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Updated: Apr 23, 2026

Evaluation of Capillary and Other Vessel Contribution to Macular Perfusion Density Measured with Optical Coherence Tomography Angiography
Published on: February 18, 2022
Macular, Peripapillary, and Midperipheral Nonperfusion in Diabetic Subjects: A Wide-Field OCTA Quantification
Luisa Frizziero1, Giulia Midena2, Luca Danieli1
1Department of Ophthalmology, University of Padova, Padova, Italy.
Purpose:
To identify and quantify the correlation between geometric perfusion deficit (GPD), a direct optical coherence tomography angiography (OCTA) metric of nonperfusion, in the macular, peripapillary, and midperipheral retina in diabetic patients, using widefield swept-source OCTA.
Methods:
Diabetic patients, with and without diabetic retinopathy (DR), underwent widefield swept-source OCTA imaging of the macula, peripapillary area, and four midperipheral retinal regions. GPD was calculated for each area, in macula both excluding (GPD) and including (GPDf) the foveal avascular zone. Correlations of GPD between regions were assessed.
Results:
We analyzed 197 diabetic eyes. A moderate-to-strong positive correlation was observed between macular and midperipheral GPD in both the superficial capillary plexus (SCP) and deep capillary plexus (DCP). The radial peripapillary capillary plexus (RPCP) also showed moderate correlations with midperipheral SCP and DCP. Subgroup analysis revealed that in both DR and no DR eyes, macular and midperipheral GPD and GPDf in SCP and DCP were significantly correlated. RPCP showed significant correlation with midperipheral DCP in DR eyes and with SCP in both groups.
Conclusions:
In diabetic patients, GPD in the macular SCP and DCP, as well as in the RPCP, correlates positively with perfusion deficits in the midperiphery.
Translational Relevance:
Optical coherence tomography angiography-based assessment of macular and peripapillary perfusion deficits enables noninvasive monitoring and may facilitate the early detection of peripheral vascular alterations in diabetic retinopathy, thus optimizing the diagnostic workflow for diabetic patients.
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