Direct assessment of capillary perfusion has been prioritized in hemodynamic management of critically ill patients in addition to optimizing blood flow on the global scale. Sublingual handheld vital microscopy has enabled online acquisition of moving image sequences of the microcirculation, including the flow of individual red blood cells in the capillary network. However, due to inherent content complexity, manual image sequence analysis remained gold standard, introducing inter-observer variability and precluding real-time image analysis for clinical therapy guidance. Here we introduce an advanced computer vision algorithm for instantaneous analysis and quantification of morphometric and kinetic information related to capillary blood flow in the sublingual microcirculation. We evaluated this technique in a porcine model of septic shock and resuscitation and cardiac surgery patients. This development is of high clinical relevance because it enables implementation of point-of-care goal-directed resuscitation procedures based on correction of microcirculatory perfusion in critically ill and perioperative patients.

Additional Metadata
Persistent URL dx.doi.org/10.1038/s42003-019-0473-8, hdl.handle.net/1765/117760
Journal Communications Biology
Citation
Hilty, M.P., Guerci, P, Ince, Y., Toraman, F., & Ince, C. (2019). MicroTools enables automated quantification of capillary density and red blood cell velocity in handheld vital microscopy. Communications Biology, 2. doi:10.1038/s42003-019-0473-8