Penn Mason McClatchey1, Nicholas A Mignemi1, Zhengang Xu1, Ian M Williams1, Jane E B Reusch2,3,4, Owen P McGuinness1,5, David H Wasserman1,5. 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 (R2 = 0.91, P < 0.0001). Software estimates of capillary hematocrit also generally agreed with by-hand measurements (R2 = 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.
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 (R2 = 0.91, P < 0.0001). Software estimates of capillary hematocrit also generally agreed with by-hand measurements (R2 = 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.
Authors: Baraa K Al-Khazraji; Nicole M Novielli; Daniel Goldman; Philip J Medeiros; Dwayne N Jackson Journal: Microcirculation Date: 2012-05 Impact factor: 2.628
Authors: Bo Ning; Matthew J Kennedy; Adam J Dixon; Naidi Sun; Rui Cao; Brian T Soetikno; Ruimin Chen; Qifa Zhou; K Kirk Shung; John A Hossack; Song Hu Journal: Opt Lett Date: 2015-03-15 Impact factor: 3.776
Authors: P Mason McClatchey; Timothy A Bauer; Judith G Regensteiner; Irene E Schauer; Amy G Huebschmann; Jane E B Reusch Journal: J Diabetes Complications Date: 2017-05-14 Impact factor: 2.852
Authors: Stephen Trzeciak; R Phillip Dellinger; Joseph E Parrillo; Massimiliano Guglielmi; Jasmeet Bajaj; Nicole L Abate; Ryan C Arnold; Susan Colilla; Sergio Zanotti; Steven M Hollenberg Journal: Ann Emerg Med Date: 2006-11-07 Impact factor: 5.721
Authors: Brian J O'Grady; Kylie M Balotin; Allison M Bosworth; P Mason McClatchey; Robert M Weinstein; Mukesh Gupta; Kara S Poole; Leon M Bellan; Ethan S Lippmann Journal: ACS Biomater Sci Eng Date: 2020-09-04
Authors: Nicholas A Mignemi; P Mason McClatchey; Kameron V Kilchrist; Ian M Williams; Bryan A Millis; Kristen E Syring; Craig L Duvall; David H Wasserman; Owen P McGuinness Journal: Am J Physiol Endocrinol Metab Date: 2019-03-12 Impact factor: 4.310
Authors: P Mason McClatchey; Ian M Williams; Zhengang Xu; Nicholas A Mignemi; Curtis C Hughey; Owen P McGuinness; Joshua A Beckman; David H Wasserman Journal: Am J Physiol Endocrinol Metab Date: 2019-09-17 Impact factor: 4.310
Authors: P Mason McClatchey; Ethan S McClain; Ian M Williams; Carlo M Malabanan; Freyja D James; Peter C Lord; Justin M Gregory; David E Cliffel; David H Wasserman Journal: Diabetes Date: 2019-08-09 Impact factor: 9.461