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Microcirculation. 2018 Jun 16:e12482. doi: 10.1111/micc.12482. [Epub ahead of print]

Automated quantification of microvascular perfusion.

Author information

1
Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee.
2
Division of Endocrinology, University of Colorado Medical School, Aurora, Colorado.
3
Department of Bioengineering, University of Colorado Denver, Denver, Colorado.
4
Department of Veterans Affairs, Aurora, Colorado.
5
Mouse Metabolic Phenotyping Center, Nashville, Tennessee.

Abstract

OBJECTIVE:

Changes in microvascular perfusion have been reported in many diseases, yet the functional significance of altered perfusion is often difficult to determine. This is partly because commonly used techniques for perfusion measurement often rely on either indirect or by-hand approaches.

METHODS:

We developed and validated a fully automated software technique to measure microvascular perfusion in videos acquired by fluorescence microscopy in the mouse gastrocnemius. Acute perfusion responses were recorded following intravenous injections with phenylephrine, SNP, or saline.

RESULTS:

Software-measured capillary flow velocity closely correlated with by-hand measured flow velocity (R = 0.91, P < 0.0001). Software estimates of capillary hematocrit also generally agreed with by-hand measurements (R = 0.64, P < 0.0001). Detection limits range from 0 to 2000 μm/s, as compared to an average flow velocity of 326 ± 102 μm/s (mean ± SD) at rest. SNP injection transiently increased capillary flow velocity and hematocrit and made capillary perfusion more steady and homogenous. Phenylephrine injection had the opposite effect in all metrics. Saline injection transiently decreased capillary flow velocity and hematocrit without influencing flow distribution or stability. All perfusion metrics were temporally stable without intervention.

CONCLUSIONS:

These results demonstrate a novel and sensitive technique for reproducible, user-independent quantification of microvascular perfusion.

KEYWORDS:

capillary recruitment; computational image processing; intravital microscopy; microvascular perfusion; nitric oxide

PMID:
29908041
DOI:
10.1111/micc.12482

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