Three-dimensional choroidal contour mapping in healthy population.

Purpose was to study 3-dimensional choroidal contour at choroidal inner boundary (CIB) and choroidal outer boundary (COB) in healthy eyes. Healthy eyes imaged on wide field swept-source optical coherence tomography were included. Delineation of CIB and COB was done based on our previously reported methods. Quantitative analysis of the surfaces of CIB and COB was based on analyzing best fit spherical radius (R) (overall and sectoral). One hundred and seven eyes of 74 subjects with a mean age of 46.4 ± 19.3 years were evaluated. Overall, R COB (mean ± SD: 22.5 ± 4.8 mm) < R CIB (32.4 ± 9.4 mm). Central sector had the least R at COB (7.2 ± 5.9 mm) as well as CIB (25.1 ± 14.3 mm) across all age groups. Regression analysis between R (CIB) and age (r = -0.31, r2 = 0.09) showed negative correlation (P < 0.001) and that between R (COB) and age was positive (r = 0.26, r2 = 0.07) (P = 0.01). To conclude, central sector is the steepest sector in comparison to all the other sectors. This is indicative of a prolate shape of choroidal contour at CIB and COB. Outer boundary of choroid is steeper than inner boundary across all age groups. However, with ageing, outer boundary becomes flatter and inner boundary becomes steeper.

Longitudinal changes in pigment epithelial detachment composition indices (PEDCI): new biomarkers in neovascular age-related macular degeneration.

PURPOSE: To evaluate novel, automated biomarkers, pigment epithelial detachment composition indices (PEDCI) in eyes with neovascular age-related macular degeneration (nAMD) undergoing anti-vascular endothelial growth factor (anti-VEGF) therapy through 24 months. METHODS: Retrospective analysis of 37 eyes (34 patients) with PED associated with nAMD receiving as-needed anti-VEGF treatment was performed. Best-corrected visual acuity (BCVA) and optical coherence tomography images were acquired at a treatment-naïve baseline and 3-, 6-, 12-, 18-, and 24-month visits. Previously validated automated imaging biomarkers, PEDCI-S (serous), PEDCI-N (neovascular), and PEDCI-F (fibrous) within PEDs were measured. ANOVA analysis and Spearman correlation were performed. RESULTS: Mean BCVA (in logMAR) was 0.60 ± 0.47, 0.45 ± 0.41, 0.49 ± 0.49, 0.61 ± 0.54, 0.59 ± 0.56, and 0.67 ± 0.57 at baseline, 3, 6, 12, 18, and 24 months respectively. Overall, BCVA showed minimal worsening of 0.07 ± 0.54 logMAR (p = 0.07). 13.38 ± 3.77 anti-VEGF injections were given through 24 months. PEDCI-F showed an increase of 0.116, 0.122, 0.036, and 0.006 at months 3, 6, 12, and 18 respectively and a decrease of 0.004 at month 24 (p = 0.03); PEDCI-S showed a decrease of 0.064, 0.130, 0.091, 0.092, and 0.095 at months 3, 6, 12, 18, and 24 respectively (p = 0.16); PEDCI-N showed a decrease of 0.052 at month 3 and an increase of 0.008, 0.055, 0.086, and 0.099 at months 6, 12, 18, and 24 respectively (p = 0.06). BCVA was negatively correlated with PEDCI-F (r = -0.28, p < 0.01), and positively correlated with PEDCI-N (r = 0.28, p < 0.01) and PEDCI-S (r = 0.15, p = 0.03). CONCLUSION: Longitudinal analysis of PEDCI supports their utility as biomarkers that characterize treatment related effects by quantifying the relative composition of PEDs.

Radiomics-Based Prediction of Anti-VEGF Treatment Response in Neovascular Age-Related Macular Degeneration With Pigment Epithelial Detachment.

Purpose: Machine learning models based on radiomic feature extraction from clinical imaging data provide effective and interpretable means for clinical decision making. This pilot study evaluated whether radiomics features in baseline optical coherence tomography (OCT) images of eyes with pigment epithelial detachment (PED) associated with neovascular age-related macular degeneration (nAMD) can predict treatment response to as-needed anti-vascular endothelial growth factor (VEGF) therapy. Methods: Thirty-nine eyes of patients with PED undergoing anti-VEGF therapy were included. All eyes underwent a loading dose followed by as-needed therapy. OCT images at baseline, month 3, and month 6 were analyzed. Images were manually separated into non-responding, recurring, and responding eyes based on the presence or absence of subretinal fluid at month 6. PED radiomics features were then extracted from each image and images were classified as responding or recurring using a machine learning classifier applied to the radiomics features. Results: Linear discriminant analysis classification of baseline features as responsive versus recurring resulted in classification performance of 64.0% (95% confidence interval [CI] = 0.63-0.65), area under the curve (AUC = 0.78, 95% CI = 0.72-0.82), sensitivity 0.79 (95% CI = 0.63-0.87), and specificity 0.58 (95% CI = 0.50-0.67). Further analysis of features in recurring eyes identified a significant shift toward non-responding mean feature values over 6 months. Conclusions: Our results demonstrate the use of radiomics features as predictors for treatment response to as-needed anti-VEGF therapy. Our study demonstrates the potential for radiomics feature in clinical decision support for personalizing anti-VEGF therapy. Translational Relevance: The ability to use PED texture features to predict treatment response facilitates personalized clinical decision making.