Development of an image-based network model of retinal vasculature.
The paper presents an image-based network model of retinal vasculature taking account of the 3D vascular distribution of the retina. Mouse retinas were prepared using flat-mount technique and vascular images were obtained using confocal microscopy. The vascular morphometric information obtained from confocal images was used for the model development. The network model developed directly represents the vascular geometry of all the large vessels of the arteriolar and venular trees and models the capillaries using uniformly distributed meshes. The vasculatures in different layers of the retina, namely the superficial, intermediate, and deep layer, were modeled separately in the network and were linked through connecting vessels. The branching data of the vasculatures was recorded using the method of connectivity matrix of network (the graph theory). Such an approach is able to take into account the detailed vasculature of individual retinas concerned. Using the network model developed, a circulation analysis based on Poiseuille's equation was carried out. The investigations produced predictions of spatial distribution of the pressure, flow, and wall shear stress in the entire retinal vasculature. The method developed can be used as a tool for continuous monitoring of the retinal circulation for clinical assessments as well as experimental studies.
Ganesan
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School of Engineering, University of Aberdeen, Aberdeen AB24 3UE, UK.
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Xu
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D000818:Animals; D001783:Blood Flow Velocity / Q000502:physiology; D001794:Blood Pressure / Q000502:physiology; D003198:Computer Simulation; D005260:Female; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D051379:Mice; D008810:Mice, Inbred C57BL; D018613:Microscopy, Confocal / Q000379:methods*; D008953:Models, Anatomic; D008955:Models, Cardiovascular; D012171:Retinal Vessels / Q000033:anatomy & histology* / Q000502:physiology*; D042262:Retinoscopy / Q000379:methods*