Development and Validation of a Novel Computed-Tomography Enterography Radiomic Approach for Characterization of Intestinal Fibrosis in Crohn's Disease.

影響因子： 17.373PMID：33609503期刊年卷：Gastroenterology 2021 Feb 17;醫學一區 胃腸肝病學 Q1 1/80DOI：10.1053/j.gastro.2021.02.027作者列表: Li X, Liang D, Meng J, Zhou J, Chen Z, Huang S, Lu B, Qiu Y, Baker ME, Ye Z, Cao Q, Wang M, Yuan C, Chen Z, Feng S, Zhang Y, Iacucci M, Ghosh S, Rieder F, Sun C, Chen M, Li Z, Mao R, Huang B, Feng ST,

BACKGROUND & AIMS:No reliable method for evaluating intestinal fibrosis in Crohn's disease (CD) exists; therefore, we developed a computed-tomography enterography (CTE)-based radiomic model (RM) for characterising intestinal fibrosis in CD.

METHODS:This retrospective-multicentre study included 167 CD patients with 212 bowel lesions (training, 98 lesions; test, 114 lesions) who underwent preoperative CTE and bowel resection at one of the three tertiary referral centres from January 2014 through June 2020. Bowel fibrosis was histologically classified as none-mild or moderate-severe. In the training cohort, 1454 radiomic features were extracted from venous-phase CTE, and a machine learning-based RM was developed based on the reproducible features using logistic regression. The RM was validated in an independent external test cohort recruited from three centres. The diagnostic performance of RM was compared with two radiologists' visual interpretation of CTE using receiver operating characteristic (ROC) curve analysis.

RESULTS:In the training cohort, the area under the ROC curve (AUC) of RM for distinguishing moderate-severe from none-mild intestinal fibrosis was 0.888 (95% confidence interval [CI]: 0.818-0.957). In the test cohort, the RM showed robust performance across three centres with an AUC of 0.816 (95% CI: 0.706-0.926), 0.724 (95% CI: 0.526-0.923), and 0.750 (95% CI: 0.560-0.940), respectively. Moreover, the RM was more accurate than visual interpretations by either radiologist (#1 AUC=0.554; #2 AUC=0.598; both P<0.001) in the test cohort. Decision curve analysis showed that the RM provided a better net benefit to predicting intestinal fibrosis than the radiologists.

CONCLUSION:A CTE-based RM allows for accurate characterisation of intestinal fibrosis in CD.

克隆氏病患者腸纖維化的新的計算機斷層掃描腸道造影放射學方法的開發和驗證

背景與目的：目前尚無可靠的方法評估克羅恩病(Crohn‘s disease，CD)的腸纖維化，因此，我們發展了一種基於計算機體層腸造影術(Computer-Tomography enterography，CTE)的放射組學模型（RM）來表徵CD的腸纖維化。

方法：這項回顧性多中心研究包括167例CD患者，212個腸道病變(訓練型，98個；測試型，114個)，他們在2014年1月至2020年6月期間在三個三級轉診中心之一接受了CTE和腸切除術。腸纖維化的組織學分類為非輕度或中度-重度。在訓練佇列中，從靜脈期CTE中提取了1454個放射組學特徵，並基於這些可重現的特徵利用Logistic迴歸開發了基於機器學習的RM。RM在從三個中心招募的獨立外部測試佇列中得到驗證。透過受試者工作特徵(ROC)曲線分析，將RM的診斷效能與兩位放射科醫師對CTE的目測解釋進行比較。

結果：在訓練佇列中，RM區分中重度和非輕度腸纖維化的ROC曲線下面積為0.888(95%可信區間：0.818~0.957)。在測試佇列中，RM在三個中心表現強勁，AUC值分別為0.816(95%CI：0.706-0.926)、0.724(95%CI：0.526-0.923)和0.750(95%CI：0.560-0.940)。此外，在測試佇列中，RM比任何一位放射科醫生的目測解釋更準確(#1AUC=0.554；#2AUC=0.598；均P<0.001)。決策曲線分析顯示，與放射科醫生相比，RM在預測腸纖維化方面提供了更好的淨效益。

結論：基於CTE的RM可以準確地描述CD中的腸纖維化。