Konnor P McDowell1, Andrée-Anne Berthiaume1,2, Taryn Tieu1, David A Hartmann3, Andy Y Shih1,4,5. 1. Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, Seattle, WA, USA. 2. Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA. 3. Department of Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA. 4. Department of Pediatrics, University of Washington, Seattle, WA, USA. 5. Department of Bioengineering, University of Washington, Seattle, WA, USA.
Abstract
BACKGROUND: Multi-photon imaging of the cerebrovasculature provides rich data on the dynamics of cortical arterioles, capillaries, and venules. Vascular diameter is the major determinant of blood flow resistance, and is the most commonly quantified metric in studies of the cerebrovasculature. However, there is a lack of accessible and easy-to-use methods to quantify vascular diameter in imaging data. METHODS: We created VasoMetrics, a macro written in ImageJ/Fiji for spatiotemporal analysis of microvascular diameter. The key feature of VasoMetrics is rapid analysis of many evenly spaced cross-sectional lines along the vessel of interest, permitting the extraction of numerous diameter measurements from individual vessels. Here we demonstrated the utility of VasoMetrics by analyzing in vivo multi-photon imaging stacks and movies collected from lightly sedated mice, as well as data from optical coherence tomography angiography (OCTA) of human retina. RESULTS: Compared to the standard approach, which is to measure cross-sectional diameters at arbitrary points along a vessel, VasoMetrics accurately reported spatiotemporal features of vessel diameter, reduced measurement bias and time spent analyzing data, and improved the reproducibility of diameter measurements between users. VasoMetrics revealed the dynamics in pial arteriole diameters during vasomotion at rest, as well as changes in capillary diameter before and after pericyte ablation. Retinal arteriole diameter was quantified from a human retinal angiogram, providing proof-of-principle that VasoMetrics can be applied to contrast-enhanced clinical imaging of microvasculature. CONCLUSIONS: VasoMetrics is a robust macro for spatiotemporal analysis of microvascular diameter in imaging applications. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
BACKGROUND: Multi-photon imaging of the cerebrovasculature provides rich data on the dynamics of cortical arterioles, capillaries, and venules. Vascular diameter is the major determinant of blood flow resistance, and is the most commonly quantified metric in studies of the cerebrovasculature. However, there is a lack of accessible and easy-to-use methods to quantify vascular diameter in imaging data. METHODS: We created VasoMetrics, a macro written in ImageJ/Fiji for spatiotemporal analysis of microvascular diameter. The key feature of VasoMetrics is rapid analysis of many evenly spaced cross-sectional lines along the vessel of interest, permitting the extraction of numerous diameter measurements from individual vessels. Here we demonstrated the utility of VasoMetrics by analyzing in vivo multi-photon imaging stacks and movies collected from lightly sedated mice, as well as data from optical coherence tomography angiography (OCTA) of human retina. RESULTS: Compared to the standard approach, which is to measure cross-sectional diameters at arbitrary points along a vessel, VasoMetrics accurately reported spatiotemporal features of vessel diameter, reduced measurement bias and time spent analyzing data, and improved the reproducibility of diameter measurements between users. VasoMetrics revealed the dynamics in pial arteriole diameters during vasomotion at rest, as well as changes in capillary diameter before and after pericyte ablation. Retinal arteriole diameter was quantified from a human retinal angiogram, providing proof-of-principle that VasoMetrics can be applied to contrast-enhanced clinical imaging of microvasculature. CONCLUSIONS: VasoMetrics is a robust macro for spatiotemporal analysis of microvascular diameter in imaging applications. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
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