Israel Medical Association Journal

Background: Hepatitis C virus (HCV) is a leading cause of cirrhosis and hepatocellular carcinoma worldwide. Several viral and host factors related to viral response have been reported in the era of treatment with pegylated (PEG)-interferon and ribavirin.

Objectives: To quantify histological findings from patients with chronic HCV using computerized morphometry and to investigate whether the results can predict response to medical treatment with peg-interferon and ribavirin.

Methods: We followed 58 patients with chronic HCV infection with METAVIR score F1 and F2 in our liver unit who were grouped according to treatment response sustained viral response (SVR) and non-SVR. Liver needle biopsies from these patients were evaluated and histological variables, such as inflammatory cells, collagen fibers and liver architecture, were quantified using computerized morphometrics. The pathologist who performed the histomorphometric analysis was blinded to previous patient clinical and histological information.

Results: Histomorphometric variables including the density of collagen fibers were collected. The number of inflammatory cells in the portal space and textural variable were found to be statistically significant and could be used together in a formula to predict response to treatment, with a sensitivity of 93% and a 100% specificity.

Conclusions: Histomorphometry may help to predict a patient's response to treatment at an early stage.

Objective: To evaluate the feasibility of using combined clinical and histomorphometric features to construct a prognostic score for the individual patient with localized renal cell carcinoma.

Patients and Methods: We studied 39 patients with pT1 and pT2 RCC who underwent radical nephrectomy between 1974 and 1983. Univariate and multivariate analyses were used to determine the association between various prognostic features and patient survival.

Results: The most important and independent predictors of survival were tumor angiogenesis (P=0.009), nuclear DNA ploidy (P=0.0071), mean nuclear area (P=0.013), and mean elongation factor (P=0.0346). Combination of these variables enabled prediction of outcome for the individual patient at a sensitivity and specificity of 78% and 89% respectively.

Conclusion: Our results indicate that no single parameter can accurately predict the outcome for patients with localized RCC. Combination of neovascularity, DNA content and morphometric shape descriptors enabled a more precise stratification of the patients into different risk categories.