Diffusion-weighted magnetic resonance imaging and micro-RNA in the diagnosis of hepatic fibrosis in chronic hepatitis C virus

弥散加权磁共振成像和微小RNA在慢性丙型肝炎肝纤维化诊断中的应用

阅读:8
作者:Tarek Besheer, Hatem Elalfy, Mohamed Abd El-Maksoud, Ahmed Abd El-Razek, Saher Taman, Khaled Zalata, Wagdy Elkashef, Hossam Zaghloul, Heba Elshahawy, Doaa Raafat, Wafaa Elemshaty, Eman Elsayed, Abdel-Hady El-Gilany, Mahmoud El-Bendary

Aim

To assess diffusion-weighted magnetic resonance imaging and miRs in diagnosing and staging hepatic fibrosis in patients with chronic hepatitis C.

Background

Diffusion-weighted magnetic resonance imaging has shown promise in the detection and quantification of hepatic fibrosis. In addition, the liver has numerous endogenous micro-RNAs (miRs) that play important roles in the regulation of biological processes such as cell proliferation and hepatic fibrosis.

Conclusion

Combining ADC and miRs offers an alternative surrogate non-invasive diagnostic tool for diagnosing and staging hepatic fibrosis in patients with chronic hepatitis C.

Methods

This prospective study included 208 patients and 82 age- and sex-matched controls who underwent diffusion-weighted magnetic resonance imaging of the abdomen, miR profiling, and liver biopsy. Pathological scoring was classified according to the METAVIR scoring system. The apparent diffusion coefficient (ADC) and miR were calculated and correlated with pathological scoring.

Results

The ADC value decreased significantly with the progression of fibrosis, from controls (F0) to patients with early fibrosis (F1 and F2) to those with late fibrosis (F3 and F4) (median 1.92, 1.53, and 1.25 × 10-3 mm2/s, respectively) (P = 0.001). The cut-off ADC value used to differentiate patients from controls was 1.83 × 10-3 mm2/s with an area under the curve (AUC) of 0.992. Combining ADC and miR-200b revealed the highest AUC (0.995) for differentiating patients from controls with an accuracy of 96.9%. The cut-off ADC used to differentiate early fibrosis from late fibrosis was 1.54 × 10-3 mm2/s with an AUC of 0.866. The combination of ADC and miR-200b revealed the best AUC (0.925) for differentiating early fibrosis from late fibrosis with an accuracy of 80.2%. The ADC correlated with miR-200b (r = - 0.61, P = 0.001), miR-21 (r = - 0.62, P = 0.001), and miR-29 (r = 0.52, P = 0.001).

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。