Quantification of Fundus Autofluorescence Features in a Molecularly Characterized Cohort of >3500 Patients with Inherited Retinal Disease from the United Kingdom.

12/11/2024

Ophthalmology science

Authors: William A Woof, Thales A C de Guimarães, Saoud Al-Khuzaei, Malena Daich Varela, Sagnik Sen, Pallavi Bagga, Bernardo Mendes, Mital Shah, Paula Burke, David Parry, Siying Lin, Gunjan Naik, Biraja Ghoshal, Bart J Liefers, Dun Jack Fu, Michalis Georgiou, Quang Nguyen, Alan Sousa da Silva, Yichen Liu, Yu Fujinami-Yokokawa, Dayyanah Sumodhee, Praveen Patel, Jennifer Furman, Ismail Moghul, Mariya Moosajee, Juliana Sallum, Samantha R De Silva, Birgit Lorenz, Frank G Holz, Kaoru Fujinami, Andrew R Webster, Omar A Mahroo, Susan M Downes, Savita Madhusudhan, Konstantinos Balaskas, Michel Michaelides, Nikolas Pontikos

PURPOSE: To quantify relevant fundus autofluorescence (FAF) features cross-sectionally and longitudinally in a large cohort of patients with inherited retinal diseases (IRDs).

DESIGN: Retrospective study of imaging data.

PARTICIPANTS: Patients with a clinical and molecularly confirmed diagnosis of IRD who have undergone 55° FAF imaging at Moorfields Eye Hospital (MEH) and the Royal Liverpool Hospital 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 6 graders in a subset of patients based on a defined grading protocol to produce segmentation masks to train an artificial intelligence model, AIRDetect, which was then applied to the entire imaging data set.

MAIN OUTCOME MEASURES: Quantitative FAF features, including area and vessel metrics, were analyzed cross-sectionally by gene and age, and longitudinally. AIRDetect feature segmentation and detection were validated with Dice score and precision/recall, respectively.

RESULTS: A total of 45 749 FAF images from 3606 patients with IRD from MEH covering 170 genes were automatically segmented using AIRDetect. Model-grader Dice scores for the disc, hypo-AF, hyper-AF, ring, and vessels were, respectively, 0.86, 0.72, 0.69, 0.68, and 0.65. Across patients at presentation, the 5 genes with the largest hypo-AF areas were , , , , and , with mean per-patient areas of 43.72, 29.57, 20.07, 19.65, and 16.92 mm, respectively. The 5 genes with the largest hyper-AF areas were , , , , and , with mean areas of 0.50, 047, 0.44, 0.38, and 0.33 mm, respectively. The 5 genes with the largest ring areas were , , , and , with mean areas of 3.60, 2.90, 2.89, 2.56, and 2.20 mm, respectively. Vessel density was found to be highest in , , , , and (11.0%, 10.4%, 10.1%, 10.1%, 9.2%) and was lower in retinitis pigmentosa (RP) and Leber congenital amaurosis genes. Longitudinal analysis of decreasing ring area in 4 RP genes (, , , and ) found to be the fastest progressor at -0.178 mm/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.

FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

PMID: 39896422