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PURPOSE: To analyze the genetics, clinical characteristics, and natural history of PDE6A-associated retinitis pigmentosa. DESIGN: Retrospective, longitudinal, observational cohort study. PARTICIPANTS: Patients with molecularly confirmed PDE6A-associated retinal dystrophy in a single tertiary referral center. METHODS: Review of medical records and retinal imaging, including fundus autofluorescence (FAF) imaging and spectral-domain optical coherence tomography (SD-OCT). Genetic results were reviewed, and the detected variants were assessed. RESULTS: Sixteen patients (32 eyes) were identified and evaluated longitudinally. Genetic analysis identified 14 variants in the PDE6A gene, including 8 novel variants. The mean age (±SD, range) was 34.8 years (± 17.4, 12 - 76) at baseline, with a mean follow-up time of 4.8 years. Best-corrected visual acuity (BCVA) was 0.45 ± 0.45 LogMAR (range 0.0 - 1.6) at baseline and 0.65 ± 0.7 LogMAR (range 0.0 - 2.3) at the last visit. BCVA was similar among eyes in 88% of patients. A hyperautofluorescent ring was observed on FAF in 50% and 44% of the eyes at baseline and follow up visit respectively, with a mean area of 9.7 ± 4.5mm2 at baseline and mean of 8.6 ± 4.8 mm2 at the follow-up visit. Mean horizontal ellipsoid zone width (EZW) at baseline was 1765 ± 1093 µm, which decreased to 1580 ± 1077 µm at follow up. Eighteen eyes exhibited cystoid macular oedema at baseline (56%), and 17 eyes (53%) at follow-up. There were statistically significant changes during the follow-up period in terms of BCVA, hyperautoflouroscent ring area and the EZW. CONCLUSIONS: This study highlights the natural history of PDE6A-retinopathy. The majority of the patients in this cohort had mild BCVA loss, and slowly progressive disease, based on FAF and OCT measurements.
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Purpose: To quantify relevant fundus autofluorescence (FAF) image features cross-sectionally and longitudinally in a large cohort of inherited retinal diseases (IRDs) patients. Design: Retrospective study of imaging data (55-degree blue-FAF on Heidelberg Spectralis) from patients. Participants: Patients with a clinical and molecularly confirmed diagnosis of IRD who have undergone FAF 55-degree imaging at Moorfields Eye Hospital (MEH) and the Royal Liverpool Hospital (RLH) between 2004 and 2019. Methods: Five FAF features of interest were defined: vessels, optic disc, perimacular ring of increased signal (ring), relative hypo-autofluorescence (hypo-AF) and hyper-autofluorescence (hyper-AF). Features were manually annotated by six graders in a subset of patients based on a defined grading protocol to produce segmentation masks to train an AI model, AIRDetect, which was then applied to the entire imaging dataset. Main Outcome Measures: Quantitative FAF imaging features including area in mm 2 and vessel metrics, were analysed cross-sectionally by gene and age, and longitudinally to determine rate of progression. AIRDetect feature segmentation and detection were validated with Dice score and precision/recall, respectively. Results: A total of 45,749 FAF images from 3,606 IRD patients from MEH covering 170 genes were automatically segmented using AIRDetect. Model-grader Dice scores for disc, hypo-AF, hyper-AF, ring and vessels were respectively 0.86, 0.72, 0.69, 0.68 and 0.65. The five genes with the largest hypo-AF areas were CHM , ABCC6 , ABCA4 , RDH12 , and RPE65 , with mean per-patient areas of 41.5, 30.0, 21.9, 21.4, and 15.1 mm 2 . The five genes with the largest hyper-AF areas were BEST1 , CDH23 , RDH12 , MYO7A , and NR2E3 , with mean areas of 0.49, 0.45, 0.44, 0.39, and 0.34 mm 2 respectively. The five genes with largest ring areas were CDH23 , NR2E3 , CRX , EYS and MYO7A, with mean areas of 3.63, 3.32, 2.84, 2.39, and 2.16 mm 2 . Vessel density was found to be highest in EFEMP1 , BEST1 , TIMP3 , RS1 , and PRPH2 (10.6%, 10.3%, 9.8%, 9.7%, 8.9%) and was lower in Retinitis Pigmentosa (RP) and Leber Congenital Amaurosis genes. Longitudinal analysis of decreasing ring area in four RP genes ( RPGR, USH2A, RHO, EYS ) found EYS to be the fastest progressor at -0.18 mm 2 /year. Conclusions: We have conducted the first large-scale cross-sectional and longitudinal quantitative analysis of FAF features across a diverse range of IRDs using a novel AI approach.