BACKGROUND: In 2018, IDx-DR was approved as a method to determine the degree of diabetic retinopathy (DR) using artificial intelligence (AI) by the FDA. METHODS: We integrated IDx-DR into the consultation at a diabetology focus clinic and report the agreement between IDx-DR and fundoscopy as well as IDx-DR and ophthalmological image assessment and the influence of different camera systems. RESULTS: Adequate image quality in miosis was achieved more frequently with the Topcon camera (n = 456; NW400, Topcon Medical Systems, Oakland, NJ, USA) compared with the Zeiss camera (n = 47; Zeiss VISUCAM 500, Carl Zeiss Meditec AG, Jena, Germany). Overall, IDx-DR analysis in miosis was possible in approximately 60% of the patients. All patients in whom IDx-DR analysis in miosis was not possible could be assessed by fundoscopy with dilated pupils. Within the group of images that could be evaluated, there was agreement between IDx-DR and ophthalmic fundoscopy in approximately 55%, overestimation of severity by IDx-DR in approximately 40% and underestimation in approximately 4%. The sensitivity (specificity) for detecting severe retinopathy requiring treatment was 95.7% (89.1%) for cases with fundus images that could be evaluated and 65.2% (66.7%) when all cases were considered (including those without images in miosis which could be evaluated). The kappa coefficient of 0.334 (p < 0.001) shows sufficient agreement between IDx-DR and physician's image analysis based on the fundus photograph, considering all patients with IDx-DR analysis that could be evaluated. The comparison between IDx-DR and the physician's funduscopy under the same conditions shows a low agreement with a kappa value of 0.168 (p < 0.001). CONCLUSION: The present study shows the possibilities and limitations of AI-assisted DR screening. A major limitation is that sufficient images cannot be obtained in miosis in approximately 40% of patients. When sufficient images were available the IDx-DR and ophthalmological diagnosis matched in more than 50% of cases. Underestimation of severity by IDx-DR occurred only rarely. For integration into an ophthalmologist's practice, this system seems suitable. Without access to an ophthalmologist the high rate of insufficient images in miosis represents an important limitation.
BACKGROUND: In 2018, IDx-DR was approved as a method to determine the degree of diabetic retinopathy (DR) using artificial intelligence (AI) by the FDA. METHODS: We integrated IDx-DR into the consultation at a diabetology focus clinic and report the agreement between IDx-DR and fundoscopy as well as IDx-DR and ophthalmological image assessment and the influence of different camera systems. RESULTS: Adequate image quality in miosis was achieved more frequently with the Topcon camera (n = 456; NW400, Topcon Medical Systems, Oakland, NJ, USA) compared with the Zeiss camera (n = 47; Zeiss VISUCAM 500, Carl Zeiss Meditec AG, Jena, Germany). Overall, IDx-DR analysis in miosis was possible in approximately 60% of the patients. All patients in whom IDx-DR analysis in miosis was not possible could be assessed by fundoscopy with dilated pupils. Within the group of images that could be evaluated, there was agreement between IDx-DR and ophthalmic fundoscopy in approximately 55%, overestimation of severity by IDx-DR in approximately 40% and underestimation in approximately 4%. The sensitivity (specificity) for detecting severe retinopathy requiring treatment was 95.7% (89.1%) for cases with fundus images that could be evaluated and 65.2% (66.7%) when all cases were considered (including those without images in miosis which could be evaluated). The kappa coefficient of 0.334 (p < 0.001) shows sufficient agreement between IDx-DR and physician's image analysis based on the fundus photograph, considering all patients with IDx-DR analysis that could be evaluated. The comparison between IDx-DR and the physician's funduscopy under the same conditions shows a low agreement with a kappa value of 0.168 (p < 0.001). CONCLUSION: The present study shows the possibilities and limitations of AI-assisted DR screening. A major limitation is that sufficient images cannot be obtained in miosis in approximately 40% of patients. When sufficient images were available the IDx-DR and ophthalmological diagnosis matched in more than 50% of cases. Underestimation of severity by IDx-DR occurred only rarely. For integration into an ophthalmologist's practice, this system seems suitable. Without access to an ophthalmologist the high rate of insufficient images in miosis represents an important limitation.
Authors: Frank D Verbraak; Michael D Abramoff; Gonny C F Bausch; Caroline Klaver; Giel Nijpels; Reinier O Schlingemann; Amber A van der Heijden Journal: Diabetes Care Date: 2019-02-14 Impact factor: 19.112
Authors: Christina J Flaxel; Ron A Adelman; Steven T Bailey; Amani Fawzi; Jennifer I Lim; G Atma Vemulakonda; Gui-Shuang Ying Journal: Ophthalmology Date: 2019-09-25 Impact factor: 12.079