• Critical care medicine · Oct 2020

    Automated Algorithm Analysis of Sublingual Microcirculation in an International Multicentral Database Identifies Alterations Associated With Disease and Mechanism of Resuscitation.

    • Matthias Peter Hilty, Sakir Akin, Christiaan Boerma, Abele Donati, Özge Erdem, Paolo Giaccaglia, Philippe Guerci, Dan Mj Milstein, Jonathan Montomoli, Fevzi Toraman, Zuhre Uz, Gerke Veenstra, and Can Ince.
    • Department of Intensive Care, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
    • Crit. Care Med. 2020 Oct 1; 48 (10): e864-e875.

    ObjectivesReliable automated handheld vital microscopy image sequence analysis and the identification of disease states and effects of therapy are prerequisites for the routine use of quantitative sublingual microcirculation measurements at the point-of-care. The present study aimed to clinically validate the recently introduced MicroTools software in a large multicentral database of perioperative and critically ill patients and to use this automatic algorithm to data-mine and identify the sublingual microcirculatory variable changes in response to disease and therapy.DesignRetrospective algorithm-based image analysis and data-mining within a large international database of sublingual capillary microscopy. Algorithm-based analysis was compared with manual analysis for validation. Thereafter, MicroTools was used to identify the functional microcirculatory alterations associated with disease conditions and identify therapeutic options for recruiting functional microcirculatory variables.SettingTen perioperative/ICU/volunteer studies in six international teaching hospitals.PatientsThe database encompass 267 adult and pediatric patients undergoing surgery, treatment for sepsis, and heart failure in the ICU and healthy volunteers.InterventionsPerioperative and ICU standard of care.Measurements And Main ResultsOne thousand five hundred twenty-five handheld vital microscopy image sequences containing 149,257 microscopy images were analyzed. 3.89 × 10 RBC positions were tracked by the algorithm in real time, and offline manual analysis was performed. Good correlation and trending ability were found between manual and automatic total and functional capillary density (r = 0.6-0.8; p < 0.0001). RBC tracking within the database demonstrated changes in functional capillary density and/or RBC velocity in septic shock, heart failure, hypovolemia, obstructive shock, and hemodilution and thus detected the presence of a disease condition. Therapies recruiting the microcirculatory diffusion and convection capacity associated with systemic vasodilation and an increase in cardiac output were separately identified.ConclusionsAlgorithm-based analysis of the sublingual microcirculation closely matched manual analysis across a broad spectrum of populations. It successfully identified a methodology to quantify microcirculatory alterations associated with disease and the success of capillary recruitment, improving point-of-care application of microcirculatory-targeted resuscitation procedures.

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