Purpose
To identify optical coherence tomography (OCT) features to predict the course of central serous chorioretinopathy (CSC) with an artificial intelligence (AI) based program
Methods
Multicenter, observational study with a retrospective design. Treatment-naïve patients with acute CSC and chronic CSC were enrolled. Baseline OCTs were examined by an AI-developed platform (Discovery® OCT Fluid and Biomarker Detector, RetinAI AG, Switzerland). Through this platform, automated retinal layers thicknesses and volumes, including intaretinal and subretinal fluid (IRF, SRF) and pigment epithelium detachment (PED) were measured. Baseline OCT features were compared between acute CSC and chronic CSC patients
Results
160 eyes of 144 patients with CSC were enrolled, of which 100 had chronic CSC and 60 acute CSC. Retinal layer analysis of baseline OCT scans showed that the inner nuclear layer, the outer nuclear layer and the photoreceptor-RPE complex were significantly thicker at baseline in eyes with acute CSC in comparison with those with chronic CSC (p<0.001). Similarly, choriocapillaris and choroidal stroma and retinal thickness (RT) were thicker in acute CSC than chronic CSC eyes (p=0.001). Volume analysis revealed average greater SRF volumes in the aCSC group in comparison with cCSC (p=0.041)
Conclusion
OCT features may be helpful to predict the clinical course of CSC. The baseline presence of an increased thickness in the outer retinal layers, choriocapillaris and choroidal stroma, and SRF volume seems to be associated with acute course of the disease