Liver Microcirculation Analysis by Red Blood Cell Motion Modeling in Intravital Microscopy Images

• Published in: IEEE transactions on biomedical engineering Vol. 55; no. 1; pp. 162 - 170
• Main Authors: Kamoun, Walid S., Schmugge, Stephen J., Kraftchick, Jerrod P., Clemens, Mark G., Shin, Min C.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2008; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Animals; Blood flow; Cell Movement - physiology; Circulatory system; Erythrocytes - cytology; Erythrocytes - physiology; Flow Cytometry - methods; Fluorescence; Image analysis; Image Interpretation, Computer-Assisted - methods; Image motion analysis; intravital microscopy; Leukocytes; Liver; Liver Circulation - physiology; Microcirculation - cytology; Microcirculation - physiology; Microscopy; Microscopy, Fluorescence - methods; Motion analysis; Protocols; Rats; Red blood cells; red blood cells (RBCs); template matching; Tracking; Visualization
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2007.910670

Intravital microscopy has been used to visualize the microcirculation by imaging fluorescent labeled red blood cells (RBCs). Traditionally, microcirculation has been modeled by computing the mean velocity of a few, randomly selected, manually tracked RBCs. However, this protocol is tedious, time consuming, and subjective with technician related bias. We present a new method for analyzing the microcirculation by modeling the RBC motion through automatic tracking. The tracking of RBCs is challenging as in each image, as many as 200 cells move through a complex network of vessels at a wide range of speeds while deforming in shape. To reliably detect RBCs traveling at a wide range of speeds, a window of temporal template matching is applied. Then, cells appearing in successive frames are corresponded based on the motion behavior constraints in terms of the direction, magnitude, and path. The performance evaluation against a ground truth indicates the detection accuracy up to 84% TP at 6% FP and a correspondence accuracy of 89%. We include an in-depth discussion on comparison of the microcirculation based on motion modeling from the proposed automated method against a mean velocity from manual analysis protocol in terms of precision, objectivity, and sensitivity.