Literature DB >> 32464129

Diabetic Retinopathy Screening Using Smartphone-Based Fundus Imaging in India.

Maximilian W M Wintergerst1, Divyansh K Mishra2, Laura Hartmann1, Payal Shah2, Vinaya K Konana2, Pradeep Sagar2, Moritz Berger3, Kaushik Murali2, Frank G Holz1, Mahesh P Shanmugam2, Robert P Finger4.   

Abstract

PURPOSE: Early detection and treatment can prevent irreversible blindness from diabetic retinopathy (DR), which is the leading cause of visual impairment among working-aged adults worldwide. Some 80% of affected persons live in low- and middle-income countries, yet lack of resources has largely prevented DR screening implementation in these world regions. Smartphone-based fundus imaging (SBFI) allows for low-cost mobile fundus examination using an adapter on a smartphone; however, key aspects such as image quality, diagnostic accuracy, and comparability of different approaches have not been systematically assessed to date.
DESIGN: Evaluation of diagnostic technology. PARTICIPANTS: A total of 381 eyes of 193 patients with diabetes were recruited at outreach eye clinics in South India.
METHODS: We compared 4 technically different approaches of SBFI (3 approaches based on direct and 1 approach based on indirect ophthalmoscopy) in terms of image quality and diagnostic accuracy for DR screening. MAIN OUTCOME MEASURES: Image quality (sharpness/focus, reflex artifacts, contrast, and illumination), field-of-view, examination time, and diagnostic accuracy for DR screening were analyzed against conventional fundus photography and clinical examination.
RESULTS: Smartphone-based fundus imaging based on indirect ophthalmoscopy yielded the best image quality (P < 0.01), the largest field-of-view, and the longest examination time (111 vs. 68-86 seconds, P < 0.0001). Agreement with the reference standard (Cohen's kappa 0.868) and sensitivity/specificity to detect DR were highest for the indirect SBFI approach (0.79/0.99 for any DR and 1.0/1.0 for severe DR, 0.79/1.0 for diabetic maculopathy).
CONCLUSIONS: Smartphone-based fundus imaging can meet DR screening requirements in an outreach setting; however, not all devices are suitable in terms of image quality and diagnostic accuracy. Smartphone-based fundus imaging might aid in alleviating the burden of DR screening in low- and middle-income countries, and these results will allow for a better selection of SBFI devices in field trials for DR screening.
Copyright © 2020 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2020        PMID: 32464129     DOI: 10.1016/j.ophtha.2020.05.025

Source DB:  PubMed          Journal:  Ophthalmology        ISSN: 0161-6420            Impact factor:   12.079


  8 in total

Review 1.  [Smartphone-based fundus photography from the perspective of medical product regulation and IT security].

Authors:  Wolfgang Lauer; Nicole Rämsch-Günther; Dina Truxius
Journal:  Ophthalmologe       Date:  2022-01-11       Impact factor: 1.059

Review 2.  [Smartphone-based fundus imaging: applications and adapters].

Authors:  Linus G Jansen; Thomas Schultz; Frank G Holz; Robert P Finger; Maximilian W M Wintergerst
Journal:  Ophthalmologe       Date:  2021-12-16       Impact factor: 1.059

Review 3.  [Technical and optical aspects of smartphone-based fundus photography : Possibilities and limitations in practice].

Authors:  Jochen Straub; Robert A Sprowl
Journal:  Ophthalmologe       Date:  2022-01-18       Impact factor: 1.059

Review 4.  The Utility of Smartphone-Based Artificial Intelligence Approaches for Diabetic Retinopathy: A Literature Review and Meta-Analysis.

Authors:  Aadil Sheikh; Ahsan Bhatti; Oluwaseun Adeyemi; Muhammad Raja; Ijaz Sheikh
Journal:  J Curr Ophthalmol       Date:  2021-10-22

5.  Optimized hybrid machine learning approach for smartphone based diabetic retinopathy detection.

Authors:  Shubhi Gupta; Sanjeev Thakur; Ashutosh Gupta
Journal:  Multimed Tools Appl       Date:  2022-02-25       Impact factor: 2.577

6.  A Classification Tree Model with Optical Coherence Tomography Angiography Variables to Screen Early-Stage Diabetic Retinopathy in Diabetic Patients.

Authors:  Hongyan Yao; Shanjun Wu; Zongyi Zhan; Zijing Li
Journal:  J Ophthalmol       Date:  2022-02-15       Impact factor: 1.909

7.  Validity of smartphone-based retinal photography (PEEK-retina) compared to the standard ophthalmic fundus camera in diagnosing diabetic retinopathy in Uganda: A cross-sectional study.

Authors:  Ahmed Mohamud Yusuf; Rebecca Claire Lusobya; John Mukisa; Charles Batte; Damalie Nakanjako; Otiti Juliet-Sengeri
Journal:  PLoS One       Date:  2022-09-06       Impact factor: 3.752

8.  Learning curve evaluation upskilling retinal imaging using smartphones.

Authors:  Linus G Jansen; Payal Shah; Bettina Wabbels; Frank G Holz; Robert P Finger; Maximilian W M Wintergerst
Journal:  Sci Rep       Date:  2021-06-16       Impact factor: 4.379

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.