Matthias Peter Hilty1,2, Sakir Akin1,3, Christiaan Boerma4, Abele Donati5, Özge Erdem6, Paolo Giaccaglia5, Philippe Guerci1,7,8, Dan Mj Milstein9, Jonathan Montomoli1,5, Fevzi Toraman10, Zuhre Uz11, Gerke Veenstra4, Can Ince1. 1. Department of Intensive Care, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. 2. Institute of Intensive Care Medicine, University Hospital of Zurich, Zurich, Switzerland. 3. Department of Intensive Care, Haga Teaching Hospital, The Hague, The Netherlands. 4. Intensive Care Unit, Medical Center Leeuwarden, Leeuwarden, The Netherlands. 5. Anesthesia and Intensive Care Unit, Department of Biomedical Sciences and Public Health, Marche Politechnic University, Ancona, Italy. 6. Intensive Care and Department of Pediatric Surgery, Sophia Children's Hospital, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. 7. Department of Anesthesiology and Critical Care Medicine, University Hospital of Nancy, France. 8. INSERM U1116, University of Lorraine, Vandoeuvre-Les-Nancy, France. 9. Department of Oral and Maxillofacial Surgery, Academic Medical Center, Amsterdam, The Netherlands. 10. Department of Anesthesiology and Reanimation, Acibadem Mehmet Ali Aydinlar University School of Medicine, Istanbul, Turkey. 11. Department of Translational Physiology, Academic Medical Center, Amsterdam, The Netherlands.
Abstract
OBJECTIVES: Reliable 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. DESIGN: Retrospective 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. SETTING: Ten perioperative/ICU/volunteer studies in six international teaching hospitals. PATIENTS: The database encompass 267 adult and pediatric patients undergoing surgery, treatment for sepsis, and heart failure in the ICU and healthy volunteers. INTERVENTIONS: Perioperative and ICU standard of care. MEASUREMENTS AND MAIN RESULTS: One 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. CONCLUSIONS: Algorithm-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.
OBJECTIVES: Reliable 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 illpatients and to use this automatic algorithm to data-mine and identify the sublingual microcirculatory variable changes in response to disease and therapy. DESIGN: Retrospective 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. SETTING: Ten perioperative/ICU/volunteer studies in six international teaching hospitals. PATIENTS: The database encompass 267 adult and pediatric patients undergoing surgery, treatment for sepsis, and heart failure in the ICU and healthy volunteers. INTERVENTIONS: Perioperative and ICU standard of care. MEASUREMENTS AND MAIN RESULTS: One 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. CONCLUSIONS: Algorithm-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.
Authors: Jan Bakker; Eduardo Kattan; Djillali Annane; Ricardo Castro; Maurizio Cecconi; Daniel De Backer; Arnaldo Dubin; Laura Evans; Michelle Ng Gong; Olfa Hamzaoui; Can Ince; Bruno Levy; Xavier Monnet; Gustavo A Ospina Tascón; Marlies Ostermann; Michael R Pinsky; James A Russell; Bernd Saugel; Thomas W L Scheeren; Jean-Louis Teboul; Antoine Vieillard Baron; Jean-Louis Vincent; Fernando G Zampieri; Glenn Hernandez Journal: Intensive Care Med Date: 2021-12-15 Impact factor: 17.440
Authors: Jason Stankiewicz; Maniraj Jeyaraju; Andrew R Deitchman; Avelino C Verceles; Alison Grazioli; Michael T McCurdy Journal: ATS Sch Date: 2021-11-30
Authors: Christian S Guay; Mariam Khebir; T Shiva Shahiri; Ariana Szilagyi; Erin Elizabeth Cole; Gabrielle Simoneau; Mohamed Badawy Journal: Intensive Care Med Exp Date: 2021-04-02
Authors: Matthias Peter Hilty; Emanuele Favaron; Pedro David Wendel Garcia; Yavuz Ahiska; Zuhre Uz; Sakir Akin; Moritz Flick; Sesmu Arbous; Daniel A Hofmaenner; Bernd Saugel; Henrik Endeman; Reto Andreas Schuepbach; Can Ince Journal: Crit Care Date: 2022-10-14 Impact factor: 19.334
Authors: Emanuele Favaron; Can Ince; Matthias P Hilty; Bülent Ergin; Philip van der Zee; Zühre Uz; Pedro D Wendel Garcia; Daniel A Hofmaenner; Claudio T Acevedo; Wim Jan van Boven; Sakir Akin; Diederik Gommers; Henrik Endeman Journal: Crit Care Med Date: 2021-04-01 Impact factor: 9.296