Liver fibrosis staging by computed tomography: Prospective randomized multicentric evaluation of image analyses

Clinics and Research in Hepatology and Gastroenterology(2022)

引用 4|浏览22
暂无评分
摘要
Aim Liver fibrosis staging is essential. We prospectively evaluated the liver fibrosis staging performance of computed tomography (CT). Methods 70 hepato-gastroenterology clinicians were randomized into three stratified groups with different image analyses of radiological semiology, i.e., on raw images (group 1) and on expert-annotated (group 2) and computerized-morphometry-enriched (group 3) images. Radiological fibrosis staging based on seven simple descriptors into four stages equivalent to Metavir stages (F0/1, F2, F3, F4=cirrhosis) was determined at baseline and after image analyses in 10 patients with chronic liver diseases (two per F) concordant for four independent fibrosis stagings including Metavir. 23,800 CT images were analysed, providing 1400 fibrosis stagings. Results Fibrosis staging: overall (3 groups) accuracy (correct classification rate) was, baseline: 43%, post-analysis: 60% (p < 0.001) without significant progression in group 1 (6%, p = 0.207) contrary to groups 2 (34%, p < 0.001) and 3 (13%, p = 0.007). Cirrhosis diagnosis: overall accuracy was, baseline: 84%, post-analysis: 89% (p < 0.001) without significant progression in group 1 (0%, p = 1) contrary to groups 2 (8%, p = 0.009) and 3 (7%, p = 0.015). Baseline AUROCs were good (≥0.83) for marked fibrosis (F≥3 or cirrhosis) in all groups. Post-analysis AUROCs became excellent (≥0.89) in group 2 for all diagnostic targets (≥0.98 for F≥3 and cirrhosis) and in group 3 for cirrhosis. In post-analysis group 2, discrimination between all F was excellent (especially, F1 from F0) with an Obuchowski index at 0.87. Negative and positive predictive values for marked fibrosis were 98% and 95%, respectively. Conclusion Simple CT descriptors accurately discriminate all Metavir liver fibrosis stages.
更多
查看译文
关键词
Computed tomography,Liver fibrosis,Cirrhosis,Staging,Non-invasive diagnosis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要