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Joseph S, Selvaraj J, Mani I, Kumaragurupari T, Shang X, Mudgil P, Ravilla T, He M. Diagnostic Accuracy of Artificial Intelligence-Based Automated Diabetic Retinopathy Screening in Real-World Settings: A Systematic Review and Meta-Analysis. Am J Ophthalmol 2024; 263:214-230. [PMID: 38438095 DOI: 10.1016/j.ajo.2024.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 02/03/2024] [Accepted: 02/12/2024] [Indexed: 03/06/2024]
Abstract
PURPOSE To evaluate the diagnostic accuracy of artificial intelligence (AI)-based automated diabetic retinopathy (DR) screening in real-world settings. DESIGN Systematic review and meta-analysis METHODS: We conducted a systematic review of relevant literature from January 2012 to August 2022 using databases including PubMed, Scopus and Web of Science. The quality of studies was evaluated using Quality Assessment for Diagnostic Accuracy Studies 2 (QUADAS-2) checklist. We calculated pooled accuracy, sensitivity, specificity, and diagnostic odds ratio (DOR) as summary measures. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO - CRD42022367034). RESULTS We included 34 studies which utilized AI algorithms for diagnosing DR based on real-world fundus images. Quality assessment of these studies indicated a low risk of bias and low applicability concern. Among gradable images, the overall pooled accuracy, sensitivity, specificity, and DOR were 81%, 94% (95% CI: 92.0-96.0), 89% (95% CI: 85.0-92.0) and 128 (95% CI: 80-204) respectively. Sub-group analysis showed that, when acceptable quality imaging could be obtained, non-mydriatic fundus images had a better DOR of 143 (95% CI: 82-251) and studies using 2 field images had a better DOR of 161 (95% CI 74-347). Our meta-regression analysis revealed a statistically significant association between DOR and variables such as the income status, and the type of fundus camera. CONCLUSION Our findings indicate that AI algorithms have acceptable performance in screening for DR using fundus images compared to human graders. Implementing a fundus camera with AI-based software has the potential to assist ophthalmologists in reducing their workload and improving the accuracy of DR diagnosis.
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Affiliation(s)
- Sanil Joseph
- From the Centre for Eye Research Australia (S.J, X.S, M.H), Royal Victorian Eye and Ear Hospital, East Melbourne, Australia; Department of Surgery (Ophthalmology) (S.J, X.S, M.H), The University of Melbourne, Melbourne, Australia; Lions Aravind Institute of Community Ophthalmology (S.J, J.S, T.R), Aravind Eye Care System. Madurai, India.
| | - Jerrome Selvaraj
- Lions Aravind Institute of Community Ophthalmology (S.J, J.S, T.R), Aravind Eye Care System. Madurai, India
| | - Iswarya Mani
- Aravind Eye Hospital and Postgraduate Institute of Ophthalmology (I.M, T.K), Madurai, India
| | | | - Xianwen Shang
- From the Centre for Eye Research Australia (S.J, X.S, M.H), Royal Victorian Eye and Ear Hospital, East Melbourne, Australia; Department of Surgery (Ophthalmology) (S.J, X.S, M.H), The University of Melbourne, Melbourne, Australia
| | - Poonam Mudgil
- School of Medicine (P.M), Western Sydney University, Campbell town, Australia; School of Rural Medicine (P.M), Charles Sturt University, Orange, NSW, Australia
| | - Thulasiraj Ravilla
- Lions Aravind Institute of Community Ophthalmology (S.J, J.S, T.R), Aravind Eye Care System. Madurai, India
| | - Mingguang He
- From the Centre for Eye Research Australia (S.J, X.S, M.H), Royal Victorian Eye and Ear Hospital, East Melbourne, Australia; Department of Surgery (Ophthalmology) (S.J, X.S, M.H), The University of Melbourne, Melbourne, Australia
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Salongcay RP, Aquino LAC, Alog GP, Locaylocay KB, Saunar AV, Peto T, Silva PS. Accuracy of Integrated Artificial Intelligence Grading Using Handheld Retinal Imaging in a Community Diabetic Eye Screening Program. OPHTHALMOLOGY SCIENCE 2024; 4:100457. [PMID: 38317871 PMCID: PMC10838904 DOI: 10.1016/j.xops.2023.100457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 11/08/2023] [Accepted: 12/11/2023] [Indexed: 02/07/2024]
Abstract
Purpose To evaluate mydriatic handheld retinal imaging performance assessed by point-of-care (POC) artificial intelligence (AI) as compared with retinal image graders at a centralized reading center (RC) in identifying diabetic retinopathy (DR) and diabetic macular edema (DME). Design Prospective, comparative study. Subjects Five thousand five hundred eighty-five eyes from 2793 adult patients with diabetes. Methods Point-of-care AI assessment of disc and macular handheld retinal images was compared with RC evaluation of validated 5-field handheld retinal images (disc, macula, superior, inferior, and temporal) in identifying referable DR (refDR; defined as moderate nonproliferative DR [NPDR], or worse, or any level of DME) and vision-threatening DR (vtDR; defined as severe NPDR or worse, or any level of center-involving DME [ciDME]). Reading center evaluation of the 5-field images followed the international DR/DME classification. Sensitivity (SN) and specificity (SP) for ungradable images, refDR, and vtDR were calculated. Main Outcome Measures Agreement for DR and DME; SN and SP for refDR, vtDR, and ungradable images. Results Diabetic retinopathy severity by RC evaluation: no DR, 67.3%; mild NPDR, 9.7%; moderate NPDR, 8.6%; severe NPDR, 4.8%; proliferative DR, 3.8%; and ungradable, 5.8%. Diabetic macular edema severity by RC evaluation was as follows: no DME (80.4%), non-ciDME (7.7%), ciDME (4.4%), and ungradable (7.5%). Referable DR was present in 25.3% and vtDR was present in 17.5% of eyes. Images were ungradable for DR or DME in 7.5% by RC evaluation and 15.4% by AI. There was substantial agreement between AI and RC for refDR (κ = 0.66) and moderate agreement for vtDR (κ = 0.54). The SN/SP of AI grading compared with RC evaluation was 0.86/0.86 for refDR and 0.92/0.80 for vtDR. Conclusions This study demonstrates that POC AI following a defined handheld retinal imaging protocol at the time of imaging has SN and SP for refDR that meets the current United States Food and Drug Administration thresholds of 85% and 82.5%, but not for vtDR. Integrating AI at the POC could substantially reduce centralized RC burden and speed information delivery to the patient, allowing more prompt eye care referral. Financial Disclosures Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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Affiliation(s)
- Recivall P. Salongcay
- Centre for Public Health, Queen’s University Belfast, Belfast, United Kingdom
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Lizzie Anne C. Aquino
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
| | - Glenn P. Alog
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Kaye B. Locaylocay
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Aileen V. Saunar
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Tunde Peto
- Centre for Public Health, Queen’s University Belfast, Belfast, United Kingdom
| | - Paolo S. Silva
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
- Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts
- Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts
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Naz H, Nijhawan R, Ahuja NJ. Clinical utility of handheld fundus and smartphone-based camera for monitoring diabetic retinal diseases: a review study. Int Ophthalmol 2024; 44:41. [PMID: 38334896 DOI: 10.1007/s10792-024-02975-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 10/29/2023] [Indexed: 02/10/2024]
Abstract
Diabetic retinopathy (DR) is the leading global cause of vision loss, accounting for 4.8% of global blindness cases as estimated by the World Health Organization (WHO). Fundus photography is crucial in ophthalmology as a diagnostic tool for capturing retinal images. However, resource and infrastructure constraints limit access to traditional tabletop fundus cameras in developing countries. Additionally, these conventional cameras are expensive, bulky, and not easily transportable. In contrast, the newer generation of handheld and smartphone-based fundus cameras offers portability, user-friendliness, and affordability. Despite their potential, there is a lack of comprehensive review studies examining the clinical utilities of these handheld (e.g. Zeiss Visuscout 100, Volk Pictor Plus, Volk Pictor Prestige, Remidio NMFOP, FC161) and smartphone-based (e.g. D-EYE, iExaminer, Peek Retina, Volk iNview, Volk Vistaview, oDocs visoScope, oDocs Nun, oDocs Nun IR) fundus cameras. This review study aims to evaluate the feasibility and practicality of these available handheld and smartphone-based cameras in medical settings, emphasizing their advantages over traditional tabletop fundus cameras. By highlighting various clinical settings and use scenarios, this review aims to fill this gap by evaluating the efficiency, feasibility, cost-effectiveness, and remote capabilities of handheld and smartphone fundus cameras, ultimately enhancing the accessibility of ophthalmic services.
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Affiliation(s)
- Huma Naz
- Department of Computer Science, University of Petroleum and Energy Studies, Dehradun, India.
| | - Rahul Nijhawan
- Thapar Institute of Engineering and Technology, Patiala, Punjab, India
| | - Neelu Jyothi Ahuja
- Department of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
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He S, Joseph S, Bulloch G, Jiang F, Kasturibai H, Kim R, Ravilla TD, Wang Y, Shi D, He M. Bridging the Camera Domain Gap With Image-to-Image Translation Improves Glaucoma Diagnosis. Transl Vis Sci Technol 2023; 12:20. [PMID: 38133514 PMCID: PMC10746931 DOI: 10.1167/tvst.12.12.20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 09/15/2023] [Indexed: 12/23/2023] Open
Abstract
Purpose The purpose of this study was to improve the automated diagnosis of glaucomatous optic neuropathy (GON), we propose a generative adversarial network (GAN) model that translates Optain images to Topcon images. Methods We trained the GAN model on 725 paired images from Topcon and Optain cameras and externally validated it using an additional 843 paired images collected from the Aravind Eye Hospital in India. An optic disc segmentation model was used to assess the disparities in disc parameters across cameras. The performance of the translated images was evaluated using root mean square error (RMSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), 95% limits of agreement (LOA), Pearson's correlations, and Cohen's Kappa coefficient. The evaluation compared the performance of the GON model on Topcon photographs as a reference to that of Optain photographs and GAN-translated photographs. Results The GAN model significantly reduced Optain false positive results for GON diagnosis, with RMSE, PSNR, and SSIM of GAN images being 0.067, 14.31, and 0.64, respectively, the mean difference of VCDR and cup-to-disc area ratio between Topcon and GAN images being 0.03, 95% LOA ranging from -0.09 to 0.15 and -0.05 to 0.10. Pearson correlation coefficients increased from 0.61 to 0.85 in VCDR and 0.70 to 0.89 in cup-to-disc area ratio, whereas Cohen's Kappa improved from 0.32 to 0.60 after GAN translation. Conclusions Image-to-image translation across cameras can be achieved by using GAN to solve the problem of disc overexposure in Optain cameras. Translational Relevance Our approach enhances the generalizability of deep learning diagnostic models, ensuring their performance on cameras that are outside of the original training data set.
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Affiliation(s)
- Shuang He
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Sanil Joseph
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia
- Department of Surgery (Ophthalmology), The University of Melbourne, Melbourne, Australia
- Lions Aravind Institute of Community Ophthalmology, Aravind Eye Care System, Madurai, India
| | - Gabriella Bulloch
- Department of Surgery (Ophthalmology), The University of Melbourne, Melbourne, Australia
| | - Feng Jiang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | | | - Ramasamy Kim
- Aravind Eye Hospital and Post Graduate Institute, Madurai, India
| | - Thulasiraj D. Ravilla
- Lions Aravind Institute of Community Ophthalmology, Aravind Eye Care System, Madurai, India
| | - Yueye Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
- Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Danli Shi
- School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Mingguang He
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
- Aravind Eye Hospital and Post Graduate Institute, Madurai, India
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Li L, Jin Y, Wang JH, Wang SS, Yuan FX. Potency of teleophthalmology as a detection tool for diabetic retinopathy. Sci Rep 2023; 13:19620. [PMID: 37949948 PMCID: PMC10638282 DOI: 10.1038/s41598-023-46554-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 11/02/2023] [Indexed: 11/12/2023] Open
Abstract
In China, the prevalence of diabetic retinopathy (DR) is increasing, so it is necessary to provide convenient and effective community outreach screening programs for DR, especially in rural and remote areas. The purpose of this study was to use the results of ophthalmologists as the gold standard to evaluate the accuracy of community general practitioners' judgement and grading of DR to find a feasible and convenient DR screening method to reduce the risk of visual impairment and blindness in known diabetes patients. Retinal images of 1646 diabetic patients who underwent DR screening through teleophthalmology at Nanchang First Hospital were collected for 30 months (January 2020 to June 2022). Retinal images were collected without medication for mydriasis, stored by community general practitioner, and diagnosed by both community general practitioner and ophthalmologist of our hospital through teleophthalmology. The grading of ophthalmologist was used as a reference or gold standard for comparison with that of community general practitioner. A total of 1646 patients and 3185 eyes were examined, including 2310 eyes with DR. The evaluation by the community general practitioner had a Kappa value of 0.578, sensitivity of 80.58%, specificity of 89.94%, and accuracy of 83.38%% in 2020; a Kappa value of 0.685, sensitivity of 95.43%, specificity of 78.55%, and accuracy of 90.77% in 2021; and a Kappa value of 0.744, sensitivity of 93.99%, specificity of 88.97%, and accuracy of 92.86% in 2022. Teleophthalmology helped with large-scale screening of DR and made it possible for community general practitioner to grade images with high accuracy after appropriate training. It is possible to solve the current shortage of eye care personnel, promote the early recognition of disease and reduce the impact of diabetes-associated blindness.
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Affiliation(s)
- Liu Li
- Department of Ophthalmology, Nanchang First Hospital, Jiangxi, 330038, China.
| | - Yu Jin
- Department of Ophthalmology, Nanchang First Hospital, Jiangxi, 330038, China
| | - Jun Hua Wang
- Department of Ophthalmology, Nanchang First Hospital, Jiangxi, 330038, China
| | - Sha Sha Wang
- Department of Ophthalmology, Nanchang First Hospital, Jiangxi, 330038, China
| | - Fang Xiu Yuan
- Department of Ophthalmology, Nanchang First Hospital, Jiangxi, 330038, China
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Jacoba CMP, Salongcay RP, Aquino LAC, Salva CMG, Saunar AV, Alog GP, Peto T, Silva PS. Comparisons of handheld retinal imaging devices with ultrawide field images for determining diabetic retinopathy severity. Acta Ophthalmol 2023; 101:670-678. [PMID: 36847205 DOI: 10.1111/aos.15651] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/20/2023] [Accepted: 02/09/2023] [Indexed: 03/01/2023]
Abstract
PURPOSE To compare diabetic retinopathy (DR) severity identified on handheld retinal imaging with ultrawide field (UWF) images. METHODS Mydriatic images of 225 eyes of 118 diabetic patients were prospectively imaged with the Aurora (AU) handheld retinal camera [5-field protocol (macula-centred, disc-centred, temporal, superior, inferior)] and compared with UWF images. Images were classified based on the international classification for DR. Sensitivity, specificity, kappa statistics (K/Kw) were calculated on an eye and person-level. RESULTS Distribution of DR severity by AU/UWF images (%) by eye was no DR 41.3/36.0, mild non-proliferative DR (NPDR) 18.7/17.8, moderate 10.2/10.7, severe 16.4/15.1, proliferative DR (PDR) 13.3/20.4. Agreement between UWF and AU was exact in 64.4%, within 1-step 90.7%, k = 0.55 (95% CI:0.45-0.65), and kw = 0.79 (95% CI:0.73-0.85) by eye, and exact in 68%, within 1-step 92.9%, k = 0.58 (95% CI:0.50-0.66), and kw = 0.76 (95% CI:0.70-0.81) by person. Sensitivity/specificity for any DR, refDR, vtDR and PDR were as follows: 0.90/0.83, 0.90/0.97, 0.82/0.95 and 0.69/1.00 by person and 0.86/0.90, 0.84/0.98, 0.75/0.95 and 0.63/0.99 by eye. Handheld imaging missed 37% (17/46) eyes and 30.8% (8/26) persons with PDR. Only 3.9% (1/26) persons or 6.5% (3/46) eyes with PDR were missed if a referral threshold of moderate NPDR was used. CONCLUSIONS Data from this study show that comparing UWF and handheld images, when PDR was the referral threshold for handheld devices, 37.0% of eyes or 30.8% of patients with PDR were missed. Due to the identification of neovascular lesions outside of the handheld fields, lower referral thresholds are needed if handheld devices are used.
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Affiliation(s)
- Cris Martin P Jacoba
- Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts, USA
- Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA
| | - Recivall P Salongcay
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Centre for Public Health, Queen's University Belfast, Belfast, UK
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Lizzie Anne C Aquino
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
| | | | - Aileen V Saunar
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Glenn P Alog
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Tunde Peto
- Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Paolo S Silva
- Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts, USA
- Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA
- Centre for Public Health, Queen's University Belfast, Belfast, UK
- Eye and Vision Institute, The Medical City, Metro Manila, Philippines
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Alabdulwahhab KM. Diabetic Retinopathy Screening Using Non-Mydriatic Fundus Camera in Primary Health Care Settings - A Multicenter Study from Saudi Arabia. Int J Gen Med 2023; 16:2255-2262. [PMID: 37304902 PMCID: PMC10255608 DOI: 10.2147/ijgm.s410197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 05/30/2023] [Indexed: 06/13/2023] Open
Abstract
Background Screening of diabetic retinopathy (DR) using the current digital imaging facilities in a primary health care setting is still in its early stages in Saudi Arabia. This study aims to reduce the risk of vision impairment and blindness among known diabetic people through early identification by general practitioners (GP) in a primary health care setting in Saudi Arabia. The objective of this study was to evaluate the accuracy of diabetic retinopathy (DR) detection by general practitioners (GPs) by comparing the agreement of DR assessment between GPs and ophthalmologists' assessment as a gold standard. Methods A hospital-based, six-month cross-sectional study was conducted, and the participants were type 2 diabetic adults from the diabetic registries of seven rural PHCs, in Saudi Arabia. After medical examination, the participants were then evaluated by fundus photography using a non-mydriatic fundus camera without medication for mydriasis. Presence or absence of DR was graded by the trained GPs in the PHCs and then compared with the grading of an ophthalmologist which was taken as a reference or a gold standard. Results A total of 899 diabetic patients were included, and the mean age of the patients was 64.89 ± 11.01 years. The evaluation by the GPs had a sensitivity of 80.69 [95% CI 74.8-85.4]; specificity of 92.23 [88.7-96.3]; positive predictive value, 74.1 [70.4-77.0]; negative predictive value, 73.34 [70.6-77.9]; and an accuracy of 84.57 [81.8-89.88]. For the consensus of agreement the adjusted kappa coefficient was from 0.74 to 0.92 for the DR. Conclusion This study demonstrates that trained GPs in rural health centers are able to provide reliable detection results of DR from fundus photographs. The study highlights the need for early DR screening programs in the rural areas of Saudi Arabia to facilitate early identification of the condition and to lessen impact of blindness due to diabetes.
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Jacoba CMP, Salongcay RP, Rageh AK, Aquino LAC, Alog GP, Saunar AV, Peto T, Silva PS. Comparisons of Handheld Retinal Imaging with Optical Coherence Tomography for the Identification of Macular Pathology in Patients with Diabetes. Ophthalmic Res 2023; 66:903-912. [PMID: 37080187 DOI: 10.1159/000530720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 04/11/2023] [Indexed: 04/22/2023]
Abstract
INTRODUCTION Handheld retinal imaging cameras are relatively inexpensive and highly portable devices that have the potential to significantly expand diabetic retinopathy (DR) screening, allowing a much broader population to be evaluated. However, it is essential to evaluate if these devices can accurately identify vision-threatening macular diseases if DR screening programs will rely on these instruments. Thus, the purpose of this study was to evaluate the detection of diabetic macular pathology using monoscopic macula-centered images using mydriatic handheld retinal imaging compared with spectral domain optical coherence tomography (SDOCT). METHODS Mydriatic 40°-60° macula-centered images taken with 3 handheld retinal imaging devices (Aurora [AU], SmartScope [SS], RetinaVue 700 [RV]) were compared with the Cirrus 6000 SDOCT taken during the same visit. Images were evaluated for the presence of diabetic macular edema (DME) on monoscopic fundus photographs adapted from Early Treatment Diabetic Retinopathy Study (ETDRS) definitions (no DME, noncenter-involved DME [non-ciDME], and center-involved DME [ciDME]). Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each device with SDOCT as gold standard. RESULTS Severity by ETDRS photos: no DR 33.3%, mild NPDR 20.4%, moderate 14.2%, severe 11.6%, proliferative 20.4%, and ungradable for DR 0%; no DME 83.1%, non-ciDME 4.9%, ciDME 12.0%, and ungradable for DME 0%. Gradable images by SDOCT (N = 217, 96.4%) showed no DME in 75.6%, non-ciDME in 9.8%, and ciDME in 11.1%. The ungradable rate for images (poor visualization in >50% of the macula) was AU: 0.9%, SS: 4.4%, and RV: 6.2%. For DME, sensitivity and specificity were similar across devices (0.5-0.64, 0.93-0.97). For nondiabetic macular pathology (ERM, pigment epithelial detachment, traction retinal detachment) across all devices, sensitivity was low to moderate (0.2-0.5) but highly specific (0.93-1.00). CONCLUSIONS Compared to SDOCT, handheld macular imaging attained high specificity but low sensitivity in identifying macular pathology. This suggests the importance of SDOCT evaluation for patients suspected to have DME on fundus photography, leading to more appropriate referral refinement.
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Affiliation(s)
- Cris Martin P Jacoba
- Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts, USA
- Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA
| | - Recivall P Salongcay
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Centre for Public Health, Queen's University, Belfast, UK
- Eyes and Vision Institute, The Medical City, Pasig City, Philippines
| | - Abdulrahman K Rageh
- Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts, USA
- Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA
| | - Lizzie Anne C Aquino
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
| | - Glenn P Alog
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eyes and Vision Institute, The Medical City, Pasig City, Philippines
| | - Aileen V Saunar
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eyes and Vision Institute, The Medical City, Pasig City, Philippines
| | - Tunde Peto
- Centre for Public Health, Queen's University, Belfast, UK
| | - Paolo S Silva
- Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts, USA
- Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
- Eyes and Vision Institute, The Medical City, Pasig City, Philippines
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Salongcay RP, Aquino LAC, Salva CMG, Saunar AV, Alog GP, Sun JK, Peto T, Silva PS. Comparison of Handheld Retinal Imaging with ETDRS 7-Standard Field Photography for Diabetic Retinopathy and Diabetic Macular Edema. Ophthalmol Retina 2022; 6:548-556. [PMID: 35278726 DOI: 10.1016/j.oret.2022.03.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 03/02/2022] [Accepted: 03/03/2022] [Indexed: 06/14/2023]
Abstract
PURPOSE To compare nonmydriatic (NM) and mydriatic (MD) handheld retinal imaging with standard ETDRS 7-field color fundus photography (ETDRS photographs) for the assessment of diabetic retinopathy (DR) and diabetic macular edema (DME). DESIGN Prospective, comparative, instrument validation study. SUBJECTS A total of 225 eyes from 116 patients with diabetes mellitus. METHODS Following a standardized protocol, NM and MD images were acquired using handheld retinal cameras (NM images: Aurora, Smartscope, and RetinaVue-700; MD images: Aurora, Smartscope, RetinaVue-700, and iNview) and dilated ETDRS photographs. Grading was performed at a centralized reading center using the International Clinical Classification for DR and DME. Kappa statistics (simple [K], weighted [Kw]) assessed the level of agreement for DR and DME. Sensitivity and specificity were calculated for any DR, referable DR (refDR), and vision-threatening DR (vtDR). MAIN OUTCOME MEASURES Agreement for DR and DME; sensitivity and specificity for any DR, refDR, and vtDR; ungradable rates. RESULTS Severity by ETDRS photographs: no DR, 33.3%; mild nonproliferative DR, 20.4%; moderate DR, 14.2%; severe DR, 11.6%; proliferative DR, 20.4%; no DME, 68.0%; DME, 9.3%; non-center involving clinically significant DME, 4.9%; center-involving clinically significant DME, 12.4%; and ungradable, 5.3%. For NM handheld retinal imaging, Kw was 0.70 to 0.73 for DR and 0.76 to 0.83 for DME. For MD handheld retinal imaging, Kw was 0.68 to 0.75 for DR and 0.77 to 0.91 for DME. Thresholds for sensitivity (0.80) and specificity (0.95) were met by NM images acquired using Smartscope and MD images acquired using Aurora and RetinaVue-700 cameras for any DR and by MD images acquired using Aurora and RetinaVue-700 cameras for refDR. Thresholds for sensitivity and specificity were met by MD images acquired using Aurora and RetinaVue-700 for DME. Nonmydriatic and MD ungradable rates for DR were 15.1% to 38.3% and 0% to 33.8%, respectively. CONCLUSIONS Following standardized protocols, NM and MD handheld retinal imaging devices have substantial agreement levels for DR and DME. With mydriasis, not all handheld retinal imaging devices meet standards for sensitivity and specificity in identifying any DR and refDR. None of the handheld devices met the established 95% specificity for vtDR, suggesting that lower referral thresholds should be used if handheld devices must be utilized. When using handheld devices, the ungradable rate is significantly reduced with mydriasis and DME sensitivity thresholds are only achieved following dilation.
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Affiliation(s)
- Recivall P Salongcay
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines; Centre for Public Health, Queen's University Belfast, Belfast, United Kingdom; Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Lizzie Anne C Aquino
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines
| | | | - Aileen V Saunar
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines; Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Glenn P Alog
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines; Eye and Vision Institute, The Medical City, Metro Manila, Philippines
| | - Jennifer K Sun
- Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts; Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts
| | - Tunde Peto
- Centre for Public Health, Queen's University Belfast, Belfast, United Kingdom
| | - Paolo S Silva
- Philippine Eye Research Institute, University of the Philippines, Manila, Philippines; Eye and Vision Institute, The Medical City, Metro Manila, Philippines; Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts; Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts.
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10
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Yuen J, Pike S, Khachikyan S, Nallasamy S. Telehealth in Ophthalmology. Digit Health 2022. [DOI: 10.36255/exon-publications-digital-health-telehealth-ophthalmology] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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11
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Handheld Fundus Camera for Diabetic Retinopathy Screening: A Comparison Study with Table-Top Fundus Camera in Real-Life Setting. J Clin Med 2022; 11:jcm11092352. [PMID: 35566478 PMCID: PMC9103652 DOI: 10.3390/jcm11092352] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 04/19/2022] [Accepted: 04/21/2022] [Indexed: 02/05/2023] Open
Abstract
The aim of the study was to validate the performance of the Optomed Aurora® handheld fundus camera in diabetic retinopathy (DR) screening. Patients who were affected by diabetes mellitus and referred to the local DR screening service underwent fundus photography using a standard table-top fundus camera and the Optomed Aurora® handheld fundus camera. All photos were taken by a single, previously unexperienced operator. Among 423 enrolled eyes, we found a prevalence of 3.55% and 3.31% referable cases with the Aurora® and with the standard table-top fundus camera, respectively. The Aurora® obtained a sensitivity of 96.9% and a specificity of 94.8% in recognizing the presence of any degree of DR, a sensitivity of 100% and a specificity of 99.8% for any degree of diabetic maculopathy (DM) and a sensitivity of 100% and specificity of 99.8% for referable cases. The overall concordance coefficient k (95% CI) was 0.889 (0.828–0.949) and 0.831 (0.658–1.004) with linear weighting for DR and DM, respectively. The presence of hypertensive retinopathy (HR) was recognized by the Aurora® with a sensitivity and specificity of 100%. The Optomed Aurora® handheld fundus camera proved to be effective in recognizing referable cases in a real-life DR screening setting. It showed comparable results to a standard table-top fundus camera in DR, DM and HR detection and grading. The Aurora® can be integrated into telemedicine solutions and artificial intelligence services which, in addition to its portability and ease of use, make it particularly suitable for DR screening.
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12
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Yao X, Son T, Ma J. Developing portable widefield fundus camera for teleophthalmology: Technical challenges and potential solutions. Exp Biol Med (Maywood) 2022; 247:289-299. [PMID: 34878934 PMCID: PMC8899340 DOI: 10.1177/15353702211063477] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
A portable, low cost, widefield fundus camera is essential for developing affordable teleophthalmology. However, conventional trans-pupillary illumination used in traditional fundus cameras limits the field of view (FOV) in a snapshot image, and frequently requires pharmacologically pupillary dilation for reliable examination of eye conditions. This minireview summarizes recent developments in alternative illumination approaches for widefield fundus photography. Miniaturized indirect illumination has been used to enable compact design for developing low cost, portable, widefield fundus camera. Contact mode trans-pars-planar illumination has been validated for ultra-widefield fundus imaging of infant eyes. Contact-free trans-pars-planar illumination has been explored for widefield imaging of adult eyes. Trans-palpebral illumination has been also demonstrated in a smartphone-based widefield fundus imager to foster affordable teleophthalmology.
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Affiliation(s)
- Xincheng Yao
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA
- Department of Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Taeyoon Son
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Jiechao Ma
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA
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13
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Sensitivity and Specificity of Handheld Fundus Cameras for Eye Disease: A Systematic Review and Pooled Analysis. Surv Ophthalmol 2021; 67:1531-1539. [PMID: 34822849 DOI: 10.1016/j.survophthal.2021.11.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 11/07/2021] [Accepted: 11/15/2021] [Indexed: 11/21/2022]
Abstract
In order to evaluate the accuracy of commercially available handheld fundus cameras for a variety of ophthalmic diagnoses, we conducted a systematic review, searching PubMed and PubMed Central and performing a bivariate analysis to determine the pooled sensitivity and specificity of handheld fundus cameras. Eleven studies validating handheld fundus cameras against a gold-standard method for disease diagnosis were included. For non-mydriatic images, pooled sensitivity was 83% (95% CI: 77-88%) and specificity was 92% (95% CI: 79-97%). For mydriatic images, pooled sensitivity was 87% (95% CI: 79-92%) and specificity was 90% (95% CI: 78-96%). Overall pooled sensitivity was 85% (95% CI: 80-89%) and specificity was 91% (95% CI: 83-95%). Of the 11 studies included, 5 assessed the diagnosis of diabetic retinopathy, for which sensitivity was 87% (95% CI: 80-92%) and specificity was 95% (95% CI: 85-98%). For all other diagnoses combined, sensitivity was 81% (95% CI: 74-87%) and specificity was 83% (95% CI: 76-89%). These findings suggest that handheld fundus cameras are capable of achieving acceptable sensitivity and specificity values for eye disease, with mydriatic images being more sensitive for disease. Diabetic retinopathy was the single diagnosis with the strongest data to support the use of handheld fundus cameras for disease screening.
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14
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Perilli R, Mariotti SP, Mastropasqua L, Bandello FM, Grigioni M, Tarricone R, Petracca F, Consoli A. Welcoming teleretinography into diabetes integrated care. Eur J Ophthalmol 2021; 32:2382-2387. [PMID: 34425693 DOI: 10.1177/11206721211039346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Integrated Care (IC) is a perfect fit for people with diabetes. Fundus examination (FE) is a disease marker for diabetologists and identifies potentially blinding complications (Diabetic Retinopathy, DR). In our Diabetes Clinic (DC) in Pescara, Italy, FE is possibly provided with telemedicine in same day as other exams, avoiding it to be a standalone clinical one; images taken with a retinal digital camera are graded by a remote ophthalmologist within a shared Electronic Health Record (EHR), immediately readable by other stakeholders; a dedicated care path to the Eye Clinic, University of Chieti-Pescara is provided for urgent cases. Personnel's worktime shortening allows gaining time for ophthalmologists' eye examinations in outpatient settings and other stakeholders' work in the DC. The need for a DR digital screening system is growing worldwide: our experience confirms the ease of implementation, and the advantage of sharing clinical data with all stakeholders when working within an EHR, aiming to optimize an IC effective system.
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Affiliation(s)
- Roberto Perilli
- Territorial Ophthalmology Unit, Local Health Authority, Pescara, Italy
| | - Silvio P Mariotti
- Department of Chronic Diseases and Health Promotion, World Health Organization, Geneva, Switzerland
| | - Leonardo Mastropasqua
- Eye Clinic and National Centre for Excellence in Ophthalmology, University of Chieti-Pescara, Chieti, Italy
| | | | - Mauro Grigioni
- National Centre for Innovative Technologies in Public Health, Istituto Superiore di Sanità, Rome, Italy
| | - Rosanna Tarricone
- Department of Social and Political Sciences, Bocconi University, Milan, Italy.,Centre for Research in Health and Social Care Management (CERGAS), Government, Health and Non Profit Division, SDA Bocconi, Milan, Italy
| | - Francesco Petracca
- Centre for Research in Health and Social Care Management (CERGAS), Government, Health and Non Profit Division, SDA Bocconi, Milan, Italy
| | - Agostino Consoli
- Chair of Endocrinology and Metabolic Diseases, University of Chieti-Pescara, Chieti, Italy
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15
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Chan EJJ, Najjar RP, Tang Z, Milea D. Deep Learning for Retinal Image Quality Assessment of Optic Nerve Head Disorders. Asia Pac J Ophthalmol (Phila) 2021; 10:282-288. [PMID: 34383719 DOI: 10.1097/apo.0000000000000404] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
ABSTRACT Deep learning (DL)-based retinal image quality assessment (RIQA) algorithms have been gaining popularity, as a solution to reduce the frequency of diagnostically unusable images. Most existing RIQA tools target retinal conditions, with a dearth of studies looking into RIQA models for optic nerve head (ONH) disorders. The recent success of DL systems in detecting ONH abnormalities on color fundus images prompts the development of tailored RIQA algorithms for these specific conditions. In this review, we discuss recent progress in DL-based RIQA models in general and the need for RIQA models tailored for ONH disorders. Finally, we propose suggestions for such models in the future.
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Affiliation(s)
| | - Raymond P Najjar
- Duke-NUS School of Medicine, Singapore
- Visual Neuroscience Group, Singapore Eye Research Institute, Singapore
| | - Zhiqun Tang
- Visual Neuroscience Group, Singapore Eye Research Institute, Singapore
| | - Dan Milea
- Duke-NUS School of Medicine, Singapore
- Visual Neuroscience Group, Singapore Eye Research Institute, Singapore
- Ophthalmology Department, Singapore National Eye Centre, Singapore
- Rigshospitalet, Copenhagen University, Denmark
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16
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Eszes DJ, Szabó DJ, Russell G, Lengyel C, Várkonyi T, Paulik E, Nagymajtényi L, Facskó A, Petrovski G, Petrovski BÉ. Diabetic Retinopathy Screening in Patients with Diabetes Using a Handheld Fundus Camera: The Experience from the South-Eastern Region in Hungary. J Diabetes Res 2021; 2021:6646645. [PMID: 33628836 PMCID: PMC7884113 DOI: 10.1155/2021/6646645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 12/20/2020] [Accepted: 01/19/2021] [Indexed: 11/18/2022] Open
Abstract
PURPOSE Diabetic retinopathy (DR) is the leading cause of vision loss among active adults in industrialized countries. We aimed to investigate the prevalence of diabetes mellitus (DM), DR and its different grades, in patients with DM in the Csongrád County, South-Eastern region, Hungary. Furthermore, we aimed to detect the risk factors for developing DR and the diabetology/ophthalmology screening patterns and frequencies, as well as the effect of socioeconomic status- (SES-) related factors on the health and behavior of DM patients. METHODS A cross-sectional study was conducted on adults (>18 years) involving handheld fundus camera screening (Smartscope Pro Optomed, Finland) and image assessment using the Spectra DR software (Health Intelligence, England). Self-completed questionnaires on self-perceived health status (SPHS) and health behavior, as well as visual acuity, HbA1c level, type of DM, and attendance at healthcare services were also recorded. RESULTS 787 participants with fundus camera images and full self-administered questionnaires were included in the study; 46.2% of the images were unassessable. T1D and T2D were present in 13.5% and 86.5% of the participants, respectively. Among the T1D and T2D patients, 25.0% and 33.5% had DR, respectively. The SES showed significant proportion differences in the T1D group. Lower education was associated with a lower DR rate compared to non-DR (7.7% vs. 40.5%), while bad/very bad perceived financial status was associated with significantly higher DR proportion compared to non-DR (63.6% vs. 22.2%). Neither the SPHS nor the health behavior showed a significant relationship with the disease for both DM groups. Mild nonproliferative retinopathy without maculopathy (R1M0) was detected in 6% and 23% of the T1D and T2D patients having DR, respectively; R1 with maculopathy (R1M1) was present in 82% and 66% of the T1D and T2D groups, respectively. Both moderate nonproliferative retinopathy with maculopathy (R2M1) and active proliferative retinopathy with maculopathy (R3M1) were detected in 6% and 7% of the T1D and T2D patients having DR, respectively. The level of HbA1c affected the attendance at the diabetology screening (HbA1c > 7% associated with >50% of all quarter-yearly attendance in DM patients, and with 10% of the diabetology screening nonattendance). CONCLUSION The prevalence of DM and DR in the studied population in Hungary followed the country trend, with a slightly higher sight-threatening DR than the previously reported national average. SES appears to affect the DR rate, in particular, for T1D. Although DR screening using handheld cameras seems to be simple and dynamic, much training and experience, as well as overcoming the issue of decreased optic clarity is needed to achieve a proper level of image assessability, and in particular, for use in future telemedicine or artificial intelligence screening programs.
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Affiliation(s)
- Dóra Júlia Eszes
- Department of Public Health, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Dóra Júlia Szabó
- Department of Ophthalmology, Szent-Györgyi Albert Clinical Center, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Greg Russell
- Eyenuk Inc., Clinical Development, Woodland Hills, CA, USA
| | - Csaba Lengyel
- Department of Medicine, Medical Faculty, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Tamás Várkonyi
- Department of Medicine, Medical Faculty, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Edit Paulik
- Department of Public Health, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - László Nagymajtényi
- Department of Public Health, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Andrea Facskó
- Department of Ophthalmology, Szent-Györgyi Albert Clinical Center, Faculty of Medicine, University of Szeged, Szeged, Hungary
| | - Goran Petrovski
- Center for Eye Research, Department of Ophthalmology, Oslo University Hospital and Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Beáta Éva Petrovski
- Center for Eye Research, Department of Ophthalmology, Oslo University Hospital and Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- The A. I. Evdokimov Moscow State University of Medicine and Dentistry of the Ministry of Healthcare the Russian Federation, Moscow, Russia
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