A cellular Nonlinear Network: Real-Time Technology for the Analysis of Microfluidic Phenomena in Blood Vessels

A new approach to the observation and analysis of dynamic structural andfunctional parameters in the microcirculation is described. The newnon-invasive optical system is based on cellular nonlinear networks(CNNs), highly integrated analogue processor arrays whose processingelements, the cells, interact directly within a finite local neighbourhood.CNNs, thanks to their parallel processing feature and spatially distributedstructure, are widely used to solve high-speed image processing andrecognition problems and in the description and modelling of biologicaldynamics through the solution of time continuous partial differentialequations (PDEs). They are therefore considered extremely suitable forspatial–temporal dynamic characterization of fluidic phenomena atmicrometric to nanometric scales, such as blood flow in microvessels andits interaction with the cells of the vessel wall. A CNN universal machine(CNN-UM) structure was used to implement, via simulation and hardware(ACE16k), the algorithms to determine the functional capillarity density(FCD) and red blood cell velocity (RBCV) in capillaries obtained byintravital microscopy during in vivo experiments on hamsters. The systemexploits the moving particles to distinguish the functional capillaries fromthe stationary background. This information is used to reconstruct a mapand to calculate the velocity of the moving objects.