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Leali M, Marongiu I, Spinelli E, Chiavieri V, Perez J, Panigada M, Grasselli G, Mauri T. Absolute values of regional ventilation-perfusion mismatch in patients with ARDS monitored by electrical impedance tomography and the role of dead space and shunt compensation. Crit Care 2024; 28:241. [PMID: 39010228 PMCID: PMC11251389 DOI: 10.1186/s13054-024-05033-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 07/11/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND Assessment of regional ventilation/perfusion (V'/Q) mismatch using electrical impedance tomography (EIT) represents a promising advancement for personalized management of the acute respiratory distress syndrome (ARDS). However, accuracy is still hindered by the need for invasive monitoring to calibrate ventilation and perfusion. Here, we propose a non-invasive correction that uses only EIT data and characterized patients with more pronounced compensation of V'/Q mismatch. METHODS We enrolled twenty-one ARDS patients on controlled mechanical ventilation. Cardiac output was measured invasively, and ventilation and perfusion were assessed by EIT. Relative V'/Q maps by EIT were calibrated to absolute values using the minute ventilation to invasive cardiac output (MV/CO) ratio (V'/Q-ABS), left unadjusted (V'/Q-REL), or corrected by MV/CO ratio derived from EIT data (V'/Q-CORR). The ratio between ventilation to dependent regions and perfusion reaching shunted units ( V D ' /QSHUNT) was calculated as an index of more effective hypoxic pulmonary vasoconstriction. The ratio between perfusion to non-dependent regions and ventilation to dead space units (QND/ V DS ' ) was calculated as an index of hypocapnic pneumoconstriction. RESULTS Our calibration factor correlated with invasive MV/CO (r = 0.65, p < 0.001), showed good accuracy and no apparent bias. Compared to V'/Q-ABS, V'/Q-REL maps overestimated ventilation (p = 0.013) and perfusion (p = 0.002) to low V'/Q units and underestimated ventilation (p = 0.011) and perfusion (p = 0.008) to high V'/Q units. The heterogeneity of ventilation and perfusion reaching different V'/Q compartments was underestimated. V'/Q-CORR maps eliminated all these differences with V'/Q-ABS (p > 0.05). HigherV D ' / Q SHUNT correlated with higher PaO2/FiO2 (r = 0.49, p = 0.025) and lower shunt fraction (ρ = - 0.59, p = 0.005). HigherQ ND / V DS ' correlated with lower PEEP (ρ = - 0.62, p = 0.003) and plateau pressure (ρ = - 0.59, p = 0.005). Lower values of both indexes were associated with less ventilator-free days (p = 0.05 and p = 0.03, respectively). CONCLUSIONS Regional V'/Q maps calibrated with a non-invasive EIT-only method closely approximate the ones obtained with invasive monitoring. Higher efficiency of shunt compensation improves oxygenation while compensation of dead space is less needed at lower airway pressure. Patients with more effective compensation mechanisms could have better outcomes.
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Affiliation(s)
- Marco Leali
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Ines Marongiu
- Department of Anesthesia, Critical Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Elena Spinelli
- Department of Anesthesia, Critical Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Valentina Chiavieri
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Joaquin Perez
- Department of Anesthesia, Critical Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Mauro Panigada
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Department of Anesthesia, Critical Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Giacomo Grasselli
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Department of Anesthesia, Critical Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Tommaso Mauri
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
- Department of Anesthesia, Critical Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
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Martin KT, Xin Y, Gaulton TG, Victor M, Santiago RR, Kim T, Morais CCA, Kazimi AA, Connell M, Gerard SE, Herrmann J, Mueller AL, Lenart A, Shen J, Khan SS, Petrov M, Reutlinger K, Rozenberg K, Amato M, Berra L, Cereda M. Electrical Impedance Tomography Identifies Evolution of Regional Perfusion in a Porcine Model of Acute Respiratory Distress Syndrome. Anesthesiology 2023; 139:815-826. [PMID: 37566686 PMCID: PMC10840641 DOI: 10.1097/aln.0000000000004731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/13/2023]
Abstract
BACKGROUND Bedside electrical impedance tomography could be useful to visualize evolving pulmonary perfusion distributions when acute respiratory distress syndrome worsens or in response to ventilatory and positional therapies. In experimental acute respiratory distress syndrome, this study evaluated the agreement of electrical impedance tomography and dynamic contrast-enhanced computed tomography perfusion distributions at two injury time points and in response to increased positive end-expiratory pressure (PEEP) and prone position. METHODS Eleven mechanically ventilated (VT 8 ml · kg-1) Yorkshire pigs (five male, six female) received bronchial hydrochloric acid (3.5 ml · kg-1) to invoke lung injury. Electrical impedance tomography and computed tomography perfusion images were obtained at 2 h (early injury) and 24 h (late injury) after injury in supine position with PEEP 5 and 10 cm H2O. In eight animals, electrical impedance tomography and computed tomography perfusion imaging were also conducted in the prone position. Electrical impedance tomography perfusion (QEIT) and computed tomography perfusion (QCT) values (as percentages of image total) were compared in eight vertical regions across injury stages, levels of PEEP, and body positions using mixed-effects linear regression. The primary outcome was agreement between QEIT and QCT, defined using limits of agreement and Pearson correlation coefficient. RESULTS Pao2/Fio2 decreased over the course of the experiment (healthy to early injury, -253 [95% CI, -317 to -189]; early to late injury, -88 [95% CI, -151 to -24]). The limits of agreement between QEIT and QCT were -4.66% and 4.73% for the middle 50% quantile of average regional perfusion, and the correlation coefficient was 0.88 (95% CI, 0.86 to 0.90]; P < 0.001). Electrical impedance tomography and computed tomography showed similar perfusion redistributions over injury stages and in response to increased PEEP. QEIT redistributions after positional therapy underestimated QCT in ventral regions and overestimated QCT in dorsal regions. CONCLUSIONS Electrical impedance tomography closely approximated computed tomography perfusion measures in experimental acute respiratory distress syndrome, in the supine position, over injury progression and with increased PEEP. Further validation is needed to determine the accuracy of electrical impedance tomography in measuring perfusion redistributions after positional changes. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Kevin T Martin
- Department of Anesthesia and Perioperative Care, University of California San Francisco, CA, USA
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Yi Xin
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Timothy G Gaulton
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Marcus Victor
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Electronics Engineering Division, Aeronautics Institute of Technology, São Paulo, Brazil
| | - Roberta R Santiago
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Taehwan Kim
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Caio C A Morais
- Department of Physical Therapy, Federal University of Pernambuco, Recife, Brazil
| | - Aubrey A Kazimi
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Marc Connell
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
- University of Pittsburgh, School of Medicine, Pittsburgh, PA, USA
| | - Sarah E Gerard
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Jacob Herrmann
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Ariel L Mueller
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Austin Lenart
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Jiacheng Shen
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Sherbano S Khan
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Mihail Petrov
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Kristan Reutlinger
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Karina Rozenberg
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Marcelo Amato
- Department of Cardio-Pulmonary, University of São Paulo, São Paulo, Brazil
| | - Lorenzo Berra
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Maurizio Cereda
- Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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Putensen C, Gattinoni L, Leonhardt S. Electrical Impedance Tomography: Is It Ready to Measure Pulmonary Perfusion Distribution at the Bedside? Anesthesiology 2023; 139:722-725. [PMID: 37934108 DOI: 10.1097/aln.0000000000004770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Affiliation(s)
- Christian Putensen
- Department of Anaesthesiology and Intensive Care Medicine, University Hospital Bonn, Bonn, Germany
| | - Luciano Gattinoni
- Department of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany
| | - Steffen Leonhardt
- Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
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Larrabee S, Nugen S, Bruhn A, Porter I, Stowe S, Adler A, Martin-Flores M, Araos J. Three-dimensional electrical impedance tomography to study regional ventilation/perfusion ratios in anesthetized pigs. Am J Physiol Lung Cell Mol Physiol 2023; 325:L638-L646. [PMID: 37724348 DOI: 10.1152/ajplung.00180.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 09/08/2023] [Accepted: 09/13/2023] [Indexed: 09/20/2023] Open
Abstract
This study aimed to develop a three-dimensional (3-D) method for assessing ventilation/perfusion (V/Q̇) ratios in a pig model of hemodynamic perturbations using electrical impedance tomography (EIT). To evaluate the physiological coherence of changes in EIT-derived V/Q̇ ratios, global EIT-derived V/Q̇ mismatches were compared with global gold standards. The study found regional heterogeneity in the distribution of V/Q̇ ratios in both the ventrodorsal and craniocaudal directions. Although global EIT-derived indices of V/Q̇ mismatch consistently underestimated both low and high V/Q̇ mismatch compared with global gold standards, the direction of the change was similar. We made the software available at no cost for other researchers to use. Future studies should compare regional V/Q̇ ratios determined by our method against other regional, high-resolution methods.NEW & NOTEWORTHY In this study, we introduce a novel 3-D method for assessing ventilation-perfusion (V/Q̇) ratios using electrical impedance tomography (EIT). Heterogeneity in V/Q̇ distribution showcases the significant potential for enhanced understanding of pulmonary conditions. This work signifies a substantial step forward in the application of EIT for monitoring and managing lung diseases.
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Affiliation(s)
- Shannon Larrabee
- Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States
| | - Sarah Nugen
- Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States
| | - Alejandro Bruhn
- Departamento de Medicina Intensiva, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ian Porter
- Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States
| | - Symon Stowe
- Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada
| | - Andy Adler
- Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada
| | - Manuel Martin-Flores
- Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States
| | - Joaquin Araos
- Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States
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5
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Wrigge H, Muders T, Petroff D. Electrical Impedance Tomography: The Electrocardiogram for the Lungs? Am J Respir Crit Care Med 2023; 208:3-5. [PMID: 37311244 PMCID: PMC10870851 DOI: 10.1164/rccm.202305-0810ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 06/06/2023] [Indexed: 06/15/2023] Open
Affiliation(s)
- Hermann Wrigge
- Department of Anesthesiology, Intensive Care, Emergency Medicine, and Pain Therapy Bergmannstrost Hospital Halle, Germany and Medical Faculty Martin-Luther University Halle-Wittenberg Halle, Germany
| | - Thomas Muders
- Department of Anesthesiology and Intensive Care Medicine University Hospital Bonn Bonn, Germany
| | - David Petroff
- Clinical Trial Centre University of Leipzig Leipzig, Germany
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Rixen J, Eliasson B, Lyra S, Leonhardt S. Shape analysis of training data for neural networks in Electrical Impedance Tomography. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38082893 DOI: 10.1109/embc40787.2023.10340254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Electrical Impedance Tomography (EIT) is a cost-effective and fast way to visualize dielectric properties of the human body, through the injection of alternating currents and measurement of the resulting potential on the bodies surface. However, this comes at the cost of low resolution as EIT is a non-linear ill-posed inverse problem. Recently Deep Learning methods have gained the interest in this field, as they provide a way to mimic non-linear functions. Most of the approaches focus on the structure of the Artificial Neural Networks (ANNs), while only glancing over the used training data. However, the structure of the training data is of great importance, as it needs to be simulated. In this work, we analyze the effect of basic shapes to be included as targets in the training data set. We compared inclusions of ellipsoids, cubes and octahedra as training data for ANNs in terms of reconstruction quality. For that, we used the well-established GREIT figures of merit on laboratory tank measurements. We found that ellipsoids resulted in the best reconstruction quality of EIT images. This shows that the choice of simulation data has an impact on the ANN reconstruction quality.Clinical relevance- This work helps to improve time independent EIT reconstruction, which in turn allows for extraction of time independent features of e.g., the lung.
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Muders T, Hentze B, Leonhardt S, Putensen C. Evaluation of Different Contrast Agents for Regional Lung Perfusion Measurement Using Electrical Impedance Tomography: An Experimental Pilot Study. J Clin Med 2023; 12:jcm12082751. [PMID: 37109088 PMCID: PMC10143707 DOI: 10.3390/jcm12082751] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 03/22/2023] [Accepted: 04/03/2023] [Indexed: 04/29/2023] Open
Abstract
Monitoring regional blood flow distribution in the lungs appears to be useful for individually optimizing ventilation therapy. Electrical impedance tomography (EIT) can be used at the bedside for indicator-based regional lung perfusion measurement. Hypertonic saline is widely used as a contrast agent but could be problematic for clinical use due to potential side effects. In five ventilated healthy pigs, we investigated the suitability of five different injectable and clinically approved solutions as contrast agents for EIT-based lung perfusion measurement. Signal extraction success rate, signal strength, and image quality were analyzed after repeated 10 mL bolus injections during temporary apnea. The best results were obtained using NaCl 5.85% and sodium-bicarbonate 8.4% with optimal success rates (100%, each), the highest signal strengths (100 ± 25% and 64 ± 17%), and image qualities (r = 0.98 ± 0.02 and 0.95 ± 0.07). Iomeprol 400 mg/mL (non-ionic iodinated X-ray contrast medium) and Glucose 5% (non-ionic glucose solution) resulted in mostly well usable signals with above average success rates (87% and 89%), acceptable signal strength (32 ± 8% and 16 + 3%), and sufficient image qualities (r = 0.80 ± 0.19 and 0.72 ± 0.21). Isotonic balanced crystalloid solution failed due to a poor success rate (42%), low signal strength (10 ± 4%), and image quality (r = 0.43 ± 0.28). While Iomeprol might enable simultaneous EIT and X-ray measurements, glucose might help to avoid sodium and chloride overload. Further research should address optimal doses to balance reliability and potential side effects.
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Affiliation(s)
- Thomas Muders
- Department of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, 53127 Bonn, Germany
| | - Benjamin Hentze
- Department of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, 53127 Bonn, Germany
- Chair for Medical Information Technology, RWTH Aachen University, 52074 Aachen, Germany
| | - Steffen Leonhardt
- Chair for Medical Information Technology, RWTH Aachen University, 52074 Aachen, Germany
| | - Christian Putensen
- Department of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, 53127 Bonn, Germany
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Jiang H, Han Y, Zheng X, Fang Q. Roles of electrical impedance tomography in lung transplantation. Front Physiol 2022; 13:986422. [PMID: 36407002 PMCID: PMC9669435 DOI: 10.3389/fphys.2022.986422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022] Open
Abstract
Lung transplantation is the preferred treatment method for patients with end-stage pulmonary disease. However, several factors hinder the progress of lung transplantation, including donor shortages, candidate selection, and various postoperative complications. Electrical impedance tomography (EIT) is a functional imaging tool that can be used to evaluate pulmonary ventilation and perfusion at the bedside. Among patients after lung transplantation, monitoring the graft’s pulmonary function is one of the most concerning issues. The feasible application of EIT in lung transplantation has been reported over the past few years, and this technique has gained increasing interest from multidisciplinary researchers. Nevertheless, physicians still lack knowledge concerning the potential applications of EIT in lung transplantation. We present an updated review of EIT in lung transplantation donors and recipients over the past few years, and discuss the potential use of ventilation- and perfusion-monitoring-based EIT in lung transplantation.
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Affiliation(s)
| | | | - Xia Zheng
- *Correspondence: Xia Zheng, ; Qiang Fang,
| | - Qiang Fang
- *Correspondence: Xia Zheng, ; Qiang Fang,
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9
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Ball L, Scaramuzzo G, Herrmann J, Cereda M. Lung aeration, ventilation, and perfusion imaging. Curr Opin Crit Care 2022; 28:302-307. [PMID: 35653251 PMCID: PMC9178949 DOI: 10.1097/mcc.0000000000000942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
PURPOSE OF REVIEW Lung imaging is a cornerstone of the management of patients admitted to the intensive care unit (ICU), providing anatomical and functional information on the respiratory system function. The aim of this review is to provide an overview of mechanisms and applications of conventional and emerging lung imaging techniques in critically ill patients. RECENT FINDINGS Chest radiographs provide information on lung structure and have several limitations in the ICU setting; however, scoring systems can be used to stratify patient severity and predict clinical outcomes. Computed tomography (CT) is the gold standard for assessment of lung aeration but requires moving the patients to the CT facility. Dual-energy CT has been recently applied to simultaneous study of lung aeration and perfusion in patients with respiratory failure. Lung ultrasound has an established role in the routine bedside assessment of ICU patients, but has poor spatial resolution and largely relies on the analysis of artifacts. Electrical impedance tomography is an emerging technique capable of depicting ventilation and perfusion at the bedside and at the regional level. SUMMARY Clinicians should be confident with the technical aspects, indications, and limitations of each lung imaging technique to improve patient care.
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Affiliation(s)
- Lorenzo Ball
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, Genoa, Italy
- Anesthesia and Intensive Care, Ospedale Policlinico San Martino, IRCCS per l’Oncologia e le Neuroscienze, Genoa, Italy
| | - Gaetano Scaramuzzo
- Department of Translational medicine, University of Ferrara, Ferrara, Italy
- Anesthesia and intensive care, Arcispedale Sant’Anna, Ferrara, Italy
| | - Jake Herrmann
- Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, United States of America
| | - Maurizio Cereda
- Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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A Rotational Invariant Neural Network for Electrical Impedance Tomography Imaging without Reference Voltage: RF-REIM-NET. Diagnostics (Basel) 2022; 12:diagnostics12040777. [PMID: 35453825 PMCID: PMC9028444 DOI: 10.3390/diagnostics12040777] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/16/2022] [Accepted: 03/19/2022] [Indexed: 02/04/2023] Open
Abstract
Background: Electrical Impedance Tomography (EIT) is a radiation-free technique for image reconstruction. However, as the inverse problem of EIT is non-linear and ill-posed, the reconstruction of sharp conductivity images poses a major problem. With the emergence of artificial neural networks (ANN), their application in EIT has recently gained interest. Methodology: We propose an ANN that can solve the inverse problem without the presence of a reference voltage. At the end of the ANN, we reused the dense layers multiple times, considering that the EIT exhibits rotational symmetries in a circular domain. To avoid bias in training data, the conductivity range used in the simulations was greater than expected in measurements. We also propose a new method that creates new data samples from existing training data. Results: We show that our ANN is more robust with respect to noise compared with the analytical Gauss–Newton approach. The reconstruction results for EIT phantom tank measurements are also clearer, as ringing artefacts are less pronounced. To evaluate the performance of the ANN under real-world conditions, we perform reconstructions on an experimental pig study with computed tomography for comparison. Conclusions: Our proposed ANN can reconstruct EIT images without the need of a reference voltage.
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11
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Nguyen DM, Duong Trong L, McEwan AL. An efficient and fast multi-band focused bioimpedance solution with EIT-based reconstruction for pulmonary embolism assessment: a simulation study from massive to segmental blockage. Physiol Meas 2022; 43. [PMID: 34986471 DOI: 10.1088/1361-6579/ac4830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 01/05/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Pulmonary embolism (PE) is an acute condition that blocks the perfusion to the lungs and is a common complication of Covid-19. However, PE is often not diagnosed in time, especially in the pandemic time due to complicated diagnosis protocol. In this study, a non-invasive, fast and efficient bioimpedance method with the EIT-based reconstruction approach is proposed to assess the lung perfusion reliably. APPROACH Some proposals are presented to improve the sensitivity and accuracy for the bioimpedance method: (1) a new electrode configuration and focused pattern to help study deep changes caused by PE within each lung field separately, (2) a measurement strategy to compensate the effect of different boundary shapes and varied respiratory conditions on the perfusion signals and (3) an estimator to predict the lung perfusion capacity, from which the severity of PE can be assessed. The proposals were tested on the first-time simulation of PE events at different locations and degrees from segmental blockages to massive blockages. Different object boundary shapes and varied respiratory conditions were included in the simulation to represent for different populations in real measurements. RESULTS The correlation between the estimator and the perfusion was very promising (R = 0.91, errors < 6%). The measurement strategy with the proposed configuration and pattern has helped stabilize the estimator to non-perfusion factors such as the boundary shapes and varied respiration conditions (3-5% errors). SIGNIFICANCE This promising preliminary result has demonstrated the proposed bioimpedance method's capability and feasibility, and might start a new direction for this application.
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Affiliation(s)
- Duc Minh Nguyen
- School of Biomedical Engineering, University of Sydney - Camperdown and Darlington Campus SciTech Library, Room 415, Level 4, Link Building Faculty of Engineering and IT, The University of Sydney, Darlington, Hanoi, New South Wales, 100000, AUSTRALIA
| | - Luong Duong Trong
- School of Electronics and Telecommunication, Hanoi University of Science and Technology, No. 1, Dai Co Viet Street, Hai Ba Trung District, Hanoi, 100000, VIET NAM
| | - Alistair L McEwan
- School of Biomedical Engineering, The University of Sydney, Room 415, Level 4, Link Building Faculty of Engineering and IT, The University of Sydney, Darlington NSW 2006, Australia, Sydney, New South Wales, 2006, AUSTRALIA
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12
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Xu M, He H, Long Y. Lung Perfusion Assessment by Bedside Electrical Impedance Tomography in Critically Ill Patients. Front Physiol 2021; 12:748724. [PMID: 34721072 PMCID: PMC8548642 DOI: 10.3389/fphys.2021.748724] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 09/13/2021] [Indexed: 12/02/2022] Open
Abstract
As a portable, radiation-free imaging modality, electrical impedance tomography (EIT) technology has shown promise in the bedside visual assessment of lung perfusion distribution in critically ill patients. The two main methods of EIT for assessing lung perfusion are the pulsatility and conductivity contrast (saline) bolus method. Increasing attention is being paid to the saline bolus EIT method in the evaluation of regional pulmonary perfusion in clinical practice. This study seeks to provide an overview of experimental and clinical studies with the aim of clarifying the progress made in the use of the saline bolus EIT method. Animal studies revealed that the saline bolus EIT method presented good consistency with single-photon emission CT (SPECT) in the evaluation of lung regional perfusion changes in various pathological conditions. Moreover, the saline bolus EIT method has been applied to assess the lung perfusion in a pulmonary embolism and the effect of positive end-expiratory pressure (PEEP) on regional ventilation/perfusion ratio (V/Q) and acute respiratory distress syndrome (ARDS) in several clinical studies. The implementation of saline boluses, data analyses, precision, and cutoff values varied among different studies, and a consensus must be reached regarding the clinical application of the saline bolus EIT method. Further study is required to validate the impact of the described saline bolus EIT method on decision-making, therapeutic management, and outcomes in critically ill patients.
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Affiliation(s)
- Mengru Xu
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Critical Care Medicine, Peking Union Medical College, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Huaiwu He
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Critical Care Medicine, Peking Union Medical College, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yun Long
- State Key Laboratory of Complex Severe and Rare Diseases, Department of Critical Care Medicine, Peking Union Medical College, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
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Hentze B, Muders T, Hoog Antink C, Putensen C, Larsson A, Hedenstierna G, Walter M, Leonhardt S. A model-based source separation algorithm for lung perfusion imaging using electrical impedance tomography. Physiol Meas 2021; 42. [PMID: 34167091 DOI: 10.1088/1361-6579/ac0e84] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 06/24/2021] [Indexed: 11/11/2022]
Abstract
Objective. Electrical impedance tomography (EIT) for lung perfusion imaging is attracting considerable interest in intensive care, as it might open up entirely new ways to adjust ventilation therapy. A promising technique is bolus injection of a conductive indicator to the central venous catheter, which yields the indicator-based signal (IBS). Lung perfusion images are then typically obtained from the IBS using the maximum slope technique. However, the low spatial resolution of EIT results in a partial volume effect (PVE), which requires further processing to avoid regional bias.Approach. In this work, we repose the extraction of lung perfusion images from the IBS as a source separation problem to account for the PVE. We then propose a model-based algorithm, called gamma decomposition (GD), to derive an efficient solution. The GD algorithm uses a signal model to transform the IBS into a parameter space where the source signals of heart and lung are separable by clustering in space and time. Subsequently, it reconstructs lung model signals from which lung perfusion images are unambiguously extracted.Main results. We evaluate the GD algorithm on EIT data of a prospective animal trial with eight pigs. The results show that it enables lung perfusion imaging using EIT at different stages of regional impairment. Furthermore, parameters of the source signals seem to represent physiological properties of the cardio-pulmonary system.Significance. This work represents an important advance in IBS processing that will likely reduce bias of EIT perfusion images and thus eventually enable imaging of regional ventilation/perfusion (V/Q) ratio.
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Affiliation(s)
- Benjamin Hentze
- Medical Information Technology, RWTH Aachen University, Pauwelsstr. 20, 52074 Aachen, Germany.,Department of Anaesthesiology and Intensive Care Medicine, University of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany
| | - Thomas Muders
- Department of Anaesthesiology and Intensive Care Medicine, University of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany
| | - Christoph Hoog Antink
- Medical Information Technology, RWTH Aachen University, Pauwelsstr. 20, 52074 Aachen, Germany.,Biomedical Engineering, TU Darmstadt, Darmstadt, Germany
| | - Christian Putensen
- Department of Anaesthesiology and Intensive Care Medicine, University of Bonn, Venusberg-Campus 1, 53127 Bonn, Germany
| | - Anders Larsson
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | | | - Marian Walter
- Medical Information Technology, RWTH Aachen University, Pauwelsstr. 20, 52074 Aachen, Germany
| | - Steffen Leonhardt
- Medical Information Technology, RWTH Aachen University, Pauwelsstr. 20, 52074 Aachen, Germany
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14
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Pelosi P, Ball L, Barbas CSV, Bellomo R, Burns KEA, Einav S, Gattinoni L, Laffey JG, Marini JJ, Myatra SN, Schultz MJ, Teboul JL, Rocco PRM. Personalized mechanical ventilation in acute respiratory distress syndrome. Crit Care 2021; 25:250. [PMID: 34271958 PMCID: PMC8284184 DOI: 10.1186/s13054-021-03686-3] [Citation(s) in RCA: 95] [Impact Index Per Article: 31.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 07/08/2021] [Indexed: 01/22/2023] Open
Abstract
A personalized mechanical ventilation approach for patients with adult respiratory distress syndrome (ARDS) based on lung physiology and morphology, ARDS etiology, lung imaging, and biological phenotypes may improve ventilation practice and outcome. However, additional research is warranted before personalized mechanical ventilation strategies can be applied at the bedside. Ventilatory parameters should be titrated based on close monitoring of targeted physiologic variables and individualized goals. Although low tidal volume (VT) is a standard of care, further individualization of VT may necessitate the evaluation of lung volume reserve (e.g., inspiratory capacity). Low driving pressures provide a target for clinicians to adjust VT and possibly to optimize positive end-expiratory pressure (PEEP), while maintaining plateau pressures below safety thresholds. Esophageal pressure monitoring allows estimation of transpulmonary pressure, but its use requires technical skill and correct physiologic interpretation for clinical application at the bedside. Mechanical power considers ventilatory parameters as a whole in the optimization of ventilation setting, but further studies are necessary to assess its clinical relevance. The identification of recruitability in patients with ARDS is essential to titrate and individualize PEEP. To define gas-exchange targets for individual patients, clinicians should consider issues related to oxygen transport and dead space. In this review, we discuss the rationale for personalized approaches to mechanical ventilation for patients with ARDS, the role of lung imaging, phenotype identification, physiologically based individualized approaches to ventilation, and a future research agenda.
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Affiliation(s)
- Paolo Pelosi
- Anesthesia and Intensive Care, San Martino Policlinico Hospital, IRCCS for Oncology and Neuroscience, Genoa, Italy.
- Department of Surgical Sciences and Integrated Diagnostic (DISC), University of Genoa, Viale Benedetto XV 16, Genoa, Italy.
| | - Lorenzo Ball
- Anesthesia and Intensive Care, San Martino Policlinico Hospital, IRCCS for Oncology and Neuroscience, Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostic (DISC), University of Genoa, Viale Benedetto XV 16, Genoa, Italy
| | - Carmen S V Barbas
- Pneumology and Intensive Care Medicine, University of São Paulo, São Paulo, Brazil
- Adult Intensive Care Unit, Albert Einstein Hospital, São Paulo, Brazil
| | - Rinaldo Bellomo
- Department of Intensive Care, Austin Hospital, Melbourne, VIC, Australia
- Department of Epidemiology and Preventive Medicine, Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia
- Data Analytics Research and Evaluation Centre, The University of Melbourne and Austin Hospital, Melbourne, Australia
- Department of Intensive Care, Royal Melbourne Hospital, Melbourne, VIC, Australia
- Department of Critical Care, The University of Melbourne, Melbourne, Australia
| | - Karen E A Burns
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
- Unity Health Toronto-St. Michael's Hospital, Li Ka Shing Knowledge Institute, Toronto, ON, Canada
| | - Sharon Einav
- Intensive Care Unit of the Shaare Zedek Medical Medical Centre, Hebrew University Faculty of Medicine, Jerusalem, Israel
| | - Luciano Gattinoni
- Department of Anaesthesiology, Emergency, and Intensive Care Medicine, University of Göttingen, Göttingen, Germany
| | - John G Laffey
- Anaesthesia and Intensive Care Medicine, University Hospital Galway, and School of Medicine, National University of Ireland, Galway, Ireland
| | - John J Marini
- University of Minnesota and Regions Hospital, St. Paul, MN, USA
| | - Sheila N Myatra
- Department of Anaesthesiology, Critical Care and Pain, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, India
| | - Marcus J Schultz
- Mahidol Oxford Tropical Medicine Research Unit (MORU), Mahidol University, Bangkok, Thailand
- Department of Intensive Care, Amsterdam University Medical Centers, Amsterdam, The Netherlands
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jean Louis Teboul
- Service de Médecine Intensive-Réanimation, Hôpital Bicêtre, Inserm UMR S_999, AP-HP Université Paris-Saclay, Le Kremlin-Bicêtre, France
| | - Patricia R M Rocco
- Laboratory of Pulmonary Investigation, Carlos Chagas Filho Institute of Biophysics, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
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15
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Raisis AL, Mosing M, Hosgood GL, Secombe CJ, Adler A, Waldmann AD. The use of electrical impedance tomography (EIT) to evaluate pulse rate in anaesthetised horses. Vet J 2021; 273:105694. [PMID: 34148609 DOI: 10.1016/j.tvjl.2021.105694] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 05/04/2021] [Accepted: 05/12/2021] [Indexed: 10/21/2022]
Abstract
Electrical impedance tomography (EIT) provides clinically useful lung images; however, it would be an advantage to extract additional cardiovascular information from the data. The aim of this study was to evaluate if cardiac-related changes measured by EIT can be used to measure pulse rate (PR) under physiological as well as high and low blood pressure states in anaesthetised horses. Electrical impedance tomography data and PR from seven horses anaesthetised in dorsal recumbency were recorded over 1 min during mechanical ventilation and 1 min of apnoea. Data were collected at four measurement time points; before and during intravenous administration of nitroprusside and phenylephrine, respectively. Nine pixels, estimated to represent the heart, were chosen from the EIT image. A novel algorithm detected peaks of impedance change for these pixels over 10 s intervals. Concurrent PR measured using an invasive blood pressure trace, was recorded every 10 s. EIT- and pulse-rate data were compared using Bland-Altman assessment for multiple measurements on each horse. Overall, 288 paired datasets from six of seven horses were available for analysis. There was excellent agreement for baseline measurements, as well as during hypertension and hypotension, with a bias of -0.26 and lower and upper limit of agreement at -2.22 (95% confidence intervals [CI], -2.89 to -1.86) and 1.69 (95% CI, 1.34-2.36) beats per min, respectively. EIT can be used to evaluate PR using cardiac-related impedance changes. More work is required to determine bias that might occur in anaesthetised horses in other recumbencies or clinical situations.
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Affiliation(s)
- A L Raisis
- School of Veterinary Medicine, College of SHEE, Murdoch University, South Street, Perth, WA, Australia
| | - M Mosing
- School of Veterinary Medicine, College of SHEE, Murdoch University, South Street, Perth, WA, Australia.
| | - G L Hosgood
- School of Veterinary Medicine, College of SHEE, Murdoch University, South Street, Perth, WA, Australia
| | - C J Secombe
- School of Veterinary Medicine, College of SHEE, Murdoch University, South Street, Perth, WA, Australia
| | - A Adler
- Systems and Computer Engineering, Carleton University, Ottawa, Canada
| | - A D Waldmann
- Department of Anesthesiology and Intensive Care Medicine, Rostock University Medical Center, Rostock, Germany
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16
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He H, Long Y, Chi Y, Yuan S, Zhao Z. Reply to Wang and Zhong: Bedside Evaluation of Pulmonary Embolism by Saline Contrast-enhanced Electrical Impedance Tomography: Considerations for Future Research. Am J Respir Crit Care Med 2021; 203:395-397. [PMID: 33091316 PMCID: PMC7874319 DOI: 10.1164/rccm.202010-3768le] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Huaiwu He
- Peking Union Medical College HospitalBeijing, China
- State Key Laboratory of Complex Severe and Rare DiseasesBeijing, China
| | - Yun Long
- Peking Union Medical College HospitalBeijing, China
- State Key Laboratory of Complex Severe and Rare DiseasesBeijing, China
| | - Yi Chi
- Peking Union Medical College HospitalBeijing, China
- State Key Laboratory of Complex Severe and Rare DiseasesBeijing, China
| | - Siyi Yuan
- Peking Union Medical College HospitalBeijing, China
- State Key Laboratory of Complex Severe and Rare DiseasesBeijing, China
| | - Zhanqi Zhao
- Furtwangen UniversityVillingen-Schwenningen, Germanyand
- Fourth Military Medical UniversityXi’an, China
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17
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Kircher M, Elke G, Stender B, Hernandez Mesa M, Schuderer F, Dossel O, Fuld MK, Halaweish AF, Hoffman EA, Weiler N, Frerichs I. Regional Lung Perfusion Analysis in Experimental ARDS by Electrical Impedance and Computed Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:251-261. [PMID: 32956046 DOI: 10.1109/tmi.2020.3025080] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Electrical impedance tomography is clinically used to trace ventilation related changes in electrical conductivity of lung tissue. Estimating regional pulmonary perfusion using electrical impedance tomography is still a matter of research. To support clinical decision making, reliable bedside information of pulmonary perfusion is needed. We introduce a method to robustly detect pulmonary perfusion based on indicator-enhanced electrical impedance tomography and validate it by dynamic multidetector computed tomography in two experimental models of acute respiratory distress syndrome. The acute injury was induced in a sublobar segment of the right lung by saline lavage or endotoxin instillation in eight anesthetized mechanically ventilated pigs. For electrical impedance tomography measurements, a conductive bolus (10% saline solution) was injected into the right ventricle during breath hold. Electrical impedance tomography perfusion images were reconstructed by linear and normalized Gauss-Newton reconstruction on a finite element mesh with subsequent element-wise signal and feature analysis. An iodinated contrast agent was used to compute pulmonary blood flow via dynamic multidetector computed tomography. Spatial perfusion was estimated based on first-pass indicator dilution for both electrical impedance and multidetector computed tomography and compared by Pearson correlation and Bland-Altman analysis. Strong correlation was found in dorsoventral (r = 0.92) and in right-to-left directions (r = 0.85) with good limits of agreement of 8.74% in eight lung segments. With a robust electrical impedance tomography perfusion estimation method, we found strong agreement between multidetector computed and electrical impedance tomography perfusion in healthy and regionally injured lungs and demonstrated feasibility of electrical impedance tomography perfusion imaging.
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18
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Electrical Impedance Tomography for Cardio-Pulmonary Monitoring. J Clin Med 2019; 8:jcm8081176. [PMID: 31394721 PMCID: PMC6722958 DOI: 10.3390/jcm8081176] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 08/05/2019] [Accepted: 08/06/2019] [Indexed: 12/14/2022] Open
Abstract
Electrical impedance tomography (EIT) is a bedside monitoring tool that noninvasively visualizes local ventilation and arguably lung perfusion distribution. This article reviews and discusses both methodological and clinical aspects of thoracic EIT. Initially, investigators addressed the validation of EIT to measure regional ventilation. Current studies focus mainly on its clinical applications to quantify lung collapse, tidal recruitment, and lung overdistension to titrate positive end-expiratory pressure (PEEP) and tidal volume. In addition, EIT may help to detect pneumothorax. Recent studies evaluated EIT as a tool to measure regional lung perfusion. Indicator-free EIT measurements might be sufficient to continuously measure cardiac stroke volume. The use of a contrast agent such as saline might be required to assess regional lung perfusion. As a result, EIT-based monitoring of regional ventilation and lung perfusion may visualize local ventilation and perfusion matching, which can be helpful in the treatment of patients with acute respiratory distress syndrome (ARDS).
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19
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Mauri T, Mercat A, Grasselli G. What's new in electrical impedance tomography. Intensive Care Med 2018; 45:674-677. [PMID: 30284639 DOI: 10.1007/s00134-018-5398-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Accepted: 09/26/2018] [Indexed: 12/29/2022]
Affiliation(s)
- Tommaso Mauri
- Department of Anesthesiology, Intensive Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy.,Department of Pathophysiology and Transplantation, University of Milan, Via Festa del Perdono 1, 20122, Milan, Italy
| | - Alain Mercat
- Département de Médecine Intensive-Réanimation, CHU d'Angers, Université d'Angers, Angers, France
| | - Giacomo Grasselli
- Department of Anesthesiology, Intensive Care and Emergency, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy. .,Department of Pathophysiology and Transplantation, University of Milan, Via Festa del Perdono 1, 20122, Milan, Italy.
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