Three-dimensional spatiotemporal analysis for the assessment of retinal capillary perfusion using a clinical OCT system

Growing evidence suggests that subtle changes in retinal microcirculation may precede structural damage in vision-threatening diseases. Among these, perfusion heterogeneity within the retinal capillary network has emerged as a promising biomarker for early detection and disease monitoring. Recent advances in optical coherence tomography (OCT) and OCT-based angiography (OCTA) have enabled high-resolution, three-dimensional imaging of retinal morphology and vasculature. However, commercial systems remain limited in their ability to accurately analyze retinal perfusion dynamics due to reliance on proprietary and undisclosed post-processing algorithms. This paper introduces an effective protocol for spatial and temporal analysis of capillary perfusion heterogeneity using unprocessed OCTA volume data acquired by a commercial retinal imaging system. The proposed method employs a novel analysis utilizing the depth-resolved pixel-wise coefficient of variation (CoV) to quantitatively estimate retinal capillary perfusion heterogeneity. Comparison between the proposed method and conventional CoV analysis emphasizes the reliability of the new approach, incorporating depth-dependent signals. By using unprocessed OCTA data, the proposed method can provide more accurate measurements of retinal perfusion heterogeneity. Furthermore, the image processing techniques developed in this study could serve as a foundation for future research in other retinal vascular disorders.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-10-22
DOI
https://doi.org/10.1038/s41598-025-20659-6
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Three-dimensional spatiotemporal analysis for the assessment of retinal capillary perfusion using a clinical OCT system

Hoyoung Jung, Valerie Mok, Myeong Jin Ju, Zaid Mammo et al.
Scientific Reports
Retinal Imaging and Analysis
article

Three-dimensional spatiotemporal analysis for the assessment of retinal capillary perfusion using a clinical OCT system

Hoyoung Jung, Valerie Mok, Myeong Jin Ju, Zaid Mammo, Yudan Chen, Jun Song, Tiffany Tse, J. S. Tsang
article en

Abstract

Growing evidence suggests that subtle changes in retinal microcirculation may precede structural damage in vision-threatening diseases. Among these, perfusion heterogeneity within the retinal capillary network has emerged as a promising biomarker for early detection and disease monitoring. Recent advances in optical coherence tomography (OCT) and OCT-based angiography (OCTA) have enabled high-resolution, three-dimensional imaging of retinal morphology and vasculature. However, commercial systems remain limited in their ability to accurately analyze retinal perfusion dynamics due to reliance on proprietary and undisclosed post-processing algorithms. This paper introduces an effective protocol for spatial and temporal analysis of capillary perfusion heterogeneity using unprocessed OCTA volume data acquired by a commercial retinal imaging system. The proposed method employs a novel analysis utilizing the depth-resolved pixel-wise coefficient of variation (CoV) to quantitatively estimate retinal capillary perfusion heterogeneity. Comparison between the proposed method and conventional CoV analysis emphasizes the reliability of the new approach, incorporating depth-dependent signals. By using unprocessed OCTA data, the proposed method can provide more accurate measurements of retinal perfusion heterogeneity. Furthermore, the image processing techniques developed in this study could serve as a foundation for future research in other retinal vascular disorders.

Scientific ReportsVol. 15(1)
University of British Columbia (CA)
Alzheimer Society, Alzheimer Society Research Program, Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 56%
Retinal Imaging and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.