Exploratory Radiomic Analysis of Anterior Segment OCT Images in Patients with Vitreoretinal Lymphoma

To explore the ability of a radiomics-based classification model of identifying anterior segment optical coherence tomography (AS-OCT) image features compatible with active vitreoretinal lymphoma (VRL). The secondary aim was to investigate the possible association between these image features and aqueous humour molecular biomarkers used in VRL assessment.

We conducted a retrospective single-centre study of patients with biopsy-proven VRL, and at least one series of baseline or follow-up AS-OCT image scans and an aqueous tap. We extracted radiomic features from a manually delineated region of interest (ROI) in anterior vitreous AS-OCT images, five were selected and trained XGBoost classifiers with leave-two-patients-out cross-validation (L2PO) to distinguish active from inactive disease, using AUC-ROC as performance metric. If present, interleukin (IL)-10:IL-6 ratios were correlated with imaging features using logistic regression analyses.

Eight patients (22 visits total, 43 eyes) were analysed. From the L2PO analysis, we obtained an AUC metric of 0.74 with a 95% confidence interval (CI) of 0.68-0.81. GLRLM_LRLGE was the feature most consistently associated with disease activity. When IL-10:IL-6 > 1 was used as the outcome, the association weakened (all p-values > 0.05), though mean and median values showed the same direction of effect.

This pilot study explored the potential innovative role of radiomics to analyse VRL activity status using AS-OCT images. Although it is currently far from being a clinical tool, radiomic analysis could be the subject of future investigations aiming to refine non-invasive monitoring strategies. Prospective studies with standardized, simultaneous serial imaging and aqueous tap are required.