Computer simulations of histologic patterns in XXXX using a cellular automaton provide correlations with prognosis.

@entity5 @entity320
Computer simulations have been used frequently in the life sciences to investigate the mechanisms of morphologic pattern formation. The cellular automaton program SMN5 is designed to simulate @entity5 growth and to estimate biologic properties by comparing real @entity5 patterns with computer-simulated reference patterns. This method was applied to 195 cases of primary @entity320 . S-100-stained sections were evaluated by image analysis and compared statistically to a reference set of 4000 simulated patterns. Estimates of @entity5 cell proliferation, motility, cell loss, cohesion, stroma destruction, and intercellular signals (autocrine and paracrine factors affecting growth, motility, and cell loss) were calculated. Twelve of 18 estimated parameters correlated significantly with @entity5 progression, as indicated by vertical @entity5 thickness (linear regression analysis: p < or = 0.05), and 13 of 18 parameters carried prognostic significance (log rank test: p < or = 0.05). Poor prognosis was associated particularly with a pronounced increase in the estimates of proliferation, @entity5 cell motility, and stromal degradation. Poor prognosis was also associated with a decrease in the estimates of cell loss, @entity5 cell cohesion, and paracrine growth factor dependence. In multivariate analysis using Cox's proportional hazard model, stromal degradation and motility showed prognostic information in addition to conventional prognostic parameters. The study shows that analytical @entity5 with computer-simulated patterns of a cellular automaton facilitates a functional interpretation of @entity5 morphology, which carries prognostic significance in @entity320 .
