Retina (Philadelphia, Pa.) · 2026
DRSPLUS RETINOGRAPHER IN PATIENTS WITH DIABETES: A Comparison Study by Consensus Grading, Reading Center, and Artificial Intelligence.
СтатьяНаблюдательное исследованиеСравнительное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Parravano Mariacristina, Costanzo Eliana, De Geronimo Daniele, Varano Monica, Rossi Tommaso, Rui Chiara, Gazzina Silvia, Querques Giuseppe
Аннотация
PURPOSE: To evaluate the gradable rate of the retinal images acquired with DRSplus retinographer in patients with diabetes and to estimate the diabetic retinopathy (DR) severity, comparing different methods of analysis and grading.
METHODS: Prospective, cross-sectional, observational study. A mosaic of overlapped retinal images in nonmydriatic condition was acquired, evaluating the gradable images rate at both image and eye-levels, from the human-study team (consensus grading), Reading Center, and an Artificial Intelligence (AI) system, respectively. The DR severity was graded by the Reading Center and the AI.
RESULTS: A total of 844 images of 422 eyes from 224 patients were included. The gradable rate was 87.4%, 97.4%, and 96.9% at image-level and was 81.3%, 97.4%, and 95.0% at eye-level, according to the consensus grading, the Reading Center, and the AI, respectively. Artificial intelligence sensitivity for detecting referable DR was 97.3%, the specificity was 80.4%, and the accuracy was 86.6%.
CONCLUSION: DRSplus retinographer allowed to image the retina in nonmydriatic condition in more than 80% of eyes, with a higher gradable rate with Reading Center and AI in comparison with consensus grading. The estimation of the DR severity showed a high sensitivity for referral cases for AI system, indicating the potentialities of telemedicine-based tool for the DR screening.
METHODS: Prospective, cross-sectional, observational study. A mosaic of overlapped retinal images in nonmydriatic condition was acquired, evaluating the gradable images rate at both image and eye-levels, from the human-study team (consensus grading), Reading Center, and an Artificial Intelligence (AI) system, respectively. The DR severity was graded by the Reading Center and the AI.
RESULTS: A total of 844 images of 422 eyes from 224 patients were included. The gradable rate was 87.4%, 97.4%, and 96.9% at image-level and was 81.3%, 97.4%, and 95.0% at eye-level, according to the consensus grading, the Reading Center, and the AI, respectively. Artificial intelligence sensitivity for detecting referable DR was 97.3%, the specificity was 80.4%, and the accuracy was 86.6%.
CONCLUSION: DRSplus retinographer allowed to image the retina in nonmydriatic condition in more than 80% of eyes, with a higher gradable rate with Reading Center and AI in comparison with consensus grading. The estimation of the DR severity showed a high sensitivity for referral cases for AI system, indicating the potentialities of telemedicine-based tool for the DR screening.