Vol 11, No 2 (2005)
Research paper
Published online: 2005-05-19
Estimation of variability of retinal vessel network caused by pathology
Acta Angiologica 2005;11(2):121-128.
Abstract
Background. The present study shows the plasticity of retinal vessel networks connected with pathology. It
seems that even in adults, retinal vessel networks can change their shape and arborisation under the
influence of angiogenic factors connected with pathological processes.
Material and methods. Fractal analysis of photographs of vascular networks revealed significant differences between controls and diabetic retinopathy, hypertensive retinopathy and AMD (age related macular degeneration). The results are based on the analysis and calculations of fractal dimensions of 173 pathological and control photographs of retinal vessels. The following patients were included in the study: 38 diabetic retinopathy, 31 hypertensive retinopathy, 32 open-angle glaucoma, 39 AMD patients and 33 controls. The fractal dimension is the mathematical parameter describing the complexity of the analysed network. The obtained images of retinal vessel networks were digitised, normalised and processed mathematically. The box counting method was used for calculation of fractal dimensions.
Conclusions. This analysis allows not only for description of the plasticity and complexity of retinal network as the effect of pathological conditions but also contains the potential to use this kind of analysis for diagnostic purposes.
Material and methods. Fractal analysis of photographs of vascular networks revealed significant differences between controls and diabetic retinopathy, hypertensive retinopathy and AMD (age related macular degeneration). The results are based on the analysis and calculations of fractal dimensions of 173 pathological and control photographs of retinal vessels. The following patients were included in the study: 38 diabetic retinopathy, 31 hypertensive retinopathy, 32 open-angle glaucoma, 39 AMD patients and 33 controls. The fractal dimension is the mathematical parameter describing the complexity of the analysed network. The obtained images of retinal vessel networks were digitised, normalised and processed mathematically. The box counting method was used for calculation of fractal dimensions.
Conclusions. This analysis allows not only for description of the plasticity and complexity of retinal network as the effect of pathological conditions but also contains the potential to use this kind of analysis for diagnostic purposes.
Keywords: fractal dimensionsretinal vessel networkplasticity of retinal angiogenesis