Analysis of correlations between local geographic atrophy growth rates and local OCT angiography-measured choriocapillaris flow deficits
Name
boe-12-7-4573.pdf
Description
Published version
Size
7.84 MB
Format
Adobe PDF
Checksum (MD5)
4f1595a1e3388d714aa447ae872c244f
Author(s)
Moult, Eric M
Shi, Yingying
Zhang, Qinqin
Wang, Liang
Mazumder, Rahul
Chen, Siyu
Chu, Zhongdi
Feuer, William
Waheed, Nadia K
Gregori, Giovanni
Date Issued
2021
Journal
Biomedical Optics Express
Publisher
The Optical Society
Citation
Moult, Eric M, Shi, Yingying, Zhang, Qinqin, Wang, Liang, Mazumder, Rahul et al. 2021. "Analysis of correlations between local geographic atrophy growth rates and local OCT angiography-measured choriocapillaris flow deficits." Biomedical Optics Express, 12 (7).
Version
Final published version
Abstract
The purpose of this study is to quantitatively assess correlations between local geographic atrophy (GA) growth rates and local optical coherence tomography angiography (OCTA)-measured choriocapillaris (CC) flow deficits. Thirty-eight eyes from 27 patients with GA secondary to age-related macular degeneration (AMD) were imaged with a commercial 1050 nm swept-source OCTA instrument at 3 visits, each separated by ∼6 months. Pearson correlations were computed between local GA growth rates, estimated using a biophysical GA growth model, and local OCTA CC flow deficit percentages measured along the GA margins of the baseline visits. The p-values associated with the null hypothesis of no Pearson correlation were estimated using a Monte Carlo permutation scheme that incorporates the effects of spatial autocorrelation. The null hypothesis (Pearson's ρ = 0) was rejected at a Benjamini-Hochberg false discovery rate of 0.2 in 15 of the 114 visit pairs, 11 of which exhibited positive correlations; even amongst these 11 visit pairs, correlations were modest (r in [0.30, 0.53]). The presented framework appears well suited to evaluating other potential imaging biomarkers of local GA growth rates.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
Harvard University--MIT Division of Health Sciences and Technology
Sloan School of Management
Massachusetts Institute of Technology. Operations Research Center
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
10.1364/BOE.427819
