There is considerable individual variation in the susceptibility of the optic nerve to damage from glaucoma. High intraocular pressure is an important risk factor, but its measurement cannot be used to reliably predict which patients will develop visual loss. Computerized threshold perimetry has increased the consistency with which reliable visual field data can be obtained. Still, perimetry remains a subjective test which may detect abnormalities only after significant optic nerve damage has occurred. There is considerable clinical and histological evidence that damage to the optic nerve head precedes measurable visual field loss. Sensitive, objective measures are required to detect glaucomatous optic nerve damage before functional loss occurs, and to provide an accurate barometer of the success or failure of treatment. This prospective longitudinal clinical study uses quantitative measurements of the surface contour of the optic nerve head and peripapillary nerve fiber layer to test the hypotheses that: 1) structural changes of the optic nerve head and nerve fiber layer precede visual field loss in subjects at risk for developing glaucoma, and 2) quantitative measurements of the optic nerve head and nerve fiber layer are more sensitive than measurements of the visual field to document progressive glaucomatous damage in patients with early glaucoma. Simultaneous stereoscopic videographic image acquisition (Rodenstock Analyzer) and computerized digital image processing will generate the quantitative measurements. To test the above hypotheses effectively, additional objectives of the proposed work are to 1) implement hardware changes in the image acquisition system to increase image and measurement resolution; 2) develop methods of image processing to increase the accuracy and decrease the variability of measurements; 3) develop new structural parameters which more closely reflect the number of retinal ganglion cell axons in an eye; 4) prospectively measure the effects of aging on the structure of the optic nerve and peripapillary nerve fiber layer in a group of age-matched normal controls, and 5) define the clinical utility of computerized image analysis of the optic nerve head and nerve fiber layer by comparison with clinical techniques.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY007353-03
Application #
3264265
Study Section
Visual Sciences A Study Section (VISA)
Project Start
1989-12-01
Project End
1992-11-30
Budget Start
1991-12-01
Budget End
1992-11-30
Support Year
3
Fiscal Year
1992
Total Cost
Indirect Cost
Name
Yale University
Department
Type
Schools of Medicine
DUNS #
082359691
City
New Haven
State
CT
Country
United States
Zip Code
06520
Ugurlu, S; Hoffman, D; Garway-Heath, D F et al. (2000) Relationship between structural abnormalities and short-wavelength perimetric defects in eyes at risk of glaucoma. Am J Ophthalmol 129:592-8
Moya, F J; Brigatti, L; Caprioli, J (1999) Effect of aging on optic nerve appearance: a longitudinal study. Br J Ophthalmol 83:567-72
Morgan, J; Caprioli, J; Koseki, Y (1999) Nitric oxide mediates excitotoxic and anoxic damage in rat retinal ganglion cells cocultured with astroglia. Arch Ophthalmol 117:1524-9
Uchida, H; Ugurlu, S; Caprioli, J (1998) Increasing peripapillary atrophy is associated with progressive glaucoma. Ophthalmology 105:1541-5
Nduaguba, C; Ugurlu, S; Caprioli, J (1998) Acquired pits of the optic nerve in glaucoma: prevalence and associated visual field loss. Acta Ophthalmol Scand 76:273-7
Caprioli, J; Park, H J; Ugurlu, S et al. (1998) Slope of the peripapillary nerve fiber layer surface in glaucoma. Invest Ophthalmol Vis Sci 39:2321-8
Ugurlu, S; Weitzman, M; Nduaguba, C et al. (1998) Acquired pit of the optic nerve: a risk factor for progression of glaucoma. Am J Ophthalmol 125:457-64
Nouri-Mahdavi, K; Brigatti, L; Weitzman, M et al. (1997) Comparison of methods to detect visual field progression in glaucoma . Ophthalmology 104:1228-36
Brigatti, L; Nouri-Mahdavi, K; Weitzman, M et al. (1997) Automatic detection of glaucomatous visual field progression with neural networks. Arch Ophthalmol 115:725-8
Brigatti, L; Hoffman, D; Caprioli, J (1996) Neural networks to identify glaucoma with structural and functional measurements. Am J Ophthalmol 121:511-21

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