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Validation of automated screening for referable diabetic retinopathy with the IDx‐DR device in the Hoorn Diabetes Care System
Author(s) -
van der Heijden Amber A,
Abramoff Michael D,
Verbraak Frank,
Hecke Ma V,
Liem Albert,
Nijpels Giel
Publication year - 2018
Publication title -
acta ophthalmologica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.534
H-Index - 87
eISSN - 1755-3768
pISSN - 1755-375X
DOI - 10.1111/aos.13613
Subject(s) - medicine , diabetic retinopathy , retinopathy , diabetes mellitus , retinal , grading (engineering) , predictive value , ophthalmology , endocrinology , civil engineering , engineering
Abstract Purpose To increase the efficiency of retinal image grading, algorithms for automated grading have been developed, such as the IDx‐DR 2.0 device. We aimed to determine the ability of this device, incorporated in clinical work flow, to detect retinopathy in persons with type 2 diabetes. Methods Retinal images of persons treated by the Hoorn Diabetes Care System (DCS) were graded by the IDx‐DR device and independently by three retinal specialists using the International Clinical Diabetic Retinopathy severity scale (ICDR) and EURODIAB criteria. Agreement between specialists was calculated. Results of the IDx‐DR device and experts were compared using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), distinguishing between referable diabetic retinopathy (RDR) and vision‐threatening retinopathy (VTDR). Area under the receiver operating characteristic curve (AUC) was calculated. Results Of the included 1415 persons, 898 (63.5%) had images of sufficient quality according to the experts and the IDx‐DR device. Referable diabetic retinopathy (RDR) was diagnosed in 22 persons (2.4%) using EURODIAB and 73 persons (8.1%) using ICDR classification. Specific intergrader agreement ranged from 40% to 61%. Sensitivity, specificity, PPV and NPV of IDx‐DR to detect RDR were 91% (95% CI: 0.69–0.98), 84% (95% CI: 0.81–0.86), 12% (95% CI: 0.08–0.18) and 100% (95% CI: 0.99–1.00; EURODIAB) and 68% (95% CI: 0.56–0.79), 86% (95% CI: 0.84–0.88), 30% (95% CI: 0.24–0.38) and 97% (95% CI: 0.95–0.98; ICDR). The AUC was 0.94 (95% CI: 0.88–1.00; EURODIAB) and 0.87 (95% CI: 0.83–0.92; ICDR). For detection of VTDR, sensitivity was lower and specificity was higher compared to RDR. AUC's were comparable. Conclusion Automated grading using the IDx‐DR device for RDR detection is a valid method and can be used in primary care, decreasing the demand on ophthalmologists.