Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study

Abstract Background The aim of this study was to validate whether regional ventilation and perfusion data measured by electrical impedance tomography (EIT) with saline bolus could discriminate three broad acute respiratory failure (ARF) etiologies. Methods Perfusion image was generated from EIT-base...

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Main Authors: Huaiwu He, Yi Chi, Yun Long, Siyi Yuan, Rui Zhang, Yingying Yang, Inéz Frerichs, Knut Möller, Feng Fu, Zhanqi Zhao
Format: Article
Language:English
Published: SpringerOpen 2021-08-01
Series:Annals of Intensive Care
Subjects:
V/Q
Online Access:https://doi.org/10.1186/s13613-021-00921-6
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record_format Article
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language English
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sources DOAJ
author Huaiwu He
Yi Chi
Yun Long
Siyi Yuan
Rui Zhang
Yingying Yang
Inéz Frerichs
Knut Möller
Feng Fu
Zhanqi Zhao
spellingShingle Huaiwu He
Yi Chi
Yun Long
Siyi Yuan
Rui Zhang
Yingying Yang
Inéz Frerichs
Knut Möller
Feng Fu
Zhanqi Zhao
Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study
Annals of Intensive Care
Electrical impedance tomography
Lung ventilation
Lung perfusion
Acute respiratory failure
V/Q
author_facet Huaiwu He
Yi Chi
Yun Long
Siyi Yuan
Rui Zhang
Yingying Yang
Inéz Frerichs
Knut Möller
Feng Fu
Zhanqi Zhao
author_sort Huaiwu He
title Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study
title_short Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study
title_full Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study
title_fullStr Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study
title_full_unstemmed Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study
title_sort three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study
publisher SpringerOpen
series Annals of Intensive Care
issn 2110-5820
publishDate 2021-08-01
description Abstract Background The aim of this study was to validate whether regional ventilation and perfusion data measured by electrical impedance tomography (EIT) with saline bolus could discriminate three broad acute respiratory failure (ARF) etiologies. Methods Perfusion image was generated from EIT-based impedance–time curves caused by 10 ml 10% NaCl injection during a respiratory hold. Ventilation image was captured before the breath holding period under regular mechanical ventilation. DeadSpace % , Shunt % and VQMatch % were calculated based on lung perfusion and ventilation images. Ventilation and perfusion maps were divided into four cross-quadrants (lower left and right, upper left and right). Regional distribution defects of each quadrant were scored as 0 (distribution% ≥ 15%), 1 (15% > distribution% ≥ 10%) and 2 (distribution% < 10%). Data percentile distributions in the control group and clinical simplicity were taken into consideration when defining the scores. Overall defect scores (Defect V , Defect Q and Defect V+Q ) were the sum of four cross-quadrants of the corresponding images. Results A total of 108 ICU patients were prospectively included: 93 with ARF and 15 without as a control. PaO2/FiO2 was significantly correlated with VQMatch % (r = 0.324, P = 0.001). Three broad etiologies of ARF were identified based on clinical judgment: pulmonary embolism-related disease (PED, n = 14); diffuse lung involvement disease (DLD, n = 21) and focal lung involvement disease (FLD, n = 58). The PED group had a significantly higher DeadSpace % [40(24)% vs. 14(15)%, PED group vs. the rest of the subjects; median(interquartile range); P < 0.0001] and Defect Q score than the other groups [1(1) vs. 0(1), PED vs. the rest; P < 0.0001]. The DLD group had a significantly lower Defect V+Q score than the PED and FLD groups [0(1) vs. 2.5(2) vs. 3(3), DLD vs. PED vs. FLD; P < 0.0001]. The FLD group had a significantly higher Defect V score than the other groups [2(2) vs. 0(1), FLD vs. the rest; P < 0.0001]. The area under the receiver operating characteristic (AUC) for using DeadSpace % to identify PED was 0.894 in all ARF patients. The AUC for using the Defect V+Q score to identify DLD was 0.893. The AUC for using the Defect V score to identify FLD was 0.832. Conclusions Our study showed that it was feasible to characterize three broad etiologies of ARF with EIT-based regional ventilation and perfusion. Further study is required to validate clinical applicability of this method. Trial registration clinicaltrials, NCT04081142. Registered 9 September 2019—retrospectively registered, https://clinicaltrials.gov/show/NCT04081142 .
topic Electrical impedance tomography
Lung ventilation
Lung perfusion
Acute respiratory failure
V/Q
url https://doi.org/10.1186/s13613-021-00921-6
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spelling doaj-3b7f2f8621d04ce287bfd188870eedea2021-08-29T11:04:05ZengSpringerOpenAnnals of Intensive Care2110-58202021-08-0111111210.1186/s13613-021-00921-6Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating studyHuaiwu He0Yi Chi1Yun Long2Siyi Yuan3Rui Zhang4Yingying Yang5Inéz Frerichs6Knut Möller7Feng Fu8Zhanqi Zhao9Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical SciencesDepartment of Anesthesiology and Intensive Care Medicine, University Medical Center of Schleswig-Holstein Campus KielInstitute of Technical Medicine, Furtwangen UniversityDepartment of Biomedical Engineering, Fourth Military Medical UniversityInstitute of Technical Medicine, Furtwangen UniversityAbstract Background The aim of this study was to validate whether regional ventilation and perfusion data measured by electrical impedance tomography (EIT) with saline bolus could discriminate three broad acute respiratory failure (ARF) etiologies. Methods Perfusion image was generated from EIT-based impedance–time curves caused by 10 ml 10% NaCl injection during a respiratory hold. Ventilation image was captured before the breath holding period under regular mechanical ventilation. DeadSpace % , Shunt % and VQMatch % were calculated based on lung perfusion and ventilation images. Ventilation and perfusion maps were divided into four cross-quadrants (lower left and right, upper left and right). Regional distribution defects of each quadrant were scored as 0 (distribution% ≥ 15%), 1 (15% > distribution% ≥ 10%) and 2 (distribution% < 10%). Data percentile distributions in the control group and clinical simplicity were taken into consideration when defining the scores. Overall defect scores (Defect V , Defect Q and Defect V+Q ) were the sum of four cross-quadrants of the corresponding images. Results A total of 108 ICU patients were prospectively included: 93 with ARF and 15 without as a control. PaO2/FiO2 was significantly correlated with VQMatch % (r = 0.324, P = 0.001). Three broad etiologies of ARF were identified based on clinical judgment: pulmonary embolism-related disease (PED, n = 14); diffuse lung involvement disease (DLD, n = 21) and focal lung involvement disease (FLD, n = 58). The PED group had a significantly higher DeadSpace % [40(24)% vs. 14(15)%, PED group vs. the rest of the subjects; median(interquartile range); P < 0.0001] and Defect Q score than the other groups [1(1) vs. 0(1), PED vs. the rest; P < 0.0001]. The DLD group had a significantly lower Defect V+Q score than the PED and FLD groups [0(1) vs. 2.5(2) vs. 3(3), DLD vs. PED vs. FLD; P < 0.0001]. The FLD group had a significantly higher Defect V score than the other groups [2(2) vs. 0(1), FLD vs. the rest; P < 0.0001]. The area under the receiver operating characteristic (AUC) for using DeadSpace % to identify PED was 0.894 in all ARF patients. The AUC for using the Defect V+Q score to identify DLD was 0.893. The AUC for using the Defect V score to identify FLD was 0.832. Conclusions Our study showed that it was feasible to characterize three broad etiologies of ARF with EIT-based regional ventilation and perfusion. Further study is required to validate clinical applicability of this method. Trial registration clinicaltrials, NCT04081142. Registered 9 September 2019—retrospectively registered, https://clinicaltrials.gov/show/NCT04081142 .https://doi.org/10.1186/s13613-021-00921-6Electrical impedance tomographyLung ventilationLung perfusionAcute respiratory failureV/Q