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A CNN-aided method to predict glaucoma progression using DARC (Detection of Apoptosing Retinal Cells) by Normando, Eduardo M.; Yap, Tim E.; Maddison, John; Miodragovic, Serge; Bonetti, Paolo; Almonte, Melanie; Mohammad, Nada G.; Ameen, Sally; Crawley, Laura; Ahmed, Faisal; Bloom, Philip A.; Cordeiro, Maria Francesca is a scholarly article available to read on EtoBox.

What is A CNN-aided method to predict glaucoma progression using DARC (Detection of Apoptosing Retinal Cells) about?

## Background: A key objective in glaucoma is to identify those at risk of rapid progression and blindness. recently, a novel first-in-man method for visualising apoptotic retinal cells called darc (detection-of-apoptosing-retinal-cells) was reported. the aim was to develop an automatic cnn-aided method of darc spot detection to enable prediction of glaucoma progression. ## Methods: Anonymised darc images were acquired from healthy control (n=40) and glaucoma (n=20) phase 2 clinical trial subjects (isrctn10751859) from which 5 observers manually counted spots. the cnn-aided algorithm was trained and validated using manual counts from control subjects, and then tested on glaucoma eyes. ## Results: The algorithm had 97.0% accuracy, 91.1% sensitivity and 97.1% specificity to spot detection when compared to manual grading of 50% controls. it was next tested on glaucoma patient eyes defined as progressing or stable based on a significant (p<0.05) rate of progression using oct-retinal nerve fibre layer measurements at 18 months. it demonstrated 85.7% sensitivity, 91.7% specificity with auc of 0.89, and a significantly (p=0.0044) greater darc count in those patients who later progressed.

Author

Normando, Eduardo M.; Yap, Tim E.; Maddison, John; Miodragovic, Serge; Bonetti, Paolo; Almonte, Melanie; Mohammad, Nada G.; Ameen, Sally; Crawley, Laura; Ahmed, Faisal; Bloom, Philip A.; Cordeiro, Maria Francesca

Publisher

Expert Reviews; Informa UK (Taylor & Francis); Taylor & Francis; Informa UK Limited (ISSN 1473-7159)

Published

2020

Language

EN