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1. Development and validation of a deep-learning model to predict 10-year atherosclerotic cardiovascular disease risk from retinal images using the UK Biobank and EyePACS 10K datasets.

Author

Vaghefi, Ehsan, Squirrell, David, Yang, Song, An, Songyang, Xie, Li, Durbin, Mary, Hou, Huiyuan, Marshall, John, Shreibati, Jacqueline, McConnell, Michael, and Budoff, Matthew

Subjects
Artificial intelligence, Cardiovascular disease risk, Pooled cohort equation, Retinal imaging
Abstract

BACKGROUND: Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death globally, and early detection of high-risk individuals is essential for initiating timely interventions. The authors aimed to develop and validate a deep learning (DL) model to predict an individuals elevated 10-year ASCVD risk score based on retinal images and limited demographic data. METHODS: The study used 89,894 retinal fundus images from 44,176 UK Biobank participants (96% non-Hispanic White, 5% diabetic) to train and test the DL model. The DL model was developed using retinal images plus age, race/ethnicity, and sex at birth to predict an individuals 10-year ASCVD risk score using the pooled cohort equation (PCE) as the ground truth. This model was then tested on the US EyePACS 10K dataset (5.8% non-Hispanic White, 99.9% diabetic), composed of 18,900 images from 8969 diabetic individuals. Elevated ASCVD risk was defined as a PCE score of ≥7.5%. RESULTS: In the UK Biobank internal validation dataset, the DL model achieved an area under the receiver operating characteristic curve of 0.89, sensitivity 84%, and specificity 90%, for detecting individuals with elevated ASCVD risk scores. In the EyePACS 10K and with the addition of a regression-derived diabetes modifier, it achieved sensitivity 94%, specificity 72%, mean error -0.2%, and mean absolute error 3.1%. CONCLUSION: This study demonstrates that DL models using retinal images can provide an additional approach to estimating ASCVD risk, as well as the value of applying DL models to different external datasets and opportunities about ASCVD risk assessment in patients living with diabetes.

Published
2024

2. Replacing the Framingham-based equation for prediction of cardiovascular disease risk and adverse outcome by using artificial intelligence and retinal imaging

Author

Vaghefi, Ehsan, Squirrell, David, An, Songyang, Yang, Song, and Marshall, John

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Purpose: To create and evaluate the accuracy of an artificial intelligence Deep learning platform (ORAiCLE) capable of using only retinal fundus images to predict both an individuals overall 5 year cardiovascular risk (CVD) and the relative contribution of the component risk factors that comprise this risk. Methods: We used 165,907 retinal images from a database of 47,236 patient visits. Initially, each image was paired with biometric data age, ethnicity, sex, presence and duration of diabetes a HDL/LDL ratios as well as any CVD event wtihin 5 years of the retinal image acquisition. A risk score based on Framingham equations was calculated. The real CVD event rate was also determined for the individuals and overall population. Finally, ORAiCLE was trained using only age, ethnicity, sex plus retinal images. Results: Compared to Framingham-based score, ORAiCLE was up to 12% more accurate in prediciting cardiovascular event in he next 5-years, especially for the highest risk group of people. The reliability and accuracy of each of the restrictive models was suboptimal to ORAiCLE performance ,indicating that it was using data from both sets of data to derive its final results. Conclusion: Retinal photography is inexpensive and only minimal training is required to acquire them as fully automated, inexpensive camera systems are now widely available. As such, AI-based CVD risk algorithms such as ORAiCLE promise to make CV health screening more accurate, more afforadable and more accessible for all. Furthermore, ORAiCLE unique ability to assess the relative contribution of the components that comprise an individuals overall risk would inform treatment decisions based on the specific needs of an individual, thereby increasing the likelihood of positive health outcomes., Comment: inaccuracies

Published
2022

4. A multi-center prospective evaluation of THEIA to detect diabetic retinopathy (DR) and diabetic macular edema (DME) in the New Zealand screening program

Author

Vaghefi, Ehsan, Yang, Song, Xie, Li, Han, David, and Squirrell, David

Subjects
Physics - Medical Physics, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Purpose: to assess the efficacy of THEIA, an artificial intelligence for screening diabetic retinopathy in a multi-center prospective study. To validate the potential application of THEIA as clinical decision making assistant in a national screening program. Methods: 902 patients were recruited from either an urban large eye hospital, or a semi-rural optometrist led screening provider, as they were attending their appointment as part of New Zealand Diabetic Screening programme. These clinics used a variety of retinal cameras and a range of operators. The de-identified images were then graded independently by three senior retinal specialists, and final results were aggregated using New Zealand grading scheme, which is then converted to referable\non-referable and Healthy\mild\more than mild\vision threatening categories. Results: compared to ground truth, THEIA achieved 100% sensitivity and [95.35%-97.44%] specificity, and negative predictive value of 100%. THEIA also did not miss any patients with more than mild or vision threatening disease. The level of agreement between the clinicians and the aggregated results was (k value: 0.9881, 0.9557, and 0.9175), and the level of agreement between THEIA and the aggregated labels was (k value: 0.9515). Conclusion: Our multi-centre prospective trial showed that THEIA does not miss referable disease when screening for diabetic retinopathy and maculopathy. It also has a very high level of granularity in reporting the disease level. Since THEIA is being tested on a variety of cameras, operating in a range of clinics (rural\urban, ophthalmologist-led\optometrist-led), we believe that it will be a suitable addition to a public diabetic screening program., Comment: Word count: 3623 Figures: 3 Tables: 6 Supplementary Tables: 7

Published
2021

9. Validation of neuron activation patterns for artificial intelligence models in oculomics.

Author

An, Songyang and Squirrell, David

Subjects
*SYSTOLIC blood pressure, *ARTIFICIAL intelligence, *RESEARCH personnel, *RETINA, *PHENOTYPES
Abstract

Recent advancements in artificial intelligence (AI) have prompted researchers to expand into the field of oculomics; the association between the retina and systemic health. Unlike conventional AI models trained on well-recognized retinal features, the retinal phenotypes that most oculomics models use are more subtle. Consequently, applying conventional tools, such as saliency maps, to understand how oculomics models arrive at their inference is problematic and open to bias. We hypothesized that neuron activation patterns (NAPs) could be an alternative way to interpret oculomics models, but currently, most existing implementations focus on failure diagnosis. In this study, we designed a novel NAP framework to interpret an oculomics model. We then applied our framework to an AI model predicting systolic blood pressure from fundus images in the United Kingdom Biobank dataset. We found that the NAP generated from our framework was correlated to the clinically relevant endpoint of cardiovascular risk. Our NAP was also able to discern two biologically distinct groups among participants who were assigned the same predicted systolic blood pressure. These results demonstrate the feasibility of our proposed NAP framework for gaining deeper insights into the functioning of oculomics models. Further work is required to validate these results on external datasets. [ABSTRACT FROM AUTHOR]

Published
2024
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12. Automation of Macular Degeneration Classification in the AREDS Dataset, Using a Novel Neural Network Design

Author

Xie,Li, Vaghefi,Ehsan, Yang,Song, Han,David, Marshall,John, Squirrell,David, Xie,Li, Vaghefi,Ehsan, Yang,Song, Han,David, Marshall,John, and Squirrell,David

Abstract

Li Xie,1 Ehsan Vaghefi,1,2 Song Yang,1 David Han,1,2 John Marshall,3 David Squirrell1,4 1Toku Eyes Limited, Auckland, New Zealand; 2School of Optometry and Vision Science, The University of Auckland, Auckland, New Zealand; 3Institute of Ophthalmology, UCL, London, UK; 4Department of Ophthalmology, Auckland District Health Board, Auckland, New ZealandCorrespondence: Ehsan Vaghefi, Tel +6493737599, Email e.vaghefi@auckland.ac.nzPurpose: To create an ensemble of Convolutional Neural Networks (CNNs), capable of detecting and stratifying the risk of progressive age-related macular degeneration (AMD) from retinal photographs.Design: Retrospective cohort study.Methods: Three individual CNNs are trained to accurately detect 1) advanced AMD, 2) drusen size and 3) the presence or otherwise of pigmentary abnormalities, from macular centered retinal images were developed. The CNNs were then arranged in a “cascading” architecture to calculate the Age-related Eye Disease Study (AREDS) Simplified 5-level risk Severity score (Risk Score 0 – Risk Score 4), for test images. The process was repeated creating a simplified binary “low risk” (Scores 0– 2) and “high risk” (Risk Score 3– 4) classification.Participants: There were a total of 188,006 images, of which 118,254 images were deemed gradable, representing 4591 patients, from the AREDS1 dataset. The gradable images were split into 50%/25%/25% ratios for training, validation and test purposes.Main Outcome Measures: The ability of the ensemble of CNNs using retinal images to predict an individual’s risk of experiencing progression of their AMD based on the AREDS 5-step Simplified Severity Scale.Results: When assessed against the 5-step Simplified Severity Scale, the results generated by the ensemble of CNN’s achieved an accuracy of 80.43% (quadratic kappa 0.870). When assessed against a simplified binary (Low Risk/High Risk) classification, an accuracy of 98.08%, sensitivity of ≥ 85% and specificity of ≥ 99%

Published
2023

13. Changes in 12-month outcomes over time for age-related macular degeneration, diabetic macular oedema and retinal vein occlusion

Author

Bhandari, Sanjeeb; https://orcid.org/0000-0002-4110-4274, Nguyen, Vuong; https://orcid.org/0000-0001-9070-9803, Hunt, Adrian; https://orcid.org/0000-0002-6261-4679, Gabrielle, Pierre-Henry; https://orcid.org/0000-0002-9688-4845, Viola, Francesco, Mehta, Hemal, Manning, Les, Squirrell, David; https://orcid.org/0000-0002-8393-7100, Arnold, Jennifer, McAllister, Ian L; https://orcid.org/0000-0003-3262-0821, Barthelmes, Daniel; https://orcid.org/0000-0002-5431-4991, Gillies, Mark; https://orcid.org/0000-0001-8580-0274, Bhandari, Sanjeeb; https://orcid.org/0000-0002-4110-4274, Nguyen, Vuong; https://orcid.org/0000-0001-9070-9803, Hunt, Adrian; https://orcid.org/0000-0002-6261-4679, Gabrielle, Pierre-Henry; https://orcid.org/0000-0002-9688-4845, Viola, Francesco, Mehta, Hemal, Manning, Les, Squirrell, David; https://orcid.org/0000-0002-8393-7100, Arnold, Jennifer, McAllister, Ian L; https://orcid.org/0000-0003-3262-0821, Barthelmes, Daniel; https://orcid.org/0000-0002-5431-4991, and Gillies, Mark; https://orcid.org/0000-0001-8580-0274

Abstract

OBJECTIVES To identify whether the outcomes of neovascular age-related macular degeneration (nAMD), diabetic macular oedema (DMO) and retinal vein occlusion (RVO) in routine clinical practice have changed over time. METHODS We analysed 12-month outcomes in treatment-naïve eyes that started aflibercept or ranibizumab for nAMD (3802 eyes), DMO (975 eyes), Branch RVO (BRVO, 357 eyes), Central RVO (CRVO, 371 eyes) and Hemi-RVO (HRVO, 54 eyes) from 2015 and 2019 tracked in the prospectively designed observational Fight Retinal Blindness! Registry. RESULTS The mean VA change at 12-month for each year between 2015 and 2019 remained stable or otherwise showed no discernible trends over time in eyes with nAMD (+3.3 to +6 letters), DMO (+3.6 to +6.7 letters) and RVO (+10.3 to +11.7 letters for BRVO, +5.9 to +17.7 letters for CRVO and 10.2 to 20.7 letters for HRVO). The median number of VEGF-inhibitor injections in eyes that completed 12-month follow-up also remained stable at 8-9 for nAMD, 6-7 for DMO, 7-9 for RVO. Fewer eyes (

Published
2023

14. Examination of alternative eGFR definitions on the performance of deep learning models for detection of chronic kidney disease from fundus photographs.

Author

An, Songyang, Vaghefi, Ehsan, Yang, Song, Xie, Li, and Squirrell, David

Subjects
CHRONIC kidney failure, EPIDERMAL growth factor receptors, DEEP learning, CYSTATIN C
Abstract

Deep learning (DL) models have shown promise in detecting chronic kidney disease (CKD) from fundus photographs. However, previous studies have utilized a serum creatinine-only estimated glomerular rate (eGFR) equation to measure kidney function despite the development of more up-to-date methods. In this study, we developed two sets of DL models using fundus images from the UK Biobank to ascertain the effects of using a creatinine and cystatin-C eGFR equation over the baseline creatinine-only eGFR equation on fundus image-based DL CKD predictors. Our results show that a creatinine and cystatin-C eGFR significantly improved classification performance over the baseline creatinine-only eGFR when the models were evaluated conventionally. However, these differences were no longer significant when the models were assessed on clinical labels based on ICD10. Furthermore, we also observed variations in model performance and systemic condition incidence between our study and the ones conducted previously. We hypothesize that limitations in existing eGFR equations and the paucity of retinal features uniquely indicative of CKD may contribute to these inconsistencies. These findings emphasize the need for developing more transparent models to facilitate a better understanding of the mechanisms underpinning the ability of DL models to detect CKD from fundus images. [ABSTRACT FROM AUTHOR]

Published
2023
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16. Changes in 12-month outcomes over time for age-related macular degeneration, diabetic macular oedema and retinal vein occlusion

Author

Bhandari, Sanjeeb, Nguyen, Vuong, Hunt, Adrian, Gabrielle, Pierre-Henry, Viola, Francesco, Mehta, Hemal, Manning, Les, Squirrell, David, Arnold, Jennifer, McAllister, Ian L, Barthelmes, Daniel, Gillies, Mark, University of Zurich, and Bhandari, Sanjeeb

Subjects
10018 Ophthalmology Clinic, 2809 Sensory Systems, Ophthalmology, Settore MED/30 - Malattie Apparato Visivo, 610 Medicine & health, 2731 Ophthalmology
Abstract

Objectives To identify whether the outcomes of neovascular age-related macular degeneration (nAMD), diabetic macular oedema (DMO) and retinal vein occlusion (RVO) in routine clinical practice have changed over time. Methods We analysed 12-month outcomes in treatment-naïve eyes that started aflibercept or ranibizumab for nAMD (3802 eyes), DMO (975 eyes), Branch RVO (BRVO, 357 eyes), Central RVO (CRVO, 371 eyes) and Hemi-RVO (HRVO, 54 eyes) from 2015 and 2019 tracked in the prospectively designed observational Fight Retinal Blindness! Registry. Results The mean VA change at 12-month for each year between 2015 and 2019 remained stable or otherwise showed no discernible trends over time in eyes with nAMD (+3.3 to +6 letters), DMO (+3.6 to +6.7 letters) and RVO (+10.3 to +11.7 letters for BRVO, +5.9 to +17.7 letters for CRVO and 10.2 to 20.7 letters for HRVO). The median number of VEGF-inhibitor injections in eyes that completed 12-month follow-up also remained stable at 8–9 for nAMD, 6–7 for DMO, 7–9 for RVO. Fewer eyes ( Conclusions Treatment patterns and outcomes for nAMD, DMO and RVO in routine clinical practice have stabilised over the past 5 years at levels inferior to those reported by the pivotal phase 3 studies. A conscious effort to treat these conditions more intensively, or with longer lasting agents, would likely improve outcomes further in our patients.

Published
2022

19. Incidence, risk factors and outcomes of submacular haemorrhage with loss of vision in neovascular age-related macular degeneration in daily clinical practice: data from the FRB! registry

Author

Gabrielle, Pierre-Henry, Maitrias, Samuel, Nguyen, Vuong, Arnold, Jennifer J, Squirrell, David, Arnould, Louis, Sanchez-Monroy, Jorge, Viola, Francesco, O'Toole, Louise, Barthelmes, Daniel, Creuzot-Garcher, Catherine, Gillies, Mark, University of Zurich, and Gabrielle, Pierre-Henry

Subjects
10018 Ophthalmology Clinic, 610 Medicine & health, 2731 Ophthalmology
Published
2022

21. Three-year treatment outcomes of Aflibercept versus Ranibizumab for diabetic macular edema:: Data from the Fight Retinal Blindness! Registry

Author

Gabrielle, Pierre-Henry, Nguyen, Vuong, Creuzot-Garcher, Catherine, Arnold, Jennifer J, Mehta, Hemal, Duran, Mónica Asencio, Bougamha, Walid, Carreño, Ester, Viola, Francesco, Squirrell, David, Barthelmes, Daniel, Gillies, Mark, and University of Zurich

Subjects
10018 Ophthalmology Clinic, Diabetic Retinopathy, Recombinant Fusion Proteins, Angiogenesis Inhibitors, 610 Medicine & health, General Medicine, Blindness, 2731 Ophthalmology, Macular Edema, Ophthalmology, Receptors, Vascular Endothelial Growth Factor, Treatment Outcome, Ranibizumab, Intravitreal Injections, Diabetes Mellitus, Humans, Registries, Retrospective Studies
Abstract

Compare the 3-year outcomes of ranibizumab versus aflibercept in eyes with diabetic macular edema in daily practice.This was a retrospective analysis of naive diabetic macular edema eyes starting intravitreal injections of ranibizumab (0.5 mg) or aflibercept (2 mg) from January 1, 2013 to December 31, 2017 that were collected in the Fight Retinal Blindness! Registry.We identified 534 eyes (ranibizumab-267 and aflibercept-267) of 402 patients. The adjusted mean (95% confidence interval) visual acuity change of +1.3 (-0.1 to 4.2) letters in the ranibizumab group and +2.4 (-0.2 to 5.1) letters (P = 0.001) in the aflibercept group at 3 years was not clinically different. However, the adjusted mean CST change seemed to remain significantly different throughout the 3-year period with higher reductions in favor of aflibercept (-87.8 [-108.3 to -67.4] µm for ranibizumab vs. -114.4 [-134.4 to -94.3] for aflibercept; P0.01). When baseline visual impairment was moderate (visual acuity ≤68 Early Treatment Diabetic Retinopathy Study letters), we found a faster improvement in visual acuity in eyes treated with aflibercept up until 18 months of treatment than eyes treated with ranibizumab, which then stayed similar until 36 months of treatment, whereas there was no apparent difference when baseline visual impairment was mild (visual acuity ≥69 Early Treatment Diabetic Retinopathy Study letters). The rate of serious adverse events was low.Aflibercept and ranibizumab were both effective and safe for diabetic macular edema over 3 years.

Published
2022

22. Three-year treatment outcomes of Aflibercept versus Ranibizumab for diabetic macular edema:: Data from the Fight Retinal Blindness! Registry

Author

Gabrielle, Pierre-Henry; https://orcid.org/0000-0002-9688-4845, Nguyen, Vuong; https://orcid.org/0000-0001-9070-9803, Creuzot-Garcher, Catherine; https://orcid.org/0000-0002-3587-4598, Arnold, Jennifer J, Mehta, Hemal, Duran, Mónica Asencio, Bougamha, Walid, Carreño, Ester, Viola, Francesco, Squirrell, David; https://orcid.org/0000-0002-8393-7100, Barthelmes, Daniel; https://orcid.org/0000-0002-5431-4991, Gillies, Mark; https://orcid.org/0000-0001-8580-0274, Gabrielle, Pierre-Henry; https://orcid.org/0000-0002-9688-4845, Nguyen, Vuong; https://orcid.org/0000-0001-9070-9803, Creuzot-Garcher, Catherine; https://orcid.org/0000-0002-3587-4598, Arnold, Jennifer J, Mehta, Hemal, Duran, Mónica Asencio, Bougamha, Walid, Carreño, Ester, Viola, Francesco, Squirrell, David; https://orcid.org/0000-0002-8393-7100, Barthelmes, Daniel; https://orcid.org/0000-0002-5431-4991, and Gillies, Mark; https://orcid.org/0000-0001-8580-0274

Abstract

PURPOSE Compare the 3-year outcomes of ranibizumab versus aflibercept in eyes with diabetic macular edema in daily practice. METHODS This was a retrospective analysis of naive diabetic macular edema eyes starting intravitreal injections of ranibizumab (0.5 mg) or aflibercept (2 mg) from January 1, 2013 to December 31, 2017 that were collected in the Fight Retinal Blindness! Registry. RESULTS We identified 534 eyes (ranibizumab-267 and aflibercept-267) of 402 patients. The adjusted mean (95% confidence interval) visual acuity change of +1.3 (-0.1 to 4.2) letters in the ranibizumab group and +2.4 (-0.2 to 5.1) letters (P = 0.001) in the aflibercept group at 3 years was not clinically different. However, the adjusted mean CST change seemed to remain significantly different throughout the 3-year period with higher reductions in favor of aflibercept (-87.8 [-108.3 to -67.4] µm for ranibizumab vs. -114.4 [-134.4 to -94.3] for aflibercept; P < 0.01). When baseline visual impairment was moderate (visual acuity ≤68 Early Treatment Diabetic Retinopathy Study letters), we found a faster improvement in visual acuity in eyes treated with aflibercept up until 18 months of treatment than eyes treated with ranibizumab, which then stayed similar until 36 months of treatment, whereas there was no apparent difference when baseline visual impairment was mild (visual acuity ≥69 Early Treatment Diabetic Retinopathy Study letters). The rate of serious adverse events was low. CONCLUSION Aflibercept and ranibizumab were both effective and safe for diabetic macular edema over 3 years.

Published
2022

23. Incidence, risk factors and outcomes of submacular haemorrhage with loss of vision in neovascular age-related macular degeneration in daily clinical practice: data from the FRB! registry

Author

Gabrielle, Pierre-Henry; https://orcid.org/0000-0002-9688-4845, Maitrias, Samuel, Nguyen, Vuong; https://orcid.org/0000-0001-9070-9803, Arnold, Jennifer J, Squirrell, David; https://orcid.org/0000-0002-8393-7100, Arnould, Louis; https://orcid.org/0000-0001-7831-8818, Sanchez-Monroy, Jorge, Viola, Francesco, O'Toole, Louise; https://orcid.org/0000-0003-4851-0918, Barthelmes, Daniel; https://orcid.org/0000-0002-5431-4991, Creuzot-Garcher, Catherine; https://orcid.org/0000-0002-3587-4598, Gillies, Mark; https://orcid.org/0000-0001-8580-0274, Gabrielle, Pierre-Henry; https://orcid.org/0000-0002-9688-4845, Maitrias, Samuel, Nguyen, Vuong; https://orcid.org/0000-0001-9070-9803, Arnold, Jennifer J, Squirrell, David; https://orcid.org/0000-0002-8393-7100, Arnould, Louis; https://orcid.org/0000-0001-7831-8818, Sanchez-Monroy, Jorge, Viola, Francesco, O'Toole, Louise; https://orcid.org/0000-0003-4851-0918, Barthelmes, Daniel; https://orcid.org/0000-0002-5431-4991, Creuzot-Garcher, Catherine; https://orcid.org/0000-0002-3587-4598, and Gillies, Mark; https://orcid.org/0000-0001-8580-0274

Abstract

PURPOSE The main purpose of the study was to report the estimated incidence, cumulative rate, risk factors and outcomes of submacular haemorrhage (SMH) with loss of vision in neovascular age-related macular degeneration (nAMD) receiving intravitreal injections (IVT) of vascular endothelial growth factor (VEGF) inhibitor in routine clinical practice. METHODS Retrospective analysis of treatment-naïve eyes receiving IVTs of VEGF inhibitors (ranibizumab, aflibercept or bevacizumab) for nAMD from 1 January 2010 to 31 December 2020 that were tracked the Fight Retinal Blindness! registry. Estimated incidence, cumulative rate and hazard ratios (HR) of SMH with loss of vision during treatment were measured using the Poisson regression, Kaplan-Meier survival curves and Cox proportional hazard models. RESULTS We identified 7642 eyes (6425 patients) with a total of 135 095 IVT over a 10-year period. One hundred five eyes developed SMH with loss of vision with a rate of 1 per 1283 injections (0.08% 95% confidence interval [95% CI] [0.06; 0.09]). The estimated incidence [95% CI] was 4.6 [3.8; 5.7] SMH with loss of vision per year per 1000 treated patients during the study. The cumulative [95% CI] rate of SMH per patient did not increase significantly with each successive injection (p = 0.947). SMH cases had a mean VA drop of around 6 lines at diagnosis, which then improved moderately to a 4-line loss at 1 year. CONCLUSIONS Submacular haemorrhage (SMH) with loss of vision is an uncommon complication that can occur at any time in eyes treated for nAMD in routine clinical practice, with only limited recovery of vision 1 year later.

Published
2022

24. Additional file 1 of Ethnic differences on long term outcomes of polypoidal choroidal vasculopathy after predominantly bevacizumab monotherapy

Author

Yap, Aaron, Wang, Nancy, and Squirrell, David

Abstract

Additional file 1: Table A1. Comparison of Clinical Outcomes in the Current Study with Previously Published Real-World Observational Studies for Polypoidal Choroidal Vasculopathy Composing Different Ethnic Compositions Treated with Anti-Vascular Endothelial Growth Factor Monotherapy or Combination Therapy with Verteporfin Photodynamic Therapy.

Published
2022
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27. Incidence, risk factors and outcomes of submacular haemorrhage with loss of vision in neovascular age‐related macular degeneration in daily clinical practice: data from the FRB! registry.

Author

Gabrielle, Pierre‐Henry, Maitrias, Samuel, Nguyen, Vuong, Arnold, Jennifer J, Squirrell, David, Arnould, Louis, Sanchez‐Monroy, Jorge, Viola, Francesco, O'Toole, Louise, Barthelmes, Daniel, Creuzot‐Garcher, Catherine, and Gillies, Mark

Subjects
MACULAR degeneration, POLYPOIDAL choroidal vasculopathy, VISION disorders, VASCULAR endothelial growth factors, PROPORTIONAL hazards models, HEMORRHAGE
Abstract

Purpose: The main purpose of the study was to report the estimated incidence, cumulative rate, risk factors and outcomes of submacular haemorrhage (SMH) with loss of vision in neovascular age‐related macular degeneration (nAMD) receiving intravitreal injections (IVT) of vascular endothelial growth factor (VEGF) inhibitor in routine clinical practice. Methods: Retrospective analysis of treatment‐naïve eyes receiving IVTs of VEGF inhibitors (ranibizumab, aflibercept or bevacizumab) for nAMD from 1 January 2010 to 31 December 2020 that were tracked the Fight Retinal Blindness! registry. Estimated incidence, cumulative rate and hazard ratios (HR) of SMH with loss of vision during treatment were measured using the Poisson regression, Kaplan–Meier survival curves and Cox proportional hazard models. Results: We identified 7642 eyes (6425 patients) with a total of 135 095 IVT over a 10‐year period. One hundred five eyes developed SMH with loss of vision with a rate of 1 per 1283 injections (0.08% 95% confidence interval [95% CI] [0.06; 0.09]). The estimated incidence [95% CI] was 4.6 [3.8; 5.7] SMH with loss of vision per year per 1000 treated patients during the study. The cumulative [95% CI] rate of SMH per patient did not increase significantly with each successive injection (p = 0.947). SMH cases had a mean VA drop of around 6 lines at diagnosis, which then improved moderately to a 4‐line loss at 1 year. Conclusions: Submacular haemorrhage (SMH) with loss of vision is an uncommon complication that can occur at any time in eyes treated for nAMD in routine clinical practice, with only limited recovery of vision 1 year later. [ABSTRACT FROM AUTHOR]

Published
2022
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30. Essentials of a Robust Deep Learning System for Diabetic Retinopathy Screening: A Systematic Literature Review

Author

Chu, Aan, Squirrell, David, Phillips, Andelka M., and Vaghefi, Ehsan

Subjects
Article Subject, education
Abstract

This systematic review was performed to identify the specifics of an optimal diabetic retinopathy deep learning algorithm, by identifying the best exemplar research studies of the field, whilst highlighting potential barriers to clinical implementation of such an algorithm. Searching five electronic databases (Embase, MEDLINE, Scopus, PubMed, and the Cochrane Library) returned 747 unique records on 20 December 2019. Predetermined inclusion and exclusion criteria were applied to the search results, resulting in 15 highest-quality publications. A manual search through the reference lists of relevant review articles found from the database search was conducted, yielding no additional records. A validation dataset of the trained deep learning algorithms was used for creating a set of optimal properties for an ideal diabetic retinopathy classification algorithm. Potential limitations to the clinical implementation of such systems were identified as lack of generalizability, limited screening scope, and data sovereignty issues. It is concluded that deep learning algorithms in the context of diabetic retinopathy screening have reported impressive results. Despite this, the potential sources of limitations in such systems must be evaluated carefully. An ideal deep learning algorithm should be clinic-, clinician-, and camera-agnostic; complying with the local regulation for data sovereignty, storage, privacy, and reporting; whilst requiring minimum human input.

Published
2020
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