Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Apr 2;13(4):27.
doi: 10.1167/tvst.13.4.27.

Anatomical Features can Affect OCT Measures Used for Clinical Decisions and Clinical Trial Endpoints

Donald C Hood  1   2 , Sol La Bruna  3 , Mary Durbin  4 , Chris Lee  4 , Yi S Hsiao  4 , Carlos G De Moraes  2 , Emmanouil Tsamis  1   2
Affiliations

Anatomical Features can Affect OCT Measures Used for Clinical Decisions and Clinical Trial Endpoints

Donald C Hood et al. Transl Vis Sci Technol. .

Abstract

Purpose: To understand the association between anatomical parameters of healthy eyes and optical coherence tomography (OCT) circumpapillary retinal nerve fiber layer (cpRNFL) thickness measurements.

Methods: OCT cpRNFL thickness was obtained from 396 healthy eyes in a commercial reference database (RDB). The temporal quadrant (TQ), superior quadrant (SQ), inferior quadrant (IQ), and global (G) cpRNFL thicknesses were analyzed. The commercial OCT devices code these values based on percentiles (red, <1%; yellow, ≥1% and <5%), after taking age and disc area into consideration. Four anatomical parameters were assessed: fovea-to-disc distance, an estimate of axial length, and the locations of the superior and the inferior peaks of the cpRNFL thickness curve. Pearson correlation values were obtained for the parameters and the thickness measures of each of the four cpRNFL regions, and t-tests were performed between the cpRNFL thicknesses coded as abnormal (red or yellow, <5%) versus normal (≥5%).

Results: For each of the four anatomical parameters, the correlation with the thickness of one or more of the TQ, SQ, IQ, and G regions exceeded the correlation with age or disc area. All four parameters were significantly (P < 0.001) associated with the abnormal cpRNFL values. The significant parameters were not the same for the different regions; for example, a parameter could be negatively correlated for the TQ but positively correlated with the SQ or IQ.

Conclusions: In addition to age and disc area, which are used for inferences in normative databases, four anatomical parameters are associated with cpRNFL thickness.

Translational relevance: Taking these additional anatomical parameters into consideration should aid diagnostic accuracy.

PubMed Disclaimer

Conflict of interest statement

Disclosure: D.C. Hood, Heidelberg Engineering (F, C, R), Novartis (C), Topcon (F, C, R); S. La Bruna, None; M. Durbin, Topcon (E); C. Lee, Topcon (E); Y.S. Hsiao, Topcon (E); C.G. De Moraes, Carl Zeiss Meditec (C, R), Heidelberg Engineering (C,R), Novartis (C), Ora Clinical (E), Perfuse Therapeutics (C), Reichert (C, R), Thea Pharma (C), Topcon (C); E. Tsamis, Topcon (R)

Figures

Figure 1.
Figure 1.
(A) The commercial OCT report (Hood Report), for one of the eyes in the Maestro RDB. (B) The numbers indicate the cpRNFL thickness (µm) for each quadrant of the cpRNFL thickness, and the colors indicate the percentile of the thickness after correction for age and disc area: red, <1%; yellow, ≥1% and <5%; green, ≥5% and <99%; and white, ≥99%. (C) An enlarged version of the cpRNFL thickness map in panel (A) with the location of the superior (S-Peak) and inferior (I-Peak) peaks of the cpRNFL curves indicated by the arrows.
Figure 2.
Figure 2.
Scatterplots for the TQ thickness versus age (A), disc area (B), fovea-to-disc distance (C), estimate of the axial length (D), location of the superior peak (E), and location of the inferior peak (F) of the cpRNFL curve. The symbols indicate eyes in the <1% (red), ≥1% and <5% (black), and ≥5% (green) percentiles, and the red lines are the best-fitting linear regression line. The black curve is the best-fitting exponential function.
Figure 3.
Figure 3.
Same as Figure 2 for the superior quadrant (SQ).
Figure 4.
Figure 4.
Same as Figure 2 for the inferior quadrant (IQ).
Figure 5.
Figure 5.
Same as Figure 2 for the global (G) cpRNFL.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Schuman JS, Hee MR, Puliafito CA, et al. .. Quantification of nerve fiber layer thickness in normal and glaucomatous eyes using optical coherence tomography. Arch Ophthalmol. 1995; 113(5): 586–596, doi:10.1001/archopht.1995.01100050054031. - DOI - PubMed
    1. Zangwill LM, Williams J, Berry CC, Knauer S, Weinreb RN.. A comparison of optical coherence tomography and retinal nerve fiber layer photography for detection of nerve fiber layer damage in glaucoma. Ophthalmology. 2000; 107(7): 1309–1315, doi:10.1016/S0161-6420(00)00168-8. - DOI - PubMed
    1. Bowd C, Zangwill LM, Berry CC, et al. .. Detecting early glaucoma by assessment of retinal nerve fiber layer thickness and visual function. Invest Ophthalmol Vis Sci. 2001; 42(9): 1993–2003. - PubMed
    1. Kanamori A, Nakamura M, Escano MFT, Seya R, Maeda H, Negi A.. Evaluation of the glaucomatous damage on retinal nerve fiber layer thickness measured by optical coherence tomography. Am J Ophthalmol. 2003; 135(4): 513–520, doi:10.1016/S0002-9394(02)02003-2. - DOI - PubMed
    1. Nouri-Mahdavi K, Hoffman D, Tannenbaum DP, Law SK, Caprioli J.. Identifying early glaucoma with optical coherence tomography. Am J Ophthalmol. 2004; 137(2): 228–235, doi:10.1016/j.ajo.2003.09.004. - DOI - PubMed

Publication types