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1 General aspects (0)   1.1 Epidemiology (16)   1.2 Population genetics (0)   1.3 Pathogenesis (6)   1.4 Quality of life (14)   1.5 Glaucomas as cause of blindness (10)   1.6 Prevention and screening (8) 2 Anatomical structures in glaucoma (0)   2.1 Conjunctiva (9)   2.2 Cornea (18)   2.3 Sclera (7)   2.4 Anterior chamber angle (12)   2.5 Meshwork (0)     2.5.1 Trabecular meshwork (9)     2.5.2 Schlemms canal (1)     2.5.3 Scleral outlet channels (0)   2.6 Aqueous humor dynamics (0)     2.6.1 Production (0)     2.6.2 Outflow (1)       2.6.2.1 Trabecular meshwork (2)       2.6.2.2 Uveoscleral (0)     2.6.3 Compostion (4)   2.7 Episcleral veins and venous pressure (0)   2.8 Iris (10)   2.9 Ciliary body (1)   2.10 Lens (1)   2.11 Vitreous body (0)   2.12 Choroid, peripapillary choroid, peripapillary atrophy (7)   2.13 Retina and retinal nerve fibre layer (23)   2.14 Optic disc (18)   2.15 Optic nerve (1)   2.16 Chiasma and retrochiasmal central nervous system (4)   2.17 Stem cells (1)   2.20 Other (0) 3 Laboratory methods (0)   3.1 Microscopy (0)   3.2 Electron microscopy (2)   3.3 Immunohistochemistry (0)   3.4 Molecular genetics (0)     3.4.1 Linkage studies (0)     3.4.2 Gene studies (22)   3.5 Molecular biology incl. SiRNA (14)   3.6 Cellular biology (34)   3.7 Biochemistry (6)   3.8 Pharmacology (2)   3.9 Pathophysiology (7)   3.10 Immunobiology (5)   3.11 Pharmacogenetics (0)   3.12 Proteomics (1)   3.13 In vivo imaging (0)     3.13.1 Laser Scanning (0)       3.13.1.1 Confocal Scanning Laser Ophthalmoscopy (0)       3.13.1.2 Confocal Scanning Laser Polarimetry (0)     3.13.2 Optical Coherence Tomography (0)       3.13.2.1 Anterior Segment (0)       3.13.2.2 Posterior Segment (0)     3.13.3 RGC Imaging (3)     3.13.4 Other (0)   3.20 Other (0) 4 Tissue culture of ocular cells (0) 5 Experimental glaucoma; animal models (0)   5.1 Rodent (21)   5.2 Primates (0)   5.3 Other (10) 6 Clinical examination methods (0)   6.1 Intraocular pressure measurement; factors affecting IOP (0)     6.1.1 Devices, techniques (12)     6.1.2 Fluctuation, circadian rhythms (4)     6.1.3 Factors affecting IOP (17)   6.2 Tonography, aqueous flow measurement (see also 2.6) (0)   6.3 Biomicroscopy (slitlamp) (0)     6.3.1 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surgery (0)     12.8.1 Without tube implant (16)     12.8.2 With tube implant or other drainage devices (25)     12.8.3 Non-perforating (6)     12.8.4 Using laser (0)     12.8.5 Other (0)     12.8.10 Woundhealing antifibrosis (14)     12.8.11 Complications, endophthalmitis (11)   12.9 Trabeculotomy, goniotomy (3)   12.10 Cyclodestruction (4)   12.11 Cyclodialysis (0)   12.12 Cataract extraction (0)     12.12.1 Intracapsular (0)     12.12.2 Extracapsular (0)     12.12.3 Phacoemulsification (6)   12.14 Combined cataract extraction and glaucoma surgery (0)     12.14.1 Intracapsular (0)     12.14.2 Extracapsular (0)     12.14.3 Phacoemulsification (8)   12.15 Capsulotomy (0)   12.16 Vitrectomy (0)   12.17 Anesthesia (2)   12.20 Other (1) 13 Therapeutic prognosis and outcome (0)   13.1 Prognostic factors (2)   13.2 Outcome (0)     13.2.1 IOP (3)     13.2.2 Visual field (0)       13.2.2.1 Progression (1)       13.2.2.2 Improvement (0)     13.2.3 Other (0) 14 Costing studies; pharmacoeconomics (8) 15 Miscellaneous (25)

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Abstract #52618 Published in IGR 15-1

Ocular hemodynamics and glaucoma: the role of mathematical modeling

Harris A; Guidoboni G; Arciero JC; Amireskandari A; Tobe LA; Siesky BA
European Journal of Ophthalmology 2013; 23: 139-146

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PURPOSE: To discuss the role of mathematical modeling in studying ocular hemodynamics, with a focus on glaucoma. METHODS: We reviewed recent literature on glaucoma, ocular blood flow, autoregulation, the optic nerve head, and the use of mathematical modeling in ocular circulation. RESULTS: Many studies suggest that alterations in ocular hemodynamics play a significant role in the development, progression, and incidence of glaucoma. Although there is currently a limited number of studies involving mathematical modeling of ocular blood flow, regulation, and diseases (such as glaucoma), preliminary modeling work shows the potential of mathematical models to elucidate the mechanisms that contribute most significantly to glaucoma progression. CONCLUSION: Mathematical modeling is a useful tool when used synergistically with clinical and laboratory data in the study of ocular blood flow and glaucoma. The development of models to investigate the relationship between ocular hemodynamic alterations and glaucoma progression will provide a unique and useful method for studying the pathophysiology of glaucoma.

Department of Ophthalmology, Indiana University School of Medicine, Indianapolis, USA. alharris@indiana.edu

Full article

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Classification:

6.11 Bloodflow measurements (Part of: 6 Clinical examination methods)

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