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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SpringerOpen
2021-08-01
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Online Access: | https://doi.org/10.1186/s13613-021-00921-6 |
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Article |
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DOAJ |
language |
English |
format |
Article |
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 |
work_keys_str_mv |
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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 |