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Michalis Georgiou, Katie M. Litts, Navjit Singh, Thomas Kane, Emily J. Patterson, Nashila Hirji, Angelos Kalitzeos, Alfredo Dubra, Michel Michaelides, Joseph Carroll; Intraobserver Repeatability and Interobserver Reproducibility of Foveal Cone Density Measurements in CNGA3- and CNGB3-Associated Achromatopsia. Trans. Vis. Sci. Tech. 2020;9(7):37. doi: https://doi.org/10.1167/tvst.9.7.37.
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© ARVO (1962-2015); The Authors (2016-present)
To examine repeatability and reproducibility of foveal cone density measurements in patients with CNGA3- and CNGB3-associated achromatopsia (ACHM) using split-detection adaptive optics scanning light ophthalmoscopy (AOSLO).
Thirty foveae from molecularly confirmed subjects with ACHM, half of whom harbored disease-causing variants in CNGA3 and half in CNGB3, underwent nonconfocal split-detection AOSLO imaging. Cone photoreceptors within the manually delineated rod-free zone were manually identified twice by two independent observers. The coordinates of the marked cones were used for quantifying foveal cone density. Cone density and difference maps were generated to compare cone topography between trials.
We observed excellent intraobserver repeatability in foveal cone density estimates, with intraclass correlation coefficients (ICCs) ranging from 0.963 to 0.991 for CNGA3 and CNGB3 subjects. Interobserver reproducibility was also excellent for both CNGA3 (ICC = 0.952; 95% confidence interval [CI], 0.903–1.0) and CNGB3 (ICC = 0.968; 95% CI, 0.935–1.0). However, Bland-Altman analysis revealed bias between observers.
Foveal cone density can be measured using the described method with good repeatability and reproducibility both for CNGA3- and CNGB3-associated ACHM. Any degree of bias observed among the observers is of uncertain clinical significance but should be evaluated on a study-specific basis.
This approach could be used to explore disease natural history, as well as to facilitate stratification of patients and monitor efficacy of interventions for ongoing and upcoming ACHM gene therapy trials.
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