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Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness

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 variatio...

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Autores principales: Tong, Janelle, Phu, Jack, Alonso-Caneiro, David, Khuu, Sieu K., Kalloniatis, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9123515/
https://www.ncbi.nlm.nih.gov/pubmed/35575777
http://dx.doi.org/10.1167/tvst.11.5.13
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author Tong, Janelle
Phu, Jack
Alonso-Caneiro, David
Khuu, Sieu K.
Kalloniatis, Michael
author_facet Tong, Janelle
Phu, Jack
Alonso-Caneiro, David
Khuu, Sieu K.
Kalloniatis, Michael
author_sort Tong, Janelle
collection PubMed
description 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 meridians; 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 deriving RGC estimates from relevant OCT parameters enables calculation of the number of RGCs responding to VF stimuli from commercial instrumentation.
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spelling pubmed-91235152022-05-22 Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness Tong, Janelle Phu, Jack Alonso-Caneiro, David Khuu, Sieu K. Kalloniatis, Michael Transl Vis Sci Technol Article 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 meridians; 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 deriving RGC estimates from relevant OCT parameters enables calculation of the number of RGCs responding to VF stimuli from commercial instrumentation. The Association for Research in Vision and Ophthalmology 2022-05-16 /pmc/articles/PMC9123515/ /pubmed/35575777 http://dx.doi.org/10.1167/tvst.11.5.13 Text en Copyright 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
spellingShingle Article
Tong, Janelle
Phu, Jack
Alonso-Caneiro, David
Khuu, Sieu K.
Kalloniatis, Michael
Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness
title Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness
title_full Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness
title_fullStr Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness
title_full_unstemmed Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness
title_short Prediction of Retinal Ganglion Cell Counts Considering Various Displacement Methods From OCT-Derived Ganglion Cell–Inner Plexiform Layer Thickness
title_sort prediction of retinal ganglion cell counts considering various displacement methods from oct-derived ganglion cell–inner plexiform layer thickness
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9123515/
https://www.ncbi.nlm.nih.gov/pubmed/35575777
http://dx.doi.org/10.1167/tvst.11.5.13
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