Original Article
Quantifying choriocapillaris flow deficits using global and localized thresholding methods: a correlation study
Abstract
Background: To investigate the correlation and agreement of two previously published choriocapillaris (CC) quantification methods using a normal database with swept-source optical coherence tomography angiography (SS-OCTA).
Methods: Normal adult subjects from all age groups imaged by SS-OCTA were used in this study. Each subject was imaged with 3 mm × 3 mm and 6 mm × 6 mm scan patterns centered on fovea, upon which en face CC images were generated by segmenting volumetric OCTA data. After signal compensation and removal of projection artifacts and noise, CC images were analyzed to identify flow deficits (FD) using two published methods. The first method utilized standard deviation from a young normal database (SD method) as the global thresholding while the second method utilized fuzzy C-means algorithm (FCM method) with local thresholding. Both methods segmented FDs from CC images and quantified FD density (FDD) and mean FD size (MFDS). In each 3 mm × 3 mm scan, three regions were quantified: a 1 mm circle (C1), a 1.5 mm rim (R1.5) and a 2.5 mm circle (C2.5). In each 6 mm × 6 mm scan, five regions were quantified: C1, R1.5, C2.5, a 2.5 mm rim (R2.5) and a 5 mm circle (C5). Spearman correlation and Bland-Altman plot analyses were conducted to compare the two methods.
Results: Data obtained from 164 normal subjects (age: 56±19, 59% females) were used in this study. Strong correlations were observed between the two methods in all comparisons (r: 0.78–0.94, all P<0.0001). Overall MFDS provided higher or comparable correlation coefficients (r) compared to FDD. We have also observed stronger correlations in the central macula compared to parafoveal and perifoveal regions for both FDD and MFDS. In regions of C1, R1.5 and C2.5, 6 mm × 6 mm scans resulted in better agreement (smaller mean bias, similar or tighter limit of agreement) between the two methods for both FDD and MFDS compared to 3 mm × 3 mm scans.
Conclusions: There are strong correlations and satisfactory agreement between SD method and FCM method. SD method requires the reference to a normal database for CC quantification while FCM does not. Both methods could be used for the analysis of CC FDs in clinical settings depending on specific study designs such as the availability of a normal database.
Methods: Normal adult subjects from all age groups imaged by SS-OCTA were used in this study. Each subject was imaged with 3 mm × 3 mm and 6 mm × 6 mm scan patterns centered on fovea, upon which en face CC images were generated by segmenting volumetric OCTA data. After signal compensation and removal of projection artifacts and noise, CC images were analyzed to identify flow deficits (FD) using two published methods. The first method utilized standard deviation from a young normal database (SD method) as the global thresholding while the second method utilized fuzzy C-means algorithm (FCM method) with local thresholding. Both methods segmented FDs from CC images and quantified FD density (FDD) and mean FD size (MFDS). In each 3 mm × 3 mm scan, three regions were quantified: a 1 mm circle (C1), a 1.5 mm rim (R1.5) and a 2.5 mm circle (C2.5). In each 6 mm × 6 mm scan, five regions were quantified: C1, R1.5, C2.5, a 2.5 mm rim (R2.5) and a 5 mm circle (C5). Spearman correlation and Bland-Altman plot analyses were conducted to compare the two methods.
Results: Data obtained from 164 normal subjects (age: 56±19, 59% females) were used in this study. Strong correlations were observed between the two methods in all comparisons (r: 0.78–0.94, all P<0.0001). Overall MFDS provided higher or comparable correlation coefficients (r) compared to FDD. We have also observed stronger correlations in the central macula compared to parafoveal and perifoveal regions for both FDD and MFDS. In regions of C1, R1.5 and C2.5, 6 mm × 6 mm scans resulted in better agreement (smaller mean bias, similar or tighter limit of agreement) between the two methods for both FDD and MFDS compared to 3 mm × 3 mm scans.
Conclusions: There are strong correlations and satisfactory agreement between SD method and FCM method. SD method requires the reference to a normal database for CC quantification while FCM does not. Both methods could be used for the analysis of CC FDs in clinical settings depending on specific study designs such as the availability of a normal database.
