{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T22:24:14Z","timestamp":1781907854265,"version":"3.54.5"},"posted":{"date-parts":[[2025,7,3]]},"group-title":"Ophthalmology","reference-count":47,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,7,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>To quantify spectral-domain optical coherence tomography (SD-OCT) images cross-sectionally and longitudinally in a large cohort of molecularly characterized patients with inherited retinal disease (IRDs) from the UK.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Design<\/jats:title>\n                  <jats:p>Retrospective study of imaging data.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Participants<\/jats:title>\n                  <jats:p>Patients with a clinical and molecularly confirmed diagnosis of IRD who have undergone macular SD-OCT imaging at Moorfields Eye Hospital (MEH) between 2011 and 2019. We retrospectively identified 4,240 IRD patients from the MEH database (198 distinct IRD genes), including 69,664 SD-OCT macular volumes.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>Eight features of interest were defined: retina, fovea, intraretinal cystic spaces (ICS), subretinal fluid (SRF), subretinal hyper-reflective material (SHRM), pigment epithelium detachment (PED), ellipsoid zone loss (EZ-loss) and retinal pigment epithelium loss (RPE-loss). Manual annotations of five b-scans per SD-OCT volume was performed for the retinal features by four graders based on a defined grading protocol. A total of 1,749 b-scans from 360 SD-OCT volumes across 275 patients were annotated for the eight retinal features for training and testing of a neural-network-based segmentation model, AIRDetect-OCT, which was then applied to the entire imaging dataset.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Main Outcome Measures<\/jats:title>\n                  <jats:p>Performance of AIRDetect-OCT, comparing to inter-grader agreement was evaluated using Dice score on a held-out dataset. Feature prevalence, volume and area were analysed cross-sectionally and longitudinally.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    The inter-grader Dice score for manual segmentation was \u226590% for retina, ICS, SRF, SHRM and PED, &gt;77% for both EZ-loss and RPE-loss. Model-grader agreement was &gt;80% for segmentation of retina, ICS, SRF, SHRM, and PED, and &gt;68% for both EZ-loss and RPE-loss. Automatic segmentation was applied to 272,168 b-scans across 7,405 SD-OCT volumes from 3,534 patients encompassing 176 unique genes. Accounting for age, male patients exhibited significantly more EZ-loss (19.6mm\n                    <jats:sup>2<\/jats:sup>\n                    vs 17.9mm\n                    <jats:sup>2<\/jats:sup>\n                    , p&lt;2.8\u00d710\n                    <jats:sup>-4<\/jats:sup>\n                    ) and RPE-loss (7.79mm\n                    <jats:sup>2<\/jats:sup>\n                    vs 6.15mm\n                    <jats:sup>2<\/jats:sup>\n                    , p&lt;3.2\u00d710\n                    <jats:sup>-6<\/jats:sup>\n                    ) than females. RPE-loss was significantly higher in Asian patients than other ethnicities (9.37mm\n                    <jats:sup>2<\/jats:sup>\n                    vs 7.29mm\n                    <jats:sup>2<\/jats:sup>\n                    , p&lt;0.03). ICS average total volume was largest in\n                    <jats:italic>RS1<\/jats:italic>\n                    (0.47mm\n                    <jats:sup>3<\/jats:sup>\n                    ) and\n                    <jats:italic>NR2E3<\/jats:italic>\n                    (0.25mm\n                    <jats:sup>3<\/jats:sup>\n                    ), SRF in\n                    <jats:italic>BEST1<\/jats:italic>\n                    (0.21mm\n                    <jats:sup>3<\/jats:sup>\n                    ) and PED in\n                    <jats:italic>EFEMP1<\/jats:italic>\n                    (0.34mm\n                    <jats:sup>3<\/jats:sup>\n                    ).\n                    <jats:italic>BEST1<\/jats:italic>\n                    and\n                    <jats:italic>PROM1<\/jats:italic>\n                    showed significantly different patterns of EZ-loss (p&lt;10\n                    <jats:sup>-4<\/jats:sup>\n                    ) and RPE-loss (p&lt;0.02) comparing the dominant to the recessive forms. Sectoral analysis revealed significantly increased EZ-loss in the inferior quadrant compared to superior quadrant for\n                    <jats:italic>RHO<\/jats:italic>\n                    (\u0394=-0.414 mm\n                    <jats:sup>2<\/jats:sup>\n                    , p=0.036) and EYS (\u0394=-0.908 mm\n                    <jats:sup>2<\/jats:sup>\n                    , p=1.5\u00d710\n                    <jats:sup>-4<\/jats:sup>\n                    ). In\n                    <jats:italic>ABCA4<\/jats:italic>\n                    retinopathy, more severe genotypes (group A) were associated with faster progression of EZ-loss (2.80\u00b10.62 mm\n                    <jats:sup>2<\/jats:sup>\n                    \/yr), whilst the p.(Gly1961Glu) variant (group D) was associated with slower progression (0.56 \u00b10.18 mm\n                    <jats:sup>2<\/jats:sup>\n                    \/yr). There were also sex differences within groups with males in group A experiencing significantly faster rates of progression of RPE-loss (2.48 \u00b11.40 mm\n                    <jats:sup>2<\/jats:sup>\n                    \/yr vs 0.87 \u00b10.62 mm\n                    <jats:sup>2<\/jats:sup>\n                    \/yr, p=0.047), but lower rates in groups B, C, and D.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>AIRDetect-OCT, a novel deep learning algorithm, enables large-scale OCT feature quantification in IRD patients uncovering cross-sectional and longitudinal phenotype correlations with demographic and genotypic parameters.<\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2025.07.03.25330767","type":"posted-content","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T20:40:26Z","timestamp":1751575226000},"source":"Crossref","is-referenced-by-count":3,"title":["Quantification of Optical Coherence Tomography Features in &gt;3500 Patients with Inherited Retinal Disease Reveals Novel Genotype-Phenotype Associations"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7555-329X","authenticated-orcid":false,"given":"William","family":"Woof","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7936-6851","authenticated-orcid":false,"given":"Thales A. 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