Department of Gastroenterology, the First Affiliated Hospital of Nanchang University, Nanchang, China.
Postdoctoral Innovation Practice Base, The First Affiliated Hospital of Nanchang University, Nanchang, People's Republic of China.
Clin Transl Gastroenterol. 2024 May 1;15(5):e00693. doi: 10.14309/ctg.0000000000000693.
To develop and validate a radiomics nomogram for assessing the response of patients with Crohn's disease (CD) to infliximab.
Radiomics features of the spleen were extracted from computed tomography enterography images of each patient's arterial phase. The feature selection process was performed using the least absolute shrinkage and selection operator algorithm, and a radiomics score was calculated based on the radiomics signature formula. Subsequently, the radiomic model and the clinical risk factor model were separately established based on the radiomics score and clinically significant features, respectively. The performance of both models was evaluated using receiver operating characteristic curves, decision curve analysis curves, and clinical impact curves.
Among the 175 patients with CD, 105 exhibited a clinical response, and 60 exhibited clinical remission after receiving infliximab treatment. Our radiomic model, comprising 20 relevant features, demonstrated excellent predictive performance. The radiomic nomogram for predicting clinical response showed good calibration and discrimination in the training cohort (area under the curve [AUC] 0.909, 95% confidence interval [CI] 0.840-0.978), the validation cohort (AUC 0.954, 95% CI 0.889-1), and the external cohort (AUC = 0.902, 95% CI 0.83-0.974). Accordingly, the nomogram was also suitable for predicting clinical remission. Decision curve analysis and clinical impact curves highlighted the clinical utility of our nomogram.
Our radiomics nomogram is a noninvasive predictive tool constructed from radiomic features of the spleen. It also demonstrated good predictive accuracy in evaluating CD patients' response to infliximab treatment. Multicenter validation provided high-level evidence for its clinical application.
为评估克罗恩病(CD)患者对英夫利昔单抗的反应,开发并验证一种基于放射组学的nomogram。
从每位患者的动脉期 CT 肠造影图像中提取脾脏的放射组学特征。采用最小绝对值收缩和选择算子算法进行特征选择,并根据放射组学特征公式计算放射组学评分。然后,根据放射组学评分和临床有意义的特征分别建立放射组学模型和临床风险因素模型。采用受试者工作特征曲线、决策曲线分析曲线和临床影响曲线评估两种模型的性能。
在 175 例 CD 患者中,105 例在接受英夫利昔单抗治疗后表现出临床缓解,60 例达到临床缓解。我们的放射组学模型包含 20 个相关特征,具有出色的预测性能。预测临床缓解的放射组学nomogram 在训练队列(曲线下面积[AUC]0.909,95%置信区间[CI]0.840-0.978)、验证队列(AUC 0.954,95%CI 0.889-1)和外部队列(AUC=0.902,95%CI 0.830-0.974)中均表现出良好的校准和区分能力。因此,该 nomogram 也适用于预测临床缓解。决策曲线分析和临床影响曲线突出了 nomogram 的临床实用性。
我们的放射组学 nomogram 是一种基于脾脏放射组学特征构建的非侵入性预测工具。它在评估 CD 患者对英夫利昔单抗治疗的反应方面也表现出良好的预测准确性。多中心验证为其临床应用提供了高级别的证据。