Diabetic Retinopathy Screening Using Artificial Intelligence and Handheld Smartphone-Based Retinal Camera

Malerbi, Fernando Korn; Andrade, Rafael; Morales, Paulo Henrique; Stuchi, José Augusto; Lencione, Diego; Paulo, Jean Vitor de; Carvalho, Mayana Pereira; Nunes, Fabrícia Silva; Rocha, Roseanne Montargil; Ferraz, Daniel; Belfort, Rubens

doi:10.1177/1932296820985567

Cited by 40 publications

(36 citation statements)

References 32 publications

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“…Patient self-screening, which has been shown to be effective using the near card [35] and Alleye program [36], may help optimize prioritization protocols for clinic visit and intravitreal injections. Moreover, telescreening using fundus photography and artificial intelligence-based classification of diabetic retinopathy have demonstrated high specificity and sensitivity in diagnosing diabetic retinopathy [37][38][39]. Furthermore, home-based monitoring of patients with DME with portable OCT systems will likely be beneficial [40].…”

Section: Discussionmentioning

confidence: 99%

The Impact of COVID-19 on Diabetic Retinopathy Monitoring and Treatment

Ahmed

Liu

2021

Curr Diab Rep

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Purpose of Review Diabetic retinopathy (DR) is one of the leading causes of vision loss worldwide. Although screening and early treatment guidelines for DR have significantly reduced the disease burden, restrictions related to the COVID-19 pandemic have changed real-world practice patterns in the management of DR. This review summarizes evolving guidelines and outcomes of the treatment of DR in the setting of the pandemic. Recent Findings Intravitreal injections for DR have decreased significantly globally during the pandemic, ranging from approximately 30 to nearly 100% reduction, compared to corresponding timepoints in 2019. Most studies on functional outcomes show a decrease in visual acuity on delayed follow-up. Summary Changing practice patterns in the management of DR has led to fewer intravitreal injections and overall reduction in visual acuity on follow-up. As COVID variants emerge, it will be necessary to continue evaluating practice guidelines.

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Section: Discussionmentioning

confidence: 99%

The Impact of COVID-19 on Diabetic Retinopathy Monitoring and Treatment

Ahmed

Liu

2021

Curr Diab Rep

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“…The present study assessed the macular tomographic characteristics of T2DM patients with suspected DME as per the screening protocol that comprised a previously validated, high-sensitivity (97.8%) algorithmic tool for the detection of more than mild DR [ 4 ]; DME was confirmed by OCT in 85.3% of such patients. DR screening programs are a fundamental milestone for the prevention of blindness secondary to diabetes, but they overwhelm health systems, as hundreds of millions of individuals need periodical screening, with increasing demands as diabetes prevalence grows globally [ 3 ].…”

Section: Discussionmentioning

confidence: 99%

“…This was a retrospective study that assessed the tomographic presence of DME in a sample of 366 of individuals over 18 years old with a previous type 2 diabetes mellitus (T2DM) diagnosis and followed at primary health care units, who were screened for DR with CFPs of both eyes, obtained with a portable smartphone-based retinal camera and an assistive deep learning (DL) AI algorithm designed to detect fundus abnormalities, which was trained with a dataset of images exclusively obtained with a portable retinal camera (Phelcom Technologies, São Carlos, Brazil) [ 4 ]. The algorithm generates a heatmap that flags suspected retinal alterations with a color scale, from blue (low importance) to red (high importance) (Fig.…”

Section: Methodsmentioning

confidence: 99%

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Diabetic Macular Edema Screened by Handheld Smartphone-based Retinal Camera and Artificial Intelligence

Malerbi

Mendes²,

Barboza³

et al. 2021

J Med Syst

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Our aim was to assess the tomographic presence of diabetic macular edema in type 2 diabetes patients screened for diabetic retinopathy with color fundus photographs and an artificial intelligence algorithm. Color fundus photographs obtained with a low-cost smartphone-based handheld retinal camera were analyzed by the algorithm; patients with suspected macular lesions underwent ocular coherence tomography. A total of 366 patients were screened; diabetic macular edema was suspected in 34 and confirmed in 29 individuals, with average age 60.5 ± 10.9 years and glycated hemoglobin 9.8 ± 2.4%; use of insulin, statins, and aspirin were reported in 44.8%, 37.9%, and 34.5% of individuals, respectively; systemic blood hypertension, dyslipidemia, abdominal obesity, chronic kidney disease, and risk for diabetic foot ulcers were present in 100%, 58.6%, 62.1%, 48.3%, and 27.5% of individuals, respectively. Proliferative diabetic retinopathy was present in 31% of patients with macular edema; severity level was associated with albuminuria (p = 0.028). Eyes with macular edema had average central macular thickness 329.89 ± 80.98 m ; intraretinal cysts, sub retinal fluid, hyper-reflective foci, epiretinal membrane, and vitreomacular traction were found in 87.2%, 6.4%, 85.1%, 10.6%, and 6.4% of eyes, respectively. Diabetic retinopathy screening overwhelms health systems and is typically based on color fundus photographs, with high false-positive rates for the detection of diabetic macular edema. The present, semi-automated strategy comprising artificial intelligence algorithms integrated with smartphone-based retinal cameras could improve screening in low-resource settings with limited availability of ocular coherence tomography, allowing increased access rates and ultimately contributing to tackle preventable blindness.

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“…This specially aids in decentralising multi-speciality health care in developing countries. [21][22][23][24][25][26][27][28][29][30][31]…”

Section: Smartphones As Indirect/wide Angled Ophthalmoscopesmentioning

confidence: 99%

Smartphone Ophthalmoscopy: is there a place for it?

Pujari¹

2021

OPTH

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Smartphone technology is advancing at a rapid pace. Their role in day-to-day life is becoming more and more intricate and irreplaceable. Of late, they have gained immense importance in different medical specialities where they possess an active ability to guide the clinician. This is particularly evident in ophthalmology, where the constantly evolving camera-illumination systems and the artificial intelligence integrated technology have unravelled many novel observations for non-contact posterior segment imaging. The scope of this review is to highlight the role of smartphones as ophthalmoscopes (direct as well as indirect). Nevertheless, their limitations and future directions are also stated here with the intention of making progress in the field of smartphone fundus imaging.

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Diabetic Retinopathy Screening Using Artificial Intelligence and Handheld Smartphone-Based Retinal Camera

Cited by 40 publications

References 32 publications

The Impact of COVID-19 on Diabetic Retinopathy Monitoring and Treatment

The Impact of COVID-19 on Diabetic Retinopathy Monitoring and Treatment

Diabetic Macular Edema Screened by Handheld Smartphone-based Retinal Camera and Artificial Intelligence

Smartphone Ophthalmoscopy: is there a place for it?

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