An Inexpensive Digital Image Analysis Technique for Liver Fibrosis Quantification in Chronic Hepatitis B Patients

Autores: Zhou Yin, Qing Ru Guo, Yan Rong, Shan Wang Ming, Chen Mei Juan, Yu Li Li, Wang Hong

Resumen

Background and aim. Quantitative digital imaging analysis to evaluate liver fibrosis is accurate, but its clinical use is limited by its high cost and lack of standardization. We aimed to validate an inexpensive digital imaging analysis technique for fibrosis quantification in chronic hepatitis B patients. Material and methods. In total, 142 chronic hepatitis B patients who underwent liver biopsy and analysis of serum fibrosis markers were included. Images of Sirius red stain sections were captured and processed using Adobe Photoshop CS3 software. The percentage of fibrosis (fibrosis index) was determined by the ratio of the fibrosis area to the total sample area, expressed in pixels, and calculated automatically. Results. A strong correlation between the fibrosis index and the Ishak, Metavir, and Laennec histological staging systems were observed (r = 0.83, 0.86, and 0.84, respectively; p < 0.001). The cutoff value associated with cirrhosis was 7.7% with an area under the receiver operating characteristic curve (AUROC) of 0.95 (95% confidence interval [CI], 0.92-0.99, p < 0.001). Furthermore, the fibrosis index yielded a cutoff value of 8.9% (AUROC, 0.74; 95% CI, 0.66-0.86), 12% (AUROC, 0.84; 95% CI, 0.75-0.93), and 14% (AUROC, 0.97; 95% CI, 0.92-1.0) for the diagnosis of cirrhosis 4a, 4b, and 4c, respectively. No serum markers or fibrosis models were correlated with the fibrosis index in Metavir F2-F4. Conclusions. The present digital imaging analysis technique is reproducible and available worldwide, allowing its use in clinical practice, and can be considered as a complementary tool to traditional histological methods.

Palabras clave: Biopsy diagnostic imaging fibrosis hepatitis B virus.

2017-12-13   |   295 visitas   |   Evalua este artículo 0 valoraciones

Vol. 16 Núm.6. Noviembre-Diciembre 2017 Pags. 881-887 Ann Hepatol 2017; 16(6)