临床模型。总共 244 名患者（训练队列，n  = 119；测试队列 1，n  = 51；测试队列 2，n = 74) 被追溯招募。检索并分析了他们的临床数据和治疗前 CTE。所有患者均接受了 IFX 诱导治疗。临床因素的可靠性和基于放射组学的特征通过接受者操作特征曲线 (AUC) 下的面积进行评估。总共从 CTE 图像中的整个发炎肠道中提取了 1130 个放射组学特征。在训练队列和测试队列 1 和 2 中，将 PNR 与 IFX 疗法区分开来的 RS 分别产生了 0.848、0.789 和 0.789 的 AUC（所有p  < 0.05）。通过结合临床预测因子（C 反应蛋白、白蛋白和体重指数）和 RS，放射组学-临床模型显示预测性能有所提高（AUC：分别为 0.864、0.794 和 0.791；所有p < 0.05)。决策曲线分析和净重新分类改进证明了放射组学-临床模型的临床实用性。在这项研究中，拟议的 RS 显示出作为临床辅助工具的潜力，可以在治疗前准确识别 PNR 高风险的 CD 患者接受 IFX 治疗。RS 和现有临床因素的结合可能使精准医学向前迈进了一步。