A proof of concept study to evaluate the treatment response of aflibercept in wARMD using OCT-A (Canada study)

Abstract

Purpose To Utilize OCT-A to measure the change in size (mm 2 ) and density (flow index) of choroidal neovascular membranes (CNVMs) from baseline to week 52 of treatment-naïve wet age-related macular degeneration (wARMD) patients receiving intravitreal aflibercept injections (IAI). Methods Patients were treated with IAI at baseline, month 1 and month 2 and then every other month for a total of 12 months. Along with clinical examination and best corrected visual acuity (BCVA), OCT-A 6and 3-mm scans were acquired at every visit between May 2017 and January 2019. Data from baseline, week 12 and week 52 were analyzed prospectively and included in the final analysis.Results Twenty-five eyes from 23 patients were included in the study. The mean BCVA at baseline and week 52 increased from 20/125 to 20/80, respectively (p \ 0.001). The mean CST at baseline and week 52 decreased from 330.48 to 222.40 lm, respectively (p \ 0.001). 1Seventeen patients (18 eyes) completed all protocol-based 6 9 6 mm and 3 9 3 mm OCT-A scans. In this subgroup, 6-mm OCT-A scans revealed that the mean size of the CNVM before and after IAI was 1.21 mm 2 and 0.56 mm 2 , respectively (p \ 0.001), while the 3-mm OCT-A scans at baseline and week 52 demonstrated a decrease in mean size of the CNVM from 0.89 to 0.37 mm 2 , respectively (p \ 0.001). The 6-mm perfusion density map revealed no difference at either time points. Conclusions OCT-A provides a useful approach for monitoring and evaluating the treatment of intravitreal aflibercept for CNVMs. Mean size of CNVMs can be identified by 3-or 6-mm scans, but without machine learning, it requires extensive segmentation. While reproducibility and clear delineation of CNVMs in wARMD using OCT-A is challenging, OCT-A does offer the ability to monitor CNVM size changes during treatment and may offer another biomarker to assist in assessing treatment response.

Utilization of deep learning to quantify fluid volume of neovascular age-related macular degeneration patients based on swept-source OCT imaging: The ONTARIO study

“…Analysis, as part of this study, began in July 2020 and ended in December 2020. The selection of participants for the CANADA study has been previously reported [ 10 ]. Twenty-three patients (25 eyes) completed the CANADA study and were enrolled into this study.…”

“…As part of the CANADA study, all patients underwent SS-OCT-A testing using the Topcon Triton Swept Source OCT (Tokyo, Japan) to identify CST and lesion size at baseline [ 10 ]. The SS-OCT-A system has a scanning speed of 100,000 A-scans per second and utilizes a wavelength-sweeping laser, with a central wavelength of 1,050 nm wavelength and a sweeping range of approximately 100 nm [ 15 ].…”

“…This performs layer segmentation as a pre-processing step to fluid segmentation that uses a deep learning-based algorithm. Performance of the fluid segmentation has previously been validated relative to two expert graders (SS and JO) [ 10 ].…”

“…Optical coherence tomography angiography (OCT-A) has revealed further retinal anatomical and vascular structures to track nARMD progression [ 9 ]. Our 2021 proof of concept CANADA trial demonstrated significantly improved choroidal neovascularization membrane (CNVM) size identification for nARMD treatment monitoring through OCT-A [ 10 ]. However, fluid volume metrics and delineation of unique fluid characterization required extensive manual segmentation and demonstrated poor acquisition of real-time values [ 10 ].…”

“…Our 2021 proof of concept CANADA trial demonstrated significantly improved choroidal neovascularization membrane (CNVM) size identification for nARMD treatment monitoring through OCT-A [ 10 ]. However, fluid volume metrics and delineation of unique fluid characterization required extensive manual segmentation and demonstrated poor acquisition of real-time values [ 10 ]. It was hypothesized that artificial intelligence (AI) would improve image segmentation, ultimately providing better personalized therapy.…”