Literature DB >> 18406188

Screening of diabetic retinopathy: effect of field number and mydriasis on sensitivity and specificity of digital fundus photography.

F Aptel1, P Denis, F Rouberol, C Thivolet.   

Abstract

PURPOSE: To evaluate the sensitivity and specificity of one- and three-field, nonmydriatic and mydriatic, and 45 degrees digital colour photography compared with mydriatic indirect ophthalmoscopy for diabetic retinopathy (DR) screening.
METHODS: A group of 79 patients (158 eyes) were included in this prospective study. Colour fundus photographs were taken with a Topcon TRC-NW6S digital camera, using four different techniques--single-field nonmydriatic; three-field nonmydriatic; single-field mydriatic; and three-field mydriatic--followed by dilated ophthalmoscopy. Two independent ophthalmologists classified blinded photographs according to the presence or absence of specific diabetic retinal findings. The sensitivity, specificity and agreement (kappa analyses) of the four methods were calculated for the presence or absence of DR and for all diabetic retinal findings.
RESULTS: The sensitivity and specificity of digital photography compared with ophthalmoscopy for detection of DR were, respectively: 77 and 99% using single-field nonmydriatic; 92 and 97% using three-field nonmydriatic; 90 and 98% using single-field mydriatic; 97 and 98% using three-field mydriatic. The degrees of agreement for the four methods were 0.82, 0.90, 0.90 and 0.95, respectively. For specific retinal findings, sensitivity was greater for detection of hard exudates, nerve fibre layer haemorrhage and venous beading, and lower for detection of microaneurysms, dot-blot haemorrhage, cotton wool spots and intraretinal microvascular anomalies.
CONCLUSION: The three-field strategy without pupil dilation represents a good compromise, with reasonable sensitivity and good comfort (short examination duration, able to drive after photography) favouring patient compliance with the screening programme.

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Mesh:

Year:  2008        PMID: 18406188     DOI: 10.1016/j.diabet.2007.12.007

Source DB:  PubMed          Journal:  Diabetes Metab        ISSN: 1262-3636            Impact factor:   6.041


  26 in total

1.  Link between retinopathy and nephropathy caused by complications of diabetes mellitus type 2.

Authors:  Pavel Kotlarsky; Arkady Bolotin; Karina Dorfman; Boris Knyazer; Tova Lifshitz; Jaime Levy
Journal:  Int Ophthalmol       Date:  2014-11-13       Impact factor: 2.031

2.  Diabetic retinopathy screening using single-field digital fundus photography at a district level in Costa Rica: a pilot study.

Authors:  Joaquin Martinez; Erick Hernandez-Bogantes; Lihteh Wu
Journal:  Int Ophthalmol       Date:  2011-01-28       Impact factor: 2.031

3.  An exudate detection method for diagnosis risk of diabetic macular edema in retinal images using feature-based and supervised classification.

Authors:  D Marin; M E Gegundez-Arias; B Ponte; F Alvarez; J Garrido; C Ortega; M J Vasallo; J M Bravo
Journal:  Med Biol Eng Comput       Date:  2018-01-10       Impact factor: 2.602

4.  Comparison Among Methods of Retinopathy Assessment (CAMRA) Study: Smartphone, Nonmydriatic, and Mydriatic Photography.

Authors:  Martha E Ryan; Ramachandran Rajalakshmi; Vijayaraghavan Prathiba; Ranjit Mohan Anjana; Harish Ranjani; K M Venkat Narayan; Timothy W Olsen; Viswanathan Mohan; Laura A Ward; Michael J Lynn; Andrew M Hendrick
Journal:  Ophthalmology       Date:  2015-07-16       Impact factor: 12.079

5.  Screening for vision-threatening diabetic retinopathy in South India: comparing portable non-mydriatic and standard fundus cameras and clinical exam.

Authors:  S Sengupta; M D Sindal; C G Besirli; S Upadhyaya; R Venkatesh; L M Niziol; A L Robin; M A Woodward; P A Newman-Casey
Journal:  Eye (Lond)       Date:  2017-09-15       Impact factor: 3.775

6.  [Diabetic retinopathy: comparison of the diagnostic features of ultra-widefield scanning laser ophthalmoscopy Optomap with ETDRS 7-field fundus photography].

Authors:  M Kernt; F Pinter; I Hadi; C Hirneiss; C Haritoglou; A Kampik; M W Ulbig; A S Neubauer
Journal:  Ophthalmologe       Date:  2011-02       Impact factor: 1.059

7.  Statistics of optical coherence tomography data from human retina.

Authors:  Norberto Mauricio Grzywacz; Joaquín de Juan; Claudia Ferrone; Daniela Giannini; David Huang; Giorgio Koch; Valentina Russo; Ou Tan; Carlo Bruni
Journal:  IEEE Trans Med Imaging       Date:  2010-03-18       Impact factor: 10.048

8.  Evaluation of diabetic retinopathy screening using a non-mydriatic retinal digital camera in primary care settings in south Israel.

Authors:  Yossi Mizrachi; Boris Knyazer; Sara Guigui; Shirley Rosen; Tova Lifshitz; Nadav Belfair; Itamar Klemperer; Marina Schneck; Jaime Levy
Journal:  Int Ophthalmol       Date:  2013-12-01       Impact factor: 2.031

9.  Predictors of Photographic Quality with a Handheld Nonmydriatic Fundus Camera Used for Screening of Vision-Threatening Diabetic Retinopathy.

Authors:  Jose R Davila; Sabyasachi S Sengupta; Leslie M Niziol; Manavi D Sindal; Cagri G Besirli; Swati Upadhyaya; Maria A Woodward; Rengaraj Venkatesh; Alan L Robin; Joseph Grubbs; Paula Anne Newman-Casey
Journal:  Ophthalmologica       Date:  2017-07-05       Impact factor: 3.250

Review 10.  Retinal Imaging Techniques for Diabetic Retinopathy Screening.

Authors:  James Kang Hao Goh; Carol Y Cheung; Shaun Sebastian Sim; Pok Chien Tan; Gavin Siew Wei Tan; Tien Yin Wong
Journal:  J Diabetes Sci Technol       Date:  2016-02-01
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