Development and validation of a radiomics signature as a non‐invasive complementary predictor of gastroesophageal varices and high‐risk varices in compensated advanced chronic liver disease: A multicenter study

医学 食管胃十二指肠镜检查 队列 接收机工作特性 内科学 静脉曲张 置信区间 放射科 金标准(测试) 胃肠病学 肝硬化 前瞻性队列研究 内窥镜检查
作者
Yifei Huang,Fangze Huang,Li Yang,Weiling Hu,Yanna Liu,Zihuai Lin,Xiangpan Meng,Manling Zeng,Chaohui He,Qing Xu,Guanghang Xie,Yanna Liu,Mingkai Liang,Xiaoguo Li,Kang Ning,Dan Xu,Jitao Wang,Liting Zhang,Xiaorong Mao,Changqing Yang
出处
期刊:Journal of Gastroenterology and Hepatology [Wiley]
卷期号:36 (6): 1562-1570 被引量:23
标识
DOI:10.1111/jgh.15306
摘要

Abstract Background and Aim Gastroesophageal varices (GEV) present in compensated advanced chronic liver disease (cACLD) and can develop into high‐risk varices (HRV). The gold standard for diagnosing GEV is esophagogastroduodenoscopy (EGD). However, EGD is invasive and less tolerant. This study aimed to develop and validate radiomics signatures based on noncontrast‐enhanced computed tomography (CT) images for non‐invasive diagnosis of GEV and HRV in patients with cACLD. Methods The multicenter trial enrolled 161 patients with cACLD from six university hospitals in China between January 2015 and September 2019, who underwent both EGD and noncontrast‐enhanced CT examination within 14 days prior to the endoscopy. Two radiomics signatures, termed r GEV and r HRV, respectively, were built based on CT images in a training cohort of 129 patients and validated in a prospective validation cohort of 32 patients (ClinicalTrials. gov identifier: NCT03749954). Results In the training cohort, both r GEV and r HRV exhibited high discriminative abilities on determining the existence of GEV and HRV with the area under receiver operating characteristic curve (AUC) of 0.941 (95% confidence interval [CI] 0.904–0.978) and 0.836 (95% CI 0.766–0.905), respectively. In validation cohort, r GEV and r HRV showed high discriminative abilities with AUCs of 0.871 (95% CI 0.739–1.000) and 0.831 (95% CI 0.685–0.978), respectively. Conclusions This study demonstrated that r GEV and r HRV could serve as the satisfying auxiliary parameters for detection of GEV and HRV with good diagnostic performance.
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