The Role of Telemedicine, In-Home Testing and Artificial Intelligence to Alleviate an Increasingly Burdened Healthcare System: Diabetic Retinopathy

Pieczyński, Janusz; Kuklo, Patrycja; Grzybowski, Andrzej

doi:10.1007/s40123-021-00353-2

Cited by 31 publications

(24 citation statements)

References 124 publications

(378 reference statements)

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“…In addition to these novel technologies, automated diagnosis by artificial intelligence is the most noteworthy topic in DR imaging, and many screening programs with or without telemedicine have been studied [ 102 ]. Smartphone-based automated diagnosing software was also reported [ 103 ] and has great potential in management of DR for the under-resourced African population [ 104 ].…”

Section: Discussionmentioning

confidence: 99%

Progress of Imaging in Diabetic Retinopathy—From the Past to the Present

Horie

Ohno‐Matsui

2022

Diagnostics

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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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Section: Discussionmentioning

confidence: 99%

Progress of Imaging in Diabetic Retinopathy—From the Past to the Present

Horie

Ohno‐Matsui

2022

Diagnostics

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“…Nevertheless, it should be noted that for a proper assessment, correct segmentation is necessary, and often there is improvement in NVC recognition with manual segmentation [79,81,86,93,103,104]. In the future, the accuracy of NVC detection in vitreoretinal slabs might increase with improvement of auto segmentation, deep learning and artificial intelligence [81,86,[107][108][109][110][111]. IRMAs seem to generate higher false positive rates due to the retinal slab image, despite the vitreoretinal slab image not showing extension into the vitreous cavity [82].…”

Section: Discussionmentioning

confidence: 99%

Update on Optical Coherence Tomography and Optical Coherence Tomography Angiography Imaging in Proliferative Diabetic Retinopathy

2021

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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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“…Apart from the medico‐legal and ethical implications, another drawback to date has been the need to develop a large enough database to validate the algorithms used. The potential, however, is large with the suggestion that easy‐to‐use retinal smartphone adapters using AI can in time be used in the home setting and easily transmitted remotely to a central database 21 …”

Section: Diabetic Retinopathy: Image Reportingmentioning

confidence: 99%

“…The potential, however, is large with the suggestion that easyto-use retinal smartphone adapters using AI can in time be used in the home setting and easily transmitted remotely to a central database. 21 The future Technology, big data, and AI with its various manifestations, are developing apace. Despite the advances which have been made there is still a range of barriers to overcome before we reach a fully utopian new approach to diabetes care.…”

Section: Diabetic Retinopathy: Image Reportingmentioning

confidence: 99%

Diabetes care: is big data the future?

Begg

2022

Practical Diabetes

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The Role of Telemedicine, In-Home Testing and Artificial Intelligence to Alleviate an Increasingly Burdened Healthcare System: Diabetic Retinopathy

Cited by 31 publications

References 124 publications

Progress of Imaging in Diabetic Retinopathy—From the Past to the Present

Progress of Imaging in Diabetic Retinopathy—From the Past to the Present

Update on Optical Coherence Tomography and Optical Coherence Tomography Angiography Imaging in Proliferative Diabetic Retinopathy

Diabetes care: is big data the future?

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