Abstract
Abstract: :
Purpose:To develop a knowledge-based model of retinal microcirculation (RMC) to simulate the relations between measurable and nonmeasurable flow-physiologic magnitudes of the RMC for normal, physiological and pathological conditions. Up to now there are no sufficient models of the RMC. The results are often false interpretations of measuring results of microcirculation. Simulation of different flow-physiological conditions of the retinal microcirculation by means of a knowledge-based model is important to understand microcirculation and measuring results. Methods:The model is based on the vessel structure of the retina consisting of four quadrants parallel to each other. Each quadrant is composed of five vessel compartments (small arteries, arterioles, capillaries, venules, veins) connected in series with a number of parallel vessels within one compartment. The network is formed by following model parameters: vessel diameters/lengths/numbers for compartment. Further parameters are measurable bloodrheological values. Nonlinear flow-pressure-relations of the Casson Flow are used to calculate the model parameters blood flow, blood velocity and retinal perfusion pressure in the large-caliber vessels. In the capillaries the nonlinear relation is included by the deformation pressure of the red blood cells. For simulating a medium healthy subject the mean values of known experimental studies are used as measurable parameters. The nonmeasurable parameters for healthy subjects are compiled from laboratory-experimental studies found in the literature. The model simulation consists of varying the nonmeasurable model parameters within plausible limits until all parameters can be combined in the model without inconsistencies. All calculated parameter values are displayed in the monitor. They may be changed for different data sets and the graphical presentation of waveforms (e.g. velocity profiles, pressure drops) allows to visualize, compare, simulate different conditions of the RMC. Results:Measurable and nonmeasurable model parameters from the literature may be unified in the model without contradictions. Model simulations deliver plausible results reproducible under clinical conditions. Conclusion:Retinamodell is a good RMC simulation tool. It is interesting to simulate pathological and therapeutical conditions e.g. glaucoma, diabetic retinopathy and occlusive diseases. Retinamodell is useful for the interpretation of measuring results and to understand therapeutic effects of RMC as well as the meaning of measuring magnitudes of the microcirculation.
Keywords: 331 blood supply • 364 computational modeling • 559 retinal connections, networks, circuitry