{"doi":"10.1364/boe.427819","title":"Analysis of correlations between local geographic atrophy growth rates and local OCT angiography-measured choriocapillaris flow deficits","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.","journal":"Biomedical Optics Express","year":2021,"id":171874,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":26,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9416,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":497246,"name":"Yingying Shi","orcid":"0000-0001-8184-0834","position":1,"is_corresponding":false},{"id":406321,"name":"Qinqin Zhang","orcid":"0000-0003-3629-1914","position":2,"is_corresponding":false},{"id":707273,"name":"Liang Wang","orcid":"0000-0001-8672-0030","position":3,"is_corresponding":false},{"id":708070,"name":"Rahul Mazumder","orcid":null,"position":4,"is_corresponding":false},{"id":334933,"name":"Siyu Chen","orcid":"0000-0002-6701-3397","position":5,"is_corresponding":false},{"id":382739,"name":"Zhongdi Chu","orcid":"0000-0001-7430-5032","position":6,"is_corresponding":false},{"id":381071,"name":"William J. Feuer","orcid":"0000-0002-9442-3076","position":7,"is_corresponding":false},{"id":326978,"name":"Nadia K. Waheed","orcid":"0000-0002-8229-7519","position":8,"is_corresponding":false},{"id":304780,"name":"Giovanni Gregori","orcid":"0000-0003-0951-2216","position":9,"is_corresponding":false},{"id":284472,"name":"Ruikang K. Wang","orcid":"0000-0001-5169-8822","position":10,"is_corresponding":false},{"id":304779,"name":"Philip J. Rosenfeld","orcid":"0000-0002-4068-6671","position":11,"is_corresponding":false},{"id":85587,"name":"James G. Fujimoto","orcid":"0000-0002-0828-4357","position":12,"is_corresponding":false},{"id":327875,"name":"Eric M. Moult","orcid":null,"position":0,"is_corresponding":true}],"reference_count":57,"raw_metadata":null,"created_at":"2026-07-18T23:46:37.150824Z","pmid":"34457433","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}