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. 2012 Oct 5;53(11):6939-46.
doi: 10.1167/iovs.12-10345.

The structure and function relationship in glaucoma: implications for detection of progression and measurement of rates of change

Affiliations

The structure and function relationship in glaucoma: implications for detection of progression and measurement of rates of change

Felipe A Medeiros et al. Invest Ophthalmol Vis Sci. .

Abstract

Purpose: To evaluate the relationship between change in estimated retinal ganglion cell (RGC) counts and change in measures of functional and structural damage in glaucoma, from cross-sectional data.

Methods: The study included 397 eyes of 397 patients with glaucoma, suspects, and healthy individuals. All eyes underwent testing with standard automated perimetry (SAP) and spectral-domain optical coherence tomography (SD-OCT). Estimates of retinal ganglion cell (RGC) counts were obtained from SAP and SD-OCT using a previously derived algorithm. Smoothing spline curves were fitted to investigate the relationship between functional/structural parameters and RGC counts. The first derivatives (i.e., slopes) of these curves were obtained to investigate the relationship between changes in these measures.

Results: A nonlinear relationship was observed between SAP mean deviation (MD) and RGC counts. The same amount of RGC loss corresponded to largely different amounts of MD change depending on the stage of the disease. For SDOCT average retinal nerve fiber layer (RNFL) thickness, a linear relationship was seen with RGC counts throughout most of the spectrum of disease, but reaching a plateau in advanced glaucoma. Changes in RGC counts for eyes with early damage corresponded to small changes in MD, but to relatively larger changes in RNFL thickness. For eyes with advanced disease, changes in RGC counts produced relatively larger changes in MD but only small or no changes in average RNFL thickness.

Conclusions: The analysis and interpretation of rates of SAP and SD-OCT change, as indicators of the velocity of neural damage in glaucoma, should take into account the severity of the disease.

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Conflict of interest statement

Disclosure: F.A. Medeiros, Carl-Zeiss Meditec (F), Heidelberg Engineering (F), Optovue, Inc. (F), Topcon (F), P; L.M. Zangwill, Carl-Zeiss Meditec (F), Heidelberg Engineering (F), Optovue, Inc. (F), Topcon (F); C. Bowd, None; K. Mansouri, None; R.N. Weinreb, Carl-Zeiss Meditec (F, C), Heidelberg Engineering (F), Optovue, Inc. (F), Topcon (F)

Figures

Figure 1.
Figure 1.
Boxplot graph illustrating the distribution of estimates of RGC counts in the four diagnostic categories: healthy eyes, eyes with ocular hypertension (OHT), eyes with GON but normal visual fields, and eyes with glaucomatous visual fields.
Figure 2.
Figure 2.
Analysis of the relationship between visual field parameters and estimated RGC counts. (A) Relationship between MD and estimated RGC counts. (B) First derivatives of the curve shown on Figure 2A plotted against estimated RGC counts. The derivatives indicate the amount of change in MD per 10,000 RGCs at different levels of RGC counts.
Figure 3.
Figure 3.
Analysis of the relationship between structural parameters and estimated RGC counts. (A) Relationship between SD-OCT, average RNFL thickness, and RGC counts. (B) First derivatives of the curve shown on Figure 3A plotted against estimated RGC counts. The derivatives indicate the amount of change in average RNFL thickness per 10,000 RGCs at different levels of RGC counts.
Figure 4.
Figure 4.
Relationship between MD, average RNFL thickness measurements, and estimated RGC counts. At early stages of damage (high RGC counts), changes in estimated RGC counts correspond to relatively smaller changes in MD (continuous line) and relatively larger changes in average RNFL thickness (dashed line). At advanced stages of damage (low RGC counts), changes in estimated RGC counts correspond to relatively large changes in MD, but only small changes in average RNFL thickness.

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