Improving Glaucoma Diagnosis with Multimodal Analysis Using Optical Coherence Tomography Angiography
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose: To assess the role of multimodal Optical Coherence Tomography Angiography (OCTA) analysis in glaucoma diagnosis. Methods: This Institutional Review Board (IRB) approved, retrospective, single academic center study consisted of 357 patients (635 eyes), including 193 healthy, 99 Ocular Hypertension (OHT), 128 open angle Glaucoma Suspect (GS) and 215 POAG eyes. The following clinical data was collected for all patients: Retinal Nerve Fiber Layer Thickness (RNFL), Cup/Disc Ratio (CDR), Central Corneal Thickness (CCT) and history of myopia, hyperopia, Hypertension (HTN), Diabetes (DM) and Cardiovascular Disease (CVD). OCTA scans of the optic nerve head and macula were analyzed using Open-Source Software (OpenCV), calculating Vessel Density (VD), Vessel Length Density (VLD) and fractal dimension (FD). The data was divided into a training and testing set. Using the training data, we created five diagnostic models (demographic, VD-FD, VLD-FD, clinical and multimodal). We calculated Receiver Operating Curves (ROC) using the testing data and compared the models using Area Under the Curve (AUC) analysis. Results: VD, VLD and FD were significantly reduced in the POAG group (p < 0.0001). The multimodal model performed the best (AUC = 0.898), followed by the clinical model (AUC = 0.888), the VD-FD model (AUC = 0.780), the VLD-FD model (AUC = 0.774) and the demographic model (AUC = 0.741). The multimodal model performed significantly better than all other models (p = 0.035). Conclusion: Our analysis indicates that diagnosing glaucoma with a multimodal approach utilizing OCTA is superior to using clinical and structural data alone.
Author: Karanjit S Kooner
Subfield: Ophthalmology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4415494288