Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Qiaokou District, 1095 Jiefang Avenue, Wuhan, Hubei, 430030, China.
Department of Radiology, West China Hospital, Sichuan University, Guoxue Alley, No. 37, Guoxue Alley, Chengdu, Sichuan, 610041, China.
BMC Med. 2024 Oct 8;22(1):441. doi: 10.1186/s12916-024-03669-5.
Delayed diagnosis of inflammatory bowel disease (IBD) is common, there is still no effective imaging system to distinguish Crohn's Disease (CD) and Ulcerative Colitis (UC) patients.
This multicenter retrospective study included IBD patients at three centers between January 2012 and May 2022. The intestinal and perianal imaging signs were evaluated. Visceral fat information from CT images was extracted, including the ratio of visceral to subcutaneous fat volume (VSR), fat distribution, and attenuation values. The valuable indicators were screened out in the derivation cohort by binary logistic regression and receiver working curve (ROC) analysis to construct an imaging report and data system for IBD (IBD-RADS), which was tested in the validation cohort.
The derivation cohort included 606 patients (365 CD, 241 UC), and the validation cohort included 155 patients (97 CD, 58 UC). Asymmetric enhancement (AE) (OR = 87.75 [28.69, 268.4]; P < 0.001), perianal fistula (OR = 4.968 [1.807, 13.66]; P = 0.002) and VSR (OR = 1.571 [1.087, 2.280]; P = 0.04) were independent predictors of CD. VSR improved the efficiency of imaging signs (AUC: 0.929 vs. 0.901; P < 0.001), with a threshold greater than 0.97 defined as visceral fat predominance (VFP). In IBD-RADS, AE was the major criterion, VFP and perianal fistula were auxiliary criteria, and intestinal fistula, limited small bowel disease, and skip distribution were special favoring items as their 100% specificity. Grade 3 to 5 correctly classified most CD patients (derivation: 96.5% (352/365), validation: 98.0% (95/97)), and 98% of those were eventually diagnosed with CD (derivation: 97.8% (352/360), validation: 98.0% (95/97)).
IBD-RADS can help radiologists distinguish between CD and UC in patients with suspected IBD.
炎症性肠病(IBD)的诊断延迟较为常见,目前仍缺乏有效的影像学系统来区分克罗恩病(CD)和溃疡性结肠炎(UC)患者。
本多中心回顾性研究纳入了 2012 年 1 月至 2022 年 5 月期间三个中心的 IBD 患者。评估了肠道和肛周的影像学征象。从 CT 图像中提取内脏脂肪信息,包括内脏与皮下脂肪体积比(VSR)、脂肪分布和衰减值。通过二元逻辑回归和接收工作曲线(ROC)分析在推导队列中筛选出有价值的指标,构建炎症性肠病(IBD)的影像学报告和数据系统(IBD-RADS),并在验证队列中进行测试。
推导队列纳入了 606 例患者(365 例 CD,241 例 UC),验证队列纳入了 155 例患者(97 例 CD,58 例 UC)。非对称强化(AE)(OR=87.75[28.69, 268.4];P<0.001)、肛周瘘(OR=4.968[1.807, 13.66];P=0.002)和 VSR(OR=1.571[1.087, 2.280];P=0.04)是 CD 的独立预测因子。VSR 提高了影像学征象的效能(AUC:0.929 比 0.901;P<0.001),定义 VSR 大于 0.97 为内脏脂肪优势(VFP)。在 IBD-RADS 中,AE 是主要标准,VFP 和肛周瘘是辅助标准,而肠道瘘、局限性小肠疾病和跳跃分布则是特异性的有利项目,其特异性为 100%。3 级到 5 级正确分类了大多数 CD 患者(推导队列:96.5%(352/365),验证队列:98.0%(95/97)),其中 98%的患者最终被诊断为 CD(推导队列:97.8%(352/360),验证队列:98.0%(95/97))。
IBD-RADS 有助于放射科医生在疑似 IBD 患者中区分 CD 和 UC。