The British journal of ophthalmology · 2019
Repeatability of automated leakage quantification and microaneurysm identification utilising an analysis platform for ultra-widefield fluorescein angiography.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Jiang Alice, Srivastava Sunil, Figueiredo Natalia, Babiuch Amy, Hu Ming, Reese Jamie, Ehlers Justis P
Аннотация
UNLABELLED: Background/aimsUltra-widefield fluorescein angiography (UWFA) provides unique opportunities for panretinal assessment of retinal diseases. The objective quantification of UWFA features is a labour-intensive manual process, limiting its utility. The present study assesses the consistency/repeatability of an automated assessment platform for the characterisation of retinal vascular features, quantification of microaneurysms (MA) and leakage foci in UWFA images.
METHODS: An Institutional Review Board-approved retrospective image analysis study was performed on UWFA images. For each eye, two arteriovenous-phase images and two late-phase images were selected. Automated assessment was performed for retinal vascular features, MA identification and leakage segmentation. Panretinal and zonal assessment of metrics was performed.
RESULTS: There was a significant correlation between paired time points for retinal vessel area and vessel length on early images (Pearson r=0.92, p<0.0001; Pearson r=0.94, p<0.0001) and late images (Pearson r=0.92, p<0.0001; Pearson r=0.92, p<0.0001, respectively). Panretinal and zonal MA counts demonstrated high repeatability between images (all p<0.0001). Similarly, panretinal leakage area and zonal leakage areas were highly correlated (all p<0.001).
CONCLUSION: This automated algorithm demonstrated very strong intrastudy correlation between paired time points in the same phases of the angiogram for quantifying retinal vascular characteristics, MA count and leakage parameters in UWFA images. These findings suggest significant flexibility in the platform for consistency in evaluating metrics over time and is encouraging for longitudinal assessment opportunities.
METHODS: An Institutional Review Board-approved retrospective image analysis study was performed on UWFA images. For each eye, two arteriovenous-phase images and two late-phase images were selected. Automated assessment was performed for retinal vascular features, MA identification and leakage segmentation. Panretinal and zonal assessment of metrics was performed.
RESULTS: There was a significant correlation between paired time points for retinal vessel area and vessel length on early images (Pearson r=0.92, p<0.0001; Pearson r=0.94, p<0.0001) and late images (Pearson r=0.92, p<0.0001; Pearson r=0.92, p<0.0001, respectively). Panretinal and zonal MA counts demonstrated high repeatability between images (all p<0.0001). Similarly, panretinal leakage area and zonal leakage areas were highly correlated (all p<0.001).
CONCLUSION: This automated algorithm demonstrated very strong intrastudy correlation between paired time points in the same phases of the angiogram for quantifying retinal vascular characteristics, MA count and leakage parameters in UWFA images. These findings suggest significant flexibility in the platform for consistency in evaluating metrics over time and is encouraging for longitudinal assessment opportunities.