Evaluating an OCT-based Algorithm of Central Subfield Thickness Estimation on AMD and DME patients

摘要: Purpose: To evaluate the accuracy of an algorithm to estimate Central Subfield Thickness (CST) from OCT volumes for patients with AMD or DME.Methods: We collected OCT volumes from two groups of patients, respectively including exudative AMD (541) and DME (1’568) patients. We refer to them as the AMD group and DME group. All patients received an anti-VEGF treatment, were treated and monitored between 01/2013 and 06/2021. We found 3’974 OCT volumes for the AMD group and 11’501 OCT volumes for the DME group. The algorithm to be evaluated relies on the CE-marked Discovery® layer segmentation algorithm (RetinAI Medical AG, Switzerland) and computes the average retinal thickness in the central-1mm region from the ETDRS grid. For each OCT volume, the true CST was measured independently by two graders and a third grader in case of disagreement. The annotations were performed by the Bern Photographic Reading Center (Inselspital, Universitätsspital Bern, Universitätsklinik für Augenheilkunde, Bern, Switzerland). After removing the ungradable OCT volumes and considering the 99 th percentile of the thicknesses, the AMD group comprises of 3’894 OCT volumes (537 patients) and the DME group of 11'269 OCT volumes (1’526 patients).Results: We reported a strong correlation between the annotated values of CSTs and the predicted ones from the algorithm (R2= 0.96) for both groups. We observed that the algorithm tends to over-estimate the retinal thickness in general, leading however to a small mean absolute error (prediction-annotation), 3.19 μm (95% CI, 2.6–3.8 μm) and 10.68 μm (95% CI, 10.4–11μm) for …