Maison Abu Raya
Rappaport Faculty of medicine; the Technion, Israel
Title: Histomorphometric findings may help predict response to antiviral therapy at an early fibrosis grade in patients with chronic HCV infection
Biography
Biography: Maison Abu Raya
Abstract
Histomorphometry is a quantitative method for investigating changes in shape, size and orientation of cells in tissues. The aim of our study is to use computerized morophometry in order to quantify the histological changes that occur in liver biopsies obtained from patients with chronic HCV, and to predict the response to medical treatment in these patients. Patients with chronic HCV genotype 1, with Metavir score F1 and F2 followed at our liver were selected and grouped according to treatment response {SVR and non-SVR}. Histological slides from the pretreated liver biopsies were scanned using the dot slide virtual microscopy Olympus system. The ImagePro plus 7.0 program has been used to quantify the amount of collagen fibers, the number of inflammatory cells and textural changes of the livers parenchyma. The Matlab software was used to calculate fractal and lacunar dimensions of the liver parenchyma in order to capture any structural changes in the livers general architecture. Our study has shown that morphometric variables including the density of collagen fibers, the fraction of inflammatory cells per portal space area, and textural parameters were found to be statistically significant and could be combined together in a mathematical formula, in order to predict response to treatment in HCV patients, with sensitivity of 93%, and 100% specificity. In conclusion morphomertic method is promising and may contribute to developing a novel expert guided automatic system predicting response to treatment in chronic HCV patients, and may be used in the future to investigate liver diseases due to different etiologies.
