Texture analysis is superior to magnetization transfer for fibrosis assessment in a gut fibrosis model

Research Square (Research Square)(2022)

引用 0|浏览3
暂无评分
摘要
Abstract Background and Aims Since there are no accurate methods for fibrosis identification or quantification, the purpose is to investigate the utility of magnetization transfer (MT) MRI and texture analysis (TA) of T2-weighted MR images for intestinal fibrosis assessment in a mouse model of gut fibrosis. Methods Chronic colitis was obtained in 16 C57BL/6 mice by cyclic administration of dextran sodium sulphate (DSS) inducing early phase inflammation and progressive bowel fibrosis. Mice underwent 7.0 T MR imaging at various timepoints. MT ratio (MTR) in the bowel wall was calculated. Textural features (skewness, kurtosis, entropy) were extracted by a filtration histogram technique. Resected colonic tissue was scored for inflammation and fibrosis. Performance of MT-MRI and TA was validated in a consecutive experiment in mice using antifibrotic therapy. Finally, a retrospective study was conducted in five CD patients who underwent bowel surgery. Results MTR and texture entropy both correlated with histopathological fibrosis (r = .85 and .81, respectively). Entropy was superior to MTR for monitoring bowel fibrosis in presence of coexisting inflammation (linear regression R² = .93 versus R2 = .01). Furthermore, texture entropy was able to assess antifibrotic therapy response (placebo mice versus treated mice at endpoint scan; Δ mean = 0.128, p < .0001). An increase in entropy was indicative of fibrosis accumulation in human CD strictures (1.29 in inflammation; 1.40 and 1.48 in mixed strictures; 1.73 and 1.90 in fibrosis). Conclusion Texture analysis of T2-weighted MR images outperforms magnetization transfer imaging in detecting the fibrotic component in mixed inflammatory-fibrotic bowel tissue and can be used for monitoring antifibrotic treatment response.
更多
查看译文
关键词
gut fibrosis model,fibrosis assessment,texture analysis,magnetization transfer
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