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Clinical Sciences |

Automated Analysis of Retinal Images for Detection of Referable Diabetic Retinopathy

Michael D. Abràmoff, MD, PhD; James C. Folk, MD; Dennis P. Han, MD; Jonathan D. Walker, MD; David F. Williams, MD, MBA; Stephen R. Russell, MD; Pascale Massin, MD, PhD; Beatrice Cochener, MD, PhD; Philippe Gain, MD, PhD; Li Tang, PhD; Mathieu Lamard, PhD; Daniela C. Moga, MD, PhD; Gwénolé Quellec, PhD; Meindert Niemeijer, PhD
JAMA Ophthalmol. 2013;131(3):351-357. doi:10.1001/jamaophthalmol.2013.1743.
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Importance  The diagnostic accuracy of computer detection programs has been reported to be comparable to that of specialists and expert readers, but no computer detection programs have been validated in an independent cohort using an internationally recognized diabetic retinopathy (DR) standard.

Objective  To determine the sensitivity and specificity of the Iowa Detection Program (IDP) to detect referable diabetic retinopathy (RDR).

Design and Setting  In primary care DR clinics in France, from January 1, 2005, through December 31, 2010, patients were photographed consecutively, and retinal color images were graded for retinopathy severity according to the International Clinical Diabetic Retinopathy scale and macular edema by 3 masked independent retinal specialists and regraded with adjudication until consensus. The IDP analyzed the same images at a predetermined and fixed set point. We defined RDR as more than mild nonproliferative retinopathy and/or macular edema.

Participants  A total of 874 people with diabetes at risk for DR.

Main Outcome Measures  Sensitivity and specificity of the IDP to detect RDR, area under the receiver operating characteristic curve, sensitivity and specificity of the retinal specialists' readings, and mean interobserver difference (κ).

Results  The RDR prevalence was 21.7% (95% CI, 19.0%-24.5%). The IDP sensitivity was 96.8% (95% CI, 94.4%-99.3%) and specificity was 59.4% (95% CI, 55.7%-63.0%), corresponding to 6 of 874 false-negative results (none met treatment criteria). The area under the receiver operating characteristic curve was 0.937 (95% CI, 0.916-0.959). Before adjudication and consensus, the sensitivity/specificity of the retinal specialists were 0.80/0.98, 0.71/1.00, and 0.91/0.95, and the mean intergrader κ was 0.822.

Conclusions  The IDP has high sensitivity and specificity to detect RDR. Computer analysis of retinal photographs for DR and automated detection of RDR can be implemented safely into the DR screening pipeline, potentially improving access to screening and health care productivity and reducing visual loss through early treatment.

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Figures

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Figure 1. Flow of the 874 participants throughout the study, including 184 patients with true-positive results, 406 with true-negative results, 6 with false-negative results, and 278 with false-positive results. Referable diabetic retinopathy is defined as more than mild nonproliferative retinopathy and/or macular edema according to the International Clinical Diabetic Retinopathy criteria by an adjudicated consensus of 3 retinal specialists.

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Figure 2. Right and left eye images of 6 of the 874 patients who had false-negative results at the set point (set point of 0.101) when comparing the Iowa Detection Program (IDP) output with the consensus International Clinical Diabetic Retinopathy (ICDR) severity level ratings (consensus) by 3 retinal specialists. Each set of eyes displays the consensus ICDR severity level (0 indicates no diabetic retinopathy [DR]; 1, mild DR; 2, moderate DR; 3, severe DR; and 4, proliferative DR) followed by the consensus ICDR diabetic macular edema (DME) severity level (0 indicates no apparent DME; 1, apparent DME).

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Grahic Jump Location

Figure 3. Receiver operator characteristics curve of the Iowa Detection Program (IDP) to detect referable diabetic retinopathy, defined as more than mild nonproliferative retinopathy and/or macular edema according to International Clinical Diabetic Retinopathy criteria by an adjudicated consensus of 4 retinal specialists and 2 selected set points. The area under the curve is 0.9373.

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