Predicting Age-related Macular Degeneration Progression from Retinal Optical Coherence Tomography with Intra-Subject Temporal Consistency

Arunava Chakravarty, Taha Emre, Dmitrii Lachinov, Antoine Rivail, Ursula Schmidt-Erfurth, Hrvoje Bogunović

Keywords: Survival Analysis, Optical Coherence Tomography, retina, Disease progression, Disease Forecasting, Prognosis, Age-related Macular Degeneration

Abstract:

The wide variability in the progression rates of Age-Related Macular Degeneration (AMD) and the absence of well-established clinical biomarkers make it difficult to predict an individual's risk of AMD progression from intermediate stage (iAMD) to late dry stage (dAMD) using Optical Coherence Tomography (OCT) scans.
To address this challenge, we propose to jointly train an AMD stage classifier to discriminate between iAMD and dAMD with a Neural-ODE that models the future trajectory of the disease progression in the learned embedding space. A temporal ordering is imposed such that the distance of a scan from the decision hyperplane of the AMD stage classifier is inversely related to its time-to-conversion. In addition, an intra-subject temporal consistency in the predicted conversion risk scores is ensured by incorporating a pair of longitudinal scans from the same eye during training. We evaluated our proposed method on a longitudinal dataset comprising 235 eyes (3,534 OCT scans) with 40 converters. The results demonstrate the effectiveness of our approach, achieving an average area under the ROC of 0.84 for predicting conversion within the next 6, 12, 18 and 24 months. Additionally, the Concordance Index of 0.78 surpasses the performance of several popular methods for survival analysis.

Submission Number: 208