Purpose: To compare various displacement models using midget retinal ganglion cell to cone (mRGC:C) ratios and to determine viability of estimating RGC counts from optical coherence tomography (OCT)–derived ganglion cell–inner plexiform layer (GCIPL) measurements. Methods: Four Drasdo model variations were applied to macular visual field (VF) stimulus locations: (1) using meridian-specific Henle fiber length along the stimulus circumference; (2) using meridian-specific differences in RGC receptive field and counts along the stimulus circumference; (3) per method (2), averaged across principal merid-ians; and (4) per method (3), with the stimulus center displaced only. The Sjöstrand model was applied (5) along the stimulus circumference and (6) to the stimulus center only. Eccentricity-dependent mRGC:C ratios were computed over displaced areas, with comparisons to previous models using sum of squares of the residuals (SSR) and root mean square error (RMSE). RGC counts estimated from OCT-derived ganglion cell layer (GCL) and GCIPL measurements, from 143 healthy participants, were compared using Bland–Altman analyses. Results: Methods 1, 2, and 5 produced mRGC:C ratios most consistent with previous models (SSR 3.82, 4.07, and 3.02; RMSE 0.22, 0.23, and 0.20), while central mRGC:C ratios were overestimated by method 3 and underestimated by methods 4 and 6. RGC counts predicted from GCIPL measurements were within 16% of GCL-based counts, with no notable bias with increasing RGC counts. Conclusions: Sjöstrand displacement and meridian-specific Drasdo displacement applied to VF stimulus circumferences produce mRGC:C ratios consistent with previous models. RGC counts can be estimated from OCT-derived GCIPL measurements. Translational Relevance: Implementing appropriate displacement methods and deriv-ing RGC estimates from relevant OCT parameters enables calculation of the number of RGCs responding to VF stimuli from commercial instrumentation.
CITATION STYLE
Tong, J., Phu, J., Alonso-Caneiro, D., Khuu, S. K., & Kalloniatis, M. (2022). Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness. Translational Vision Science and Technology, 11(5). https://doi.org/10.1167/tvst.11.5.13
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