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. 2023 May 23;13(2):168–183. doi: 10.4103/tjo.TJO-D-23-00022

Table 1.

Summary of studies using fundus photographs for predicting glaucoma progression

Year First author Aim Outcome Dataset Model Input Output Results
2020 Thakur et al.[24] Predict glaucoma before onset AUC 66,721 fundus photos, 3272 eyes, 1636 subjects MobileNetV2 Fundus photo Glaucoma prediction before onset AUC for onset 4–7 years before disease: 0.77 (95% CI: 0.75–0.79). AUC for onset 1–3 years before disease: 0.88 (95% CI: 0.86–0.91)
2021 Medeiros et al.[25] Use fundus photo to predict glaucoma progression (RNFL loss >1 µm/year) AROC 86,123 pairs, 8831 eyes, 5529 subjects ResNet 50 Fundus photo Progressor versus no progressor RNFL predictions AROC: 0.86 (95% CI: 0.83–0.88) to discriminate progressors from nonprogressors. For detecting fast progressors (slope faster than 2 µm/year), AROC: 0.96 (95% CI: 0.94–0.98), sensitivity: 97% and specificity: 80%
2022 Li et al.[26] Predict progression from fundus images (3 experts defined progression) AUROC 17,497 eyes, 9346 subjects PredictNet (based on ConvNet) Fundus photo Glaucoma progression Glaucoma progression: AUROCs of 0.87 (0.81–0.92) and 0.88 (0.83–0.94) in two test datasets
2023 Lin et al.[27] NTG progression using retinal caliber analysis C statistic of cox regression model 197 patients SIVA-DLS Fundus photo features + other predictors CRAE/CRVE from DL algorithm CRAE + CRVE + age + gender + IOP + MOPP + SBP have C=0.85 for VF deterioration and C=0.703 for progressive RNFL thinning

AUC/AUROC=Area under the receiver operating characteristic curve, CRAE=Central retinal arteriolar equivalent, CRVE=Central retinal venular equivalent, IOP=Intraocular pressure, MOPP=Mean ocular perfusion pressure, RNFL=Retinal nerve fibre layer, DL=Deep learning, SIVA-DLS=Singapore I vessel analyzer DL system, SBP=Systolic blood pressure, VF=Visual field, NTG=Normal tension glaucoma, CI=Confidence interval