Changes in the Foveal Outer Nuclear Layer of Central Serous Chorioretinopathy Patients Over the Disease Course and Their Response to Photodynamic Therapy

Objective:To investigate the association between foveal outer nuclear layer (ONL) thickness and the natural course of central serous chorioretinopathy (CSC), as well as the thickness change after photodynamic therapy (PDT), exploring the PDT timing for CSC.Methods:This retrospective consecutive case series included 358 CSC patients between January 2014 and December 2019. All patients were divided into four groups depending on disease duration: Group A: ≤1 month; Group B: >1 and ≤3 months; Group C: >3 and≤6 months and Group D: >6 months. Foveal ONL thickness of the CSC eye and the clinically healthy fellow eye were measured and compared in all patients. Fifty-six patients were successfully treated with half-dose of PDT, showing complete subretinal fluid absorption, were followed up for more than 6 months and further investigated. The recovery of foveal ONL thickness was analyzed in the affected eyes of patients with different disease duration.Results:No significant reduction was found in CSC foveal ONL thickness (μm) compared to the fellow eye in patients with disease duration less than 1 week (112.3 ± 12.2 vs. 116.7 ± 15.3, P = 0.268). Patients with longer disease duration had varying degrees of ONL thinning compared to the contralateral eye (all P < 0.05) and this difference was more pronounced in patients with disease duration greater than 6 months (75.8 ± 12.9 vs. 113.0 ± 11.5, P < 0.001). At 6-month follow-up after PDT, foveal ONL thickness of patients with <1 month disease duration recovered significantly from onset (97.3 ± 18.2 to 113.6 ± 8.7, P < 0.001) and became similar to that of the healthy fellow eye. Foveal ONL thickness of patients with duration>1 and≤3 months recovered significantly (88.5 ± 11.5 to 95.8 ± 11.3, P = 0.012) but remained thinner than that of the healthy fellow eye. Foveal ONL thickness did not improve significantly in cases with disease duration longer than 3 months (P > 0.05).Conclusion:Foveal ONL thinning was positively associated with disease duration prior to treatment suggesting that longer disease duration limits scope for foveal ONL recovery. CSC patients should be treated with PDT as soon as possible to prevent disease development and reduced visual function.

Factors Predicting Response to Selective Retina Therapy in Patients with Chronic Central Serous Chorioretinopathy

This retrospective study aimed to assess the safety and efficacy of selective retina therapy (SRT) with real-time feedback-controlled dosimetry (RFD) for chronic central serous chorioretinopathy (CSC) and to evaluate factors predictive of treatment response. We included 137 eyes of 135 patients with chronic CSC. SRT was performed to cover each of the leakage areas on fundus fluorescein angiography. Changes in mean best-corrected visual acuity (BCVA), central macular thickness (CMT), and subretinal fluid (SRF) height were evaluated at baseline and at 3 and 6 months after treatment. Complete SRF resolution was observed in 52.6% (72/137 eyes) and 90.5% (124/137 eyes) at 3 and 6 months, respectively. Mean BCVA (logMAR) significantly improved from 0.41 ± 0.31 at baseline to 0.33 ± 0.31 at month 6 (p < 0.001). Mean CMT significantly decreased from 347.67 ± 97.38 μm at baseline to 173.42 ± 30.95 μm at month 6 (p < 0.001). Mean SRF height significantly decreased from 187.85 ± 97.56 µm at baseline to 8.60 ± 31.29 µm after 6 months (p < 0.001). Baseline SRF height was a significant predictive factor for retreatment requirement (p = 0.008). In conclusion, SRT showed favorable anatomical outcomes in patients with chronic CSC. A higher baseline SRF height was a risk factor for retreatment.

Classifying central serous chorioretinopathy subtypes with a deep neural network using optical coherence tomography images: a cross-sectional study

Central serous chorioretinopathy (CSC) is the fourth most common retinopathy and can reduce quality of life. CSC is assessed using optical coherence tomography (OCT), but deep learning systems have not been used to classify CSC subtypes. This study aimed to build a deep learning system model to distinguish CSC subtypes using a convolutional neural network (CNN). We enrolled 435 patients with CSC from a single tertiary center between January 2015 and January 2020. Data from spectral domain OCT (SD-OCT) images of the patients were analyzed using a deep CNN. Five-fold cross-validation was employed to evaluate the model’s ability to discriminate acute, non-resolving, inactive, and chronic atrophic CSC. We compared the performances of the proposed model, Resnet-50, Inception-V3, and eight ophthalmologists. Overall, 3209 SD-OCT images were included. The proposed model showed an average cross-validation accuracy of 70.0% (95% confidence interval [CI], 0.676–0.718) and the highest test accuracy was 73.5%. Additional evaluation in an independent set of 104 patients demonstrated the reliable performance of the proposed model (accuracy: 76.8%). Our model could classify CSC subtypes with high accuracy. Thus, automated deep learning systems could be useful in the classification and management of CSC.