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Kang D, Wu H, Yuan L, Shi Y, Jin K, Grzybowski A. A Beginner's Guide to Artificial Intelligence for Ophthalmologists. Ophthalmol Ther 2024; 13:1841-1855. [PMID: 38734807 PMCID: PMC11178755 DOI: 10.1007/s40123-024-00958-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 04/22/2024] [Indexed: 05/13/2024] Open
Abstract
The integration of artificial intelligence (AI) in ophthalmology has promoted the development of the discipline, offering opportunities for enhancing diagnostic accuracy, patient care, and treatment outcomes. This paper aims to provide a foundational understanding of AI applications in ophthalmology, with a focus on interpreting studies related to AI-driven diagnostics. The core of our discussion is to explore various AI methods, including deep learning (DL) frameworks for detecting and quantifying ophthalmic features in imaging data, as well as using transfer learning for effective model training in limited datasets. The paper highlights the importance of high-quality, diverse datasets for training AI models and the need for transparent reporting of methodologies to ensure reproducibility and reliability in AI studies. Furthermore, we address the clinical implications of AI diagnostics, emphasizing the balance between minimizing false negatives to avoid missed diagnoses and reducing false positives to prevent unnecessary interventions. The paper also discusses the ethical considerations and potential biases in AI models, underscoring the importance of continuous monitoring and improvement of AI systems in clinical settings. In conclusion, this paper serves as a primer for ophthalmologists seeking to understand the basics of AI in their field, guiding them through the critical aspects of interpreting AI studies and the practical considerations for integrating AI into clinical practice.
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Affiliation(s)
- Daohuan Kang
- Department of Ophthalmology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Hongkang Wu
- Eye Center, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China
| | - Lu Yuan
- Department of Ophthalmology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Yu Shi
- Eye Center, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China
- Zhejiang University School of Medicine, Hangzhou, China
| | - Kai Jin
- Eye Center, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Andrzej Grzybowski
- Institute for Research in Ophthalmology, Foundation for Ophthalmology Development, Poznan, Poland.
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Zhang X, Ma L, Sun D, Yi M, Wang Z. Artificial Intelligence in Telemedicine: A Global Perspective Visualization Analysis. Telemed J E Health 2024. [PMID: 38436235 DOI: 10.1089/tmj.2023.0704] [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: 03/05/2024] Open
Abstract
Background: The use of artificial intelligence (AI) in telemedicine has been a popular topic in academic research in recent years, resulting in a surge of literature publications. This study provides a scientific overview of AI in telemedicine through bibliometric and visualization analysis. Methods: The Web of Science Core Collection was used as the data source, and the search was conducted on June 1, 2023. A total of 2,860 articles and review studies published in English between 2010 and 2023 were included. This study analyzed general information on the field, trends in publication output, countries/regions, authors, journals, influential articles, keyword usage, and knowledge flows between disciplines. The Bibliometrix R package, VOSviewer, and CiteSpace were used for the analysis. Results: The rate of articles published on AI in telemedicine is increasing by ∼42.1% annually. The United States and China are the top two countries in terms of the number of articles published, accounting for 37.1% of the overall publication volume. In addition to AI and telemedicine, machine learning, digital health, and deep learning are the top three keywords in terms of frequency of occurrence. The keyword time trend graph shows that ChatGPT became one of the important keywords in 2023. The analysis of burst detection suggests that mobile health, based on mobile phones, may be a promising area for future research. Conclusions: This study systematically reviewed the development of AI in telemedicine and identified current research hotspots and future research directions. The results will provide impetus for the innovative development of this field.
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Affiliation(s)
- Xu Zhang
- School of Nursing, Peking University, Beijing, China
| | - Li Ma
- Department of Emergency Medicine, Peking University Third Hospital, Beijing, China
| | - Di Sun
- School of Nursing, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China
| | - Mo Yi
- School of Nursing, Peking University, Beijing, China
| | - Zhiwen Wang
- School of Nursing, Peking University, Beijing, China
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3
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Palaniappan K, Lin EYT, Vogel S. Global Regulatory Frameworks for the Use of Artificial Intelligence (AI) in the Healthcare Services Sector. Healthcare (Basel) 2024; 12:562. [PMID: 38470673 PMCID: PMC10930608 DOI: 10.3390/healthcare12050562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 02/23/2024] [Accepted: 02/26/2024] [Indexed: 03/14/2024] Open
Abstract
The healthcare sector is faced with challenges due to a shrinking healthcare workforce and a rise in chronic diseases that are worsening with demographic and epidemiological shifts. Digital health interventions that include artificial intelligence (AI) are being identified as some of the potential solutions to these challenges. The ultimate aim of these AI systems is to improve the patient's health outcomes and satisfaction, the overall population's health, and the well-being of healthcare professionals. The applications of AI in healthcare services are vast and are expected to assist, automate, and augment several healthcare services. Like any other emerging innovation, AI in healthcare also comes with its own risks and requires regulatory controls. A review of the literature was undertaken to study the existing regulatory landscape for AI in the healthcare services sector in developed nations. In the global regulatory landscape, most of the regulations for AI revolve around Software as a Medical Device (SaMD) and are regulated under digital health products. However, it is necessary to note that the current regulations may not suffice as AI-based technologies are capable of working autonomously, adapting their algorithms, and improving their performance over time based on the new real-world data that they have encountered. Hence, a global regulatory convergence for AI in healthcare, similar to the voluntary AI code of conduct that is being developed by the US-EU Trade and Technology Council, would be beneficial to all nations, be it developing or developed.
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Affiliation(s)
- Kavitha Palaniappan
- Centre of Regulatory Excellence, Duke-NUS Medical School, Singapore 169857, Singapore
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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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5
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Than J, Sim PY, Muttuvelu D, Ferraz D, Koh V, Kang S, Huemer J. Teleophthalmology and retina: a review of current tools, pathways and services. Int J Retina Vitreous 2023; 9:76. [PMID: 38053188 DOI: 10.1186/s40942-023-00502-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 10/02/2023] [Indexed: 12/07/2023] Open
Abstract
Telemedicine, the use of telecommunication and information technology to deliver healthcare remotely, has evolved beyond recognition since its inception in the 1970s. Advances in telecommunication infrastructure, the advent of the Internet, exponential growth in computing power and associated computer-aided diagnosis, and medical imaging developments have created an environment where telemedicine is more accessible and capable than ever before, particularly in the field of ophthalmology. Ever-increasing global demand for ophthalmic services due to population growth and ageing together with insufficient supply of ophthalmologists requires new models of healthcare provision integrating telemedicine to meet present day challenges, with the recent COVID-19 pandemic providing the catalyst for the widespread adoption and acceptance of teleophthalmology. In this review we discuss the history, present and future application of telemedicine within the field of ophthalmology, and specifically retinal disease. We consider the strengths and limitations of teleophthalmology, its role in screening, community and hospital management of retinal disease, patient and clinician attitudes, and barriers to its adoption.
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Affiliation(s)
- Jonathan Than
- Moorfields Eye Hospital NHS Foundation Trust, 162 City Road, London, UK
| | - Peng Y Sim
- Moorfields Eye Hospital NHS Foundation Trust, 162 City Road, London, UK
| | - Danson Muttuvelu
- Department of Ophthalmology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- MitØje ApS/Danske Speciallaeger Aps, Aarhus, Denmark
| | - Daniel Ferraz
- D'Or Institute for Research and Education (IDOR), São Paulo, Brazil
- Institute of Ophthalmology, University College London, London, UK
| | - Victor Koh
- Department of Ophthalmology, National University Hospital, Singapore, Singapore
| | - Swan Kang
- Moorfields Eye Hospital NHS Foundation Trust, 162 City Road, London, UK
| | - Josef Huemer
- Moorfields Eye Hospital NHS Foundation Trust, 162 City Road, London, UK.
- Department of Ophthalmology and Optometry, Kepler University Hospital, Johannes Kepler University, Linz, Austria.
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Rák T, Kovács-Valasek A, Pöstyéni E, Csutak A, Gábriel R. Complementary Approaches to Retinal Health Focusing on Diabetic Retinopathy. Cells 2023; 12:2699. [PMID: 38067127 PMCID: PMC10705724 DOI: 10.3390/cells12232699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/20/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023] Open
Abstract
Diabetes mellitus affects carbohydrate homeostasis but also influences fat and protein metabolism. Due to ophthalmic complications, it is a leading cause of blindness worldwide. The molecular pathology reveals that nuclear factor kappa B (NFκB) has a central role in the progression of diabetic retinopathy, sharing this signaling pathway with another major retinal disorder, glaucoma. Therefore, new therapeutic approaches can be elaborated to decelerate the ever-emerging "epidemics" of diabetic retinopathy and glaucoma targeting this critical node. In our review, we emphasize the role of an improvement of lifestyle in its prevention as well as the use of phytomedicals associated with evidence-based protocols. A balanced personalized therapy requires an integrative approach to be more successful for prevention and early treatment.
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Affiliation(s)
- Tibor Rák
- Department of Ophthalmology, Clinical Centre, Medical School, University of Pécs, Rákóczi út 2., 7623 Pécs, Hungary; (T.R.)
| | - Andrea Kovács-Valasek
- Department of Neurobiology, University of Pécs, Ifjúság útja 6, 7624 Pécs, Hungary
- János Szentágothai Research Centre, University of Pécs, Ifjúság útja 20, 7624 Pécs, Hungary
| | - Etelka Pöstyéni
- Department of Neurobiology, University of Pécs, Ifjúság útja 6, 7624 Pécs, Hungary
| | - Adrienne Csutak
- Department of Ophthalmology, Clinical Centre, Medical School, University of Pécs, Rákóczi út 2., 7623 Pécs, Hungary; (T.R.)
| | - Róbert Gábriel
- Department of Neurobiology, University of Pécs, Ifjúság útja 6, 7624 Pécs, Hungary
- János Szentágothai Research Centre, University of Pécs, Ifjúság útja 20, 7624 Pécs, Hungary
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7
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Land MR, Patel PA, Bui T, Jiao C, Ali A, Ibnamasud S, Patel PN, Sheth V. Examining the Role of Telemedicine in Diabetic Retinopathy. J Clin Med 2023; 12:jcm12103537. [PMID: 37240642 DOI: 10.3390/jcm12103537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 04/21/2023] [Accepted: 05/16/2023] [Indexed: 05/28/2023] Open
Abstract
With the increasing prevalence of diabetic retinopathy (DR), screening is of the utmost importance to prevent vision loss for patients and reduce financial costs for the healthcare system. Unfortunately, it appears that the capacity of optometrists and ophthalmologists to adequately perform in-person screenings of DR will be insufficient within the coming years. Telemedicine offers the opportunity to expand access to screening while reducing the economic and temporal burden associated with current in-person protocols. The present literature review summarizes the latest developments in telemedicine for DR screening, considerations for stakeholders, barriers to implementation, and future directions in this area. As the role of telemedicine in DR screening continues to expand, further work will be necessary to continually optimize practices and improve long-term patient outcomes.
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Affiliation(s)
- Matthew R Land
- Department of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
| | - Parth A Patel
- Department of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
| | - Tommy Bui
- Department of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
| | - Cheng Jiao
- Department of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
| | - Arsalan Ali
- Burnett School of Medicine, Texas Christian University, Fort Worth, TX 76129, USA
| | - Shadman Ibnamasud
- Department of Ophthalmology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
| | - Prem N Patel
- Department of Ophthalmology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Veeral Sheth
- Department of Ophthalmology, University Retina and Macula Associates, Oak Forest, IL 60452, USA
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8
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Ahuja AS, Polascik BW, Doddapaneni D, Byrnes ES, Sridhar J. The Digital Metaverse: Applications in Artificial Intelligence, Medical Education, and Integrative Health. Integr Med Res 2023; 12:100917. [PMID: 36691642 PMCID: PMC9860100 DOI: 10.1016/j.imr.2022.100917] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 11/06/2022] [Accepted: 11/16/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- Abhimanyu S. Ahuja
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, United States of America
| | - Bryce W. Polascik
- Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Divyesh Doddapaneni
- Department of Internal Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Eamonn S. Byrnes
- Department of Internal Medicine, Orlando Regional Medical Center, Orlando, Florida, United States of America
| | - Jayanth Sridhar
- Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miller School of Medicine, Miami, Florida, United States of America,Corresponding author at: Jayanth Sridhar, Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miller School of Medicine, 900 NW 17th Street, Miami, FL, 33136.
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9
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Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions. Diagnostics (Basel) 2022; 13:diagnostics13010100. [PMID: 36611392 PMCID: PMC9818832 DOI: 10.3390/diagnostics13010100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/12/2022] [Accepted: 12/26/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Having several applications in medicine, and in ophthalmology in particular, artificial intelligence (AI) tools have been used to detect visual function deficits, thus playing a key role in diagnosing eye diseases and in predicting the evolution of these common and disabling diseases. AI tools, i.e., artificial neural networks (ANNs), are progressively involved in detecting and customized control of ophthalmic diseases. The studies that refer to the efficiency of AI in medicine and especially in ophthalmology were analyzed in this review. MATERIALS AND METHODS We conducted a comprehensive review in order to collect all accounts published between 2015 and 2022 that refer to these applications of AI in medicine and especially in ophthalmology. Neural networks have a major role in establishing the demand to initiate preliminary anti-glaucoma therapy to stop the advance of the disease. RESULTS Different surveys in the literature review show the remarkable benefit of these AI tools in ophthalmology in evaluating the visual field, optic nerve, and retinal nerve fiber layer, thus ensuring a higher precision in detecting advances in glaucoma and retinal shifts in diabetes. We thus identified 1762 applications of artificial intelligence in ophthalmology: review articles and research articles (301 pub med, 144 scopus, 445 web of science, 872 science direct). Of these, we analyzed 70 articles and review papers (diabetic retinopathy (N = 24), glaucoma (N = 24), DMLV (N = 15), other pathologies (N = 7)) after applying the inclusion and exclusion criteria. CONCLUSION In medicine, AI tools are used in surgery, radiology, gynecology, oncology, etc., in making a diagnosis, predicting the evolution of a disease, and assessing the prognosis in patients with oncological pathologies. In ophthalmology, AI potentially increases the patient's access to screening/clinical diagnosis and decreases healthcare costs, mainly when there is a high risk of disease or communities face financial shortages. AI/DL (deep learning) algorithms using both OCT and FO images will change image analysis techniques and methodologies. Optimizing these (combined) technologies will accelerate progress in this area.
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Ultra-wide-field fundus photography compared to ophthalmoscopy in diagnosing and classifying major retinal diseases. Sci Rep 2022; 12:19287. [PMID: 36369463 PMCID: PMC9650656 DOI: 10.1038/s41598-022-23170-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 10/26/2022] [Indexed: 11/13/2022] Open
Abstract
To analyze the performance of ultra-wide-field (UWF) fundus photography compared with ophthalmoscopy in identifying and classifying retinal diseases. Patients examined for presumed major retinal disorders were consecutively enrolled. Each patient underwent indirect ophthalmoscopic evaluation, with scleral depression and/or fundus biomicroscopy, when clinically indicated, and mydriatic UWF fundus imaging by means of CLARUS 500™ fundus camera. Each eye was classified by a clinical grader and two image graders in the following groups: normal retina, diabetic retinopathy, vascular abnormalities, macular degenerations and dystrophies, retinal and choroidal tumors, peripheral degenerative lesions and retinal detachment and myopic alterations. 7024 eyes of new patients were included. The inter-grader agreement for images classification was perfect (kappa = 0.998, 95% Confidence Interval (95%CI) = 0.997-0.999), as the two methods concordance for retinal diseases diagnosis (kappa = 0.997, 95%CI = 0.996-0.999) without statistically significant difference. UWF fundus imaging might be an alternative to ophthalmoscopy, since it allows to accurately classify major retinal diseases, widening the range of disorders possibly diagnosed with teleophthalmology. Although the clinician should be aware of the possibility that a minority of the most peripheral lesions may be not entirely visualized, it might be considered a first line diagnostic modality, in the context of a full ophthalmological examination.
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Kiburg KV, Turner A, He M. Telemedicine and delivery of ophthalmic care in rural and remote communities: Drawing from Australian experience. Clin Exp Ophthalmol 2022; 50:793-800. [PMID: 35975938 DOI: 10.1111/ceo.14147] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/07/2022] [Accepted: 08/12/2022] [Indexed: 01/07/2023]
Abstract
Rural and remote communities in Australia are characterised by small but widely dispersed populations. This has been proven to be a major hurdle in access to medical care services with screening and treatment goals repeatedly being missed. Telemedicine in ophthalmology provides the opportunity to increase the availability of high quality and timely access to healthcare within. Recent years has also seen the introduction of artificial intelligence (AI) in ophthalmology, particularly in the screening of diseases. AI will hopefully increase the number of appropriate referrals, reduce travel time for patients and ensure timely triage given the low number of qualified optometrists and ophthalmologists. Telemedicine and AI has been introduced in a number of countries and has led to tremendous benefits and advantages when compared to standard practices. This paper summarises current practices in telemedicine and AI and the future of this technology in improving patient care in the field of ophthalmology.
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Affiliation(s)
- Katerina V Kiburg
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Victoria, Australia
| | - Angus Turner
- Lions Outback Vision, Lions Eye Institute, Nedlands, Western Australia, Australia.,Centre for Ophthalmology and Visual Science, University of Western Australia, Nedlands, Western Australia, Australia
| | - Mingguang He
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Victoria, Australia
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Horie S, Ohno-Matsui K. Progress of Imaging in Diabetic Retinopathy-From the Past to the Present. Diagnostics (Basel) 2022; 12:diagnostics12071684. [PMID: 35885588 PMCID: PMC9319818 DOI: 10.3390/diagnostics12071684] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 06/24/2022] [Accepted: 07/06/2022] [Indexed: 02/05/2023] Open
Abstract
Advancement of imaging technology in retinal diseases provides us more precise understanding and new insights into the diseases' pathologies. Diabetic retinopathy (DR) is one of the leading causes of sight-threatening retinal diseases worldwide. Colour fundus photography and fluorescein angiography have long been golden standard methods in detecting retinal vascular pathology in this disease. One of the major advancements is macular observation given by optical coherence tomography (OCT). OCT dramatically improves the diagnostic quality in macular edema in DR. The technology of OCT is also applied to angiography (OCT angiograph: OCTA), which enables retinal vascular imaging without venous dye injection. Similar to OCTA, in terms of their low invasiveness, single blue color SLO image could be an alternative method in detecting non-perfused areas. Conventional optical photography has been gradually replaced to scanning laser ophthalmoscopy (SLO), which also make it possible to produce spectacular ultra-widefield (UWF) images. Since retinal vascular changes of DR are found in the whole retina up to periphery, it would be one of the best targets in UWF imaging. Additionally, evolvement of artificial intelligence (AI) has been applied to automated diagnosis of DR, and AI-based DR management is one of the major topics in this field. This review is trying to look back on the progress of imaging of DR comprehensively from the past to the present.
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Affiliation(s)
- Shintaro Horie
- Department of Advanced Ophthalmic Imaging, Tokyo Medical and Dental University, Tokyo 113-8519, Japan;
| | - Kyoko Ohno-Matsui
- Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo 113-8519, Japan
- Correspondence: ; Tel.: +81-3-5803-5302
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13
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Begg A. Diabetes care: is big data the future? PRACTICAL DIABETES 2022. [DOI: 10.1002/pdi.2391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Alan Begg
- Division of Molecular and Clinical Medicine, University of Dundee UK
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14
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Update on Optical Coherence Tomography and Optical Coherence Tomography Angiography Imaging in Proliferative Diabetic Retinopathy. Diagnostics (Basel) 2021; 11:diagnostics11101869. [PMID: 34679567 PMCID: PMC8535055 DOI: 10.3390/diagnostics11101869] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/22/2021] [Accepted: 10/07/2021] [Indexed: 12/29/2022] Open
Abstract
Proliferative diabetic retinopathy (PDR) is a major cause of blindness in diabetic individuals. Optical coherence tomography (OCT) and OCT-angiography (OCTA) are noninvasive imaging techniques useful for the diagnosis and assessment of PDR. We aim to review several recent developments using OCT and discuss their present and potential future applications in the clinical setting. An electronic database search was performed so as to include all studies assessing OCT and/or OCTA findings in PDR patients published from 1 January 2020 to 31 May 2021. Thirty studies were included, and the most recently published data essentially focused on the higher detection rate of neovascularization obtained with widefield-OCT and/or OCTA (WF-OCT/OCTA) and on the increasing quality of retinal imaging with quality levels non-inferior to widefield-fluorescein angiography (WF-FA). There were also significant developments in the study of retinal nonperfusion areas (NPAs) using these techniques and research on the impact of PDR treatment on NPAs and on vascular density. It is becoming increasingly clear that it is critical to use adequate imaging protocols focused on optimized segmentation and maximized imaged retinal area, with ongoing technological development through artificial intelligence and deep learning. These latest findings emphasize the growing applicability and role of noninvasive imaging in managing PDR with the added benefit of avoiding the repetition of invasive conventional FA.
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