Quantitative Mapping of Hemodynamics in the Lung, Brain, and Dorsal Window Chamber-Grown Tumors Using a Novel, Automated Algorithm

Andrew N. Fontanella, Thies Schroeder, Daryl W. Hochman, Raymond E. Chen, Gabi Hanna, Michael M. Haglund, Timothy W Secomb, Gregory M. Palmer, Mark W. Dewhirst

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Objective: Hemodynamic properties of vascular beds are of great interest in a variety of clinical and laboratory settings. However, there presently exists no automated, accurate, technically simple method for generating blood velocity maps of complex microvessel networks. Methods: Here, we present a novel algorithm that addresses the problem of acquiring quantitative maps by applying pixel-by-pixel cross-correlation to video data. Temporal signals at every spatial coordinate are compared with signals at neighboring points, generating a series of correlation maps from which speed and direction are calculated. User-assisted definition of vessel geometries is not required, and sequential data are analyzed automatically, without user bias. Results: Velocity measurements were validated against the dual-slit method and against in vitro capillary flow with known velocities. The algorithm was tested in three different biological models in order to demonstrate its versatility. Conclusions: The hemodynamic maps presented here demonstrate an accurate, quantitative method of analyzing dynamic vascular systems.

Original languageEnglish (US)
Pages (from-to)724-735
Number of pages12
JournalMicrocirculation
Volume20
Issue number8
DOIs
StatePublished - Nov 2013

Fingerprint

Hemodynamics
Lung
Brain
Blood Vessels
Neoplasms
Biological Models
Microvessels

Keywords

  • Blood flow
  • Computational
  • Image processing
  • Tumor microcirculation

ASJC Scopus subject areas

  • Physiology
  • Physiology (medical)
  • Molecular Biology
  • Cardiology and Cardiovascular Medicine

Cite this

Fontanella, A. N., Schroeder, T., Hochman, D. W., Chen, R. E., Hanna, G., Haglund, M. M., ... Dewhirst, M. W. (2013). Quantitative Mapping of Hemodynamics in the Lung, Brain, and Dorsal Window Chamber-Grown Tumors Using a Novel, Automated Algorithm. Microcirculation, 20(8), 724-735. https://doi.org/10.1111/micc.12072

Quantitative Mapping of Hemodynamics in the Lung, Brain, and Dorsal Window Chamber-Grown Tumors Using a Novel, Automated Algorithm. / Fontanella, Andrew N.; Schroeder, Thies; Hochman, Daryl W.; Chen, Raymond E.; Hanna, Gabi; Haglund, Michael M.; Secomb, Timothy W; Palmer, Gregory M.; Dewhirst, Mark W.

In: Microcirculation, Vol. 20, No. 8, 11.2013, p. 724-735.

Research output: Contribution to journalArticle

Fontanella, AN, Schroeder, T, Hochman, DW, Chen, RE, Hanna, G, Haglund, MM, Secomb, TW, Palmer, GM & Dewhirst, MW 2013, 'Quantitative Mapping of Hemodynamics in the Lung, Brain, and Dorsal Window Chamber-Grown Tumors Using a Novel, Automated Algorithm', Microcirculation, vol. 20, no. 8, pp. 724-735. https://doi.org/10.1111/micc.12072
Fontanella, Andrew N. ; Schroeder, Thies ; Hochman, Daryl W. ; Chen, Raymond E. ; Hanna, Gabi ; Haglund, Michael M. ; Secomb, Timothy W ; Palmer, Gregory M. ; Dewhirst, Mark W. / Quantitative Mapping of Hemodynamics in the Lung, Brain, and Dorsal Window Chamber-Grown Tumors Using a Novel, Automated Algorithm. In: Microcirculation. 2013 ; Vol. 20, No. 8. pp. 724-735.
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