Purpose: To characterize macular blood flow connectivity in vivo using high-resolution perifoveal High Res OCT raster scans were performed on healthy participants. To mitigate the limitations of projection-resolved OCT-angiography, flow and structural data were used to observe the vascular structures of the superficial vascular complex (SVC) and the deep vascular complex. Vascular segmentation and rendering were performed using Imaris 9.5 software. Inflow and outflow patterns were classified according to vascular diameter and branching order from superficial arteries and veins, respectively. Results: Eight eyes from eight participants were included in this analysis, from which 422 inflow and 459 outflow connections were characterized. Arteries had direct arteriolar connections to the SVC (78%) and to the intermediate capillary plexus (ICP, 22%). Deep capillary plexus (DCP) inflow derived from small-diameter vessels succeeding ICP arterioles. The most prevalent outflow pathways coursed through superficial draining venules (74%). DCP draining venules ordinarily merged with ICP draining venules and drained independently of superficial venules in 21% of cases. The morphology of DCP draining venules in structural HighRes OCT is distinct from other vessels crossing the inner nuclear layer and can be used to identify superficial veins. Conclusions: Vascular connectivity analysis supports a hybrid circuitry of blood flow within the human parafoveal macula. Translational Relevance: Characterization of parafoveal macular blood flow connectivity in vivo using a precise segmentation of HighRes OCT is consistent with ground-truth microscopy studies and shows a hybrid circuitry. © 2022 The Authors.

Cabral, D., Fradinho, A.C., Pereira, T., Ramakrishnan, M.S., Bacci, T., An, D., et al. (2022). Macular Vascular Imaging and Connectivity Analysis Using High-Resolution Optical Coherence Tomography. TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 11(6), 1-11 [10.1167/tvst.11.6.2].

Macular Vascular Imaging and Connectivity Analysis Using High-Resolution Optical Coherence Tomography

Bacci T.;
2022-01-01

Abstract

Purpose: To characterize macular blood flow connectivity in vivo using high-resolution perifoveal High Res OCT raster scans were performed on healthy participants. To mitigate the limitations of projection-resolved OCT-angiography, flow and structural data were used to observe the vascular structures of the superficial vascular complex (SVC) and the deep vascular complex. Vascular segmentation and rendering were performed using Imaris 9.5 software. Inflow and outflow patterns were classified according to vascular diameter and branching order from superficial arteries and veins, respectively. Results: Eight eyes from eight participants were included in this analysis, from which 422 inflow and 459 outflow connections were characterized. Arteries had direct arteriolar connections to the SVC (78%) and to the intermediate capillary plexus (ICP, 22%). Deep capillary plexus (DCP) inflow derived from small-diameter vessels succeeding ICP arterioles. The most prevalent outflow pathways coursed through superficial draining venules (74%). DCP draining venules ordinarily merged with ICP draining venules and drained independently of superficial venules in 21% of cases. The morphology of DCP draining venules in structural HighRes OCT is distinct from other vessels crossing the inner nuclear layer and can be used to identify superficial veins. Conclusions: Vascular connectivity analysis supports a hybrid circuitry of blood flow within the human parafoveal macula. Translational Relevance: Characterization of parafoveal macular blood flow connectivity in vivo using a precise segmentation of HighRes OCT is consistent with ground-truth microscopy studies and shows a hybrid circuitry. © 2022 The Authors.
2022
Cabral, D., Fradinho, A.C., Pereira, T., Ramakrishnan, M.S., Bacci, T., An, D., et al. (2022). Macular Vascular Imaging and Connectivity Analysis Using High-Resolution Optical Coherence Tomography. TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 11(6), 1-11 [10.1167/tvst.11.6.2].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1223674