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An algorim for quantification of hemodynamic properties in murine dorsal window chamber video images
Author(s) -
Fontanella Andrew Nicholas,
Palmer Greg,
Schroeder Thies,
Dewhirst Mark W
Publication year - 2011
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.25.1_supplement.lb350
Subject(s) - dorsum , pixel , sliding window protocol , computer science , flow (mathematics) , window (computing) , computer vision , blood flow , intensity (physics) , hemodynamics , dynamics (music) , biological system , artificial intelligence , biomedical engineering , simulation , physics , anatomy , mechanics , acoustics , medicine , optics , cardiology , biology , operating system
We have developed a computational algorithm for the quantification of hemodynamic parameters from video‐rate images of blood flow in a dorsal window chamber model. This method analyses local correlations in pixel intensity fluctuations due to single erythrocyte movement to determine flow rates and direction of movement. The ability to quantify these parameters is of major importance in assessing vascular remodeling in tumor models. Since vascular oxygen/nutrient/drug transport dynamics play a major role in determining tumor progression and response to treatment, the ability to automatically quantify treatment induced effects is an invaluable asset to the dorsal window chamber model. Whereas earlier efforts to quantify flow dynamics relied heavily upon manual vessel identification and sampling of segments of interest, this method provides an entirely automated method by which values for relative velocity and direction of movement can be assigned to every pixel in the field of view. This advancement in analysis will facilitate much more rapid and less biased data generation than currently available image analysis techniques.