The three-dimensional structural configuration of the central retinal vessel trunk and branches as a glaucoma biomarker

PURPOSE: To assess whether the 3-dimensional (3D) structural configuration of the central retinal vessel trunk and its branches (CRVT & B) could be used as a diagnostic marker for glaucoma. DESIGN: Retrospective, deep-learning approach diagnosis study. METHODS: We trained a deep learning network to automatically segment the CRVT & B from the B-scans of the optical coherence tomography (OCT) volume of the op -tic nerve head. Subsequently, 2 different approaches were used for glaucoma diagnosis using the structural configuration of the CRVT & B as extracted from the OCT volumes. In the first approach, we aimed to provide a diagnosis using only 3D convolutional neural networks and the 3D structure of the CRVT & B. For the second approach, we projected the 3D structure of the CRVT & B ortho-graphically onto sagittal, frontal, and transverse planes to obtain 3 two-dimensional (2D) images, and then a 2D convolutional neural network was used for diagnosis. The segmentation accuracy was evaluated using the Dice co-efficient, whereas the diagnostic accuracy was assessed using the area under the receiver operating characteristic curves (AUCs). The diagnostic performance of the CRVT & B was also compared with that of retinal nerve fiber layer (RNFL) thickness (calculated in the same cohorts). RESULTS: Our segmentation network was able to efficiently segment retinal blood vessels from OCT scans. On a test set, we achieved a Dice coefficient of 0.81 & PLUSMN; 0.07. The 3D and 2D diagnostic networks were able to differentiate glaucoma from nonglaucoma subjects with accuracies of 82.7% and 83.3%, respectively. The corresponding AUCs for the CRVT & B were 0.89 and 0.90, higher than those obtained with RNFL thickness alone (AUCs ranging from 0.74 to 0.80). CONCLUSIONS: Our work demonstrated that the diagnostic power of the CRVT & B is superior to that of a gold-standard glaucoma parameter, that is, RNFL thick-ness. Our work also suggested that the major retinal blood vessels form a skeleton -the configuration of which may be representative of major optic nerve head structural changes as typically observed with the development and progression of glaucoma. (C) 2022 Elsevier Inc. All rights reserved.

Automated summary

This study demonstrates the potential of using the 3D structural configuration of the central retinal vessel trunk and its branches as a diagnostic marker for glaucoma, showing higher accuracy in diagnosis compared to traditional RNFL thickness measurements. The segmentation network and diagnostic networks achieved good performance in differentiating glaucoma from non-glaucoma subjects.