Determination of respiratory gas flow by electrical impedance tomography in an animal model of mechanical ventilation

BMC Pulmonary Medicine

Klaus Markstaller⁴  Matthias David³  Andreas Vogt²  Stephan Bierschock¹  Stefan Boehme⁴  Marc Bodenstein³ 

[1] Department of Anaesthesiology and Intensive Care Medicine, University Hospital of Cologne, Cologne 50924, Germany;Department of Anaesthesiology and Pain Therapy, Inselspital, Bern University Hospital, and University of Bern, Bern 3010, Switzerland;Department of Anaesthesiology, University Medical Center Mainz, Mainz 55101, Germany;Department of Anaesthesia, General Hospital of the City of Vienna, Vienna 1090, Austria

关键词: Spirometry;    Intensive care medicine;    Acute respiratory failure;    Acute lung injury;    Acute respiratory distress syndrome;    Mechanical ventilation;    Electrical impedance tomography;    Regional respiratory gas flow;   

Others  :  862982
DOI  :  10.1186/1471-2466-14-73

 received in 2013-09-07, accepted in 2014-03-28,  发布年份 2014

【 摘 要 】

Background

A recent method determines regional gas flow of the lung by electrical impedance tomography (EIT). The aim of this study is to show the applicability of this method in a porcine model of mechanical ventilation in healthy and diseased lungs. Our primary hypothesis is that global gas flow measured by EIT can be correlated with spirometry. Our secondary hypothesis is that regional analysis of respiratory gas flow delivers physiologically meaningful results.

Methods

In two sets of experiments n = 7 healthy pigs and n = 6 pigs before and after induction of lavage lung injury were investigated. EIT of the lung and spirometry were registered synchronously during ongoing mechanical ventilation. In-vivo aeration of the lung was analysed in four regions-of-interest (ROI) by EIT: 1) global, 2) ventral (non-dependent), 3) middle and 4) dorsal (dependent) ROI. Respiratory gas flow was calculated by the first derivative of the regional aeration curve. Four phases of the respiratory cycle were discriminated. They delivered peak and late inspiratory and expiratory gas flow (PIF, LIF, PEF, LEF) characterizing early or late inspiration or expiration.

Results

Linear regression analysis of EIT and spirometry in healthy pigs revealed a very good correlation measuring peak flow and a good correlation detecting late flow. PIF_EIT = 0.702 · PIF_spiro + 117.4, r² = 0.809; PEF_EIT = 0.690 · PEF_spiro-124.2, r² = 0.760; LIF_EIT = 0.909 · LIF_spiro + 27.32, r² = 0.572 and LEF_EIT = 0.858 · LEF_spiro-10.94, r² = 0.647. EIT derived absolute gas flow was generally smaller than data from spirometry. Regional gas flow was distributed heterogeneously during different phases of the respiratory cycle. But, the regional distribution of gas flow stayed stable during different ventilator settings. Moderate lung injury changed the regional pattern of gas flow.

Conclusions

We conclude that the presented method is able to determine global respiratory gas flow of the lung in different phases of the respiratory cycle. Additionally, it delivers meaningful insight into regional pulmonary characteristics, i.e. the regional ability of the lung to take up and to release air.

【 授权许可】

   
2014 Bodenstein et al.; licensee BioMed Central Ltd.

【 图 表 】

【 参考文献 】

• [1]Bodenstein M, David M, Markstaller K: Principles of electrical impedance tomography and its clinical application. Crit Care Med 2009, 37:713-724.
• [2]Richard JC, Pouzot C, Gros A, Tourevieille C, Lebars D, Lavenne F, Frerichs I, Guerin C: Electrical impedance tomography compared to positron emission tomography for the measurement of regional lung ventilation: an experimental study. Crit Care 2009, 13:R82. BioMed Central Full Text
• [3]Hinz J, Neumann P, Dudykevych T, Andersson LG, Wrigge H, Burchardi H, Hedenstierna G: Regional ventilation by electrical impedance tomography: a comparison with ventilation scintigraphy in pigs. Chest 2003, 124:314-322.
• [4]Kunst PW, Vonk Noordegraaf A, Hoekstra OS, Postmus PE, de Vries PM: Ventilation and perfusion imaging by electrical impedance tomography: a comparison with radionuclide scanning. Physiol Meas 1998, 19:481-490.
• [5]Victorino JA, Borges JB, Okamoto VN, Matos GF, Tucci MR, Caramez MP, Tanaka H, Sipmann FS, Santos DC, Barbas CS, Carvalho CR, Amato MB: Imbalances in regional lung ventilation: a validation study on electrical impedance tomography. Am J Respir Crit Care Med 2004, 169:791-800.
• [6]Frerichs I, Hinz J, Herrmann P, Weisser G, Hahn G, Quintel M, Hellige G: Regional lung perfusion as determined by electrical impedance tomography in comparison with electron beam CT imaging. IEEE Trans Med Imag 2002, 21:646-652.
• [7]Hahn G, Sipinkova I, Baisch F, Hellige G: Changes in the thoracic impedance distribution under different ventilatory conditions. Physiol Meas 1995, 16:A161-A173.
• [8]Wrigge H, Zinserling J, Muders T, Varelmann D, Gunther U, von der Groeben C, Magnusson A, Hedenstierna G, Putensen C: Electrical impedance tomography compared with thoracic computed tomography during a slow inflation maneuver in experimental models of lung injury. Crit Care Med 2008, 36:903-909.
• [9]Frerichs I, Hahn G, Golisch W, Kurpitz M, Burchardi H, Hellige G: Monitoring perioperative changes in distribution of pulmonary ventilation by functional electrical impedance tomography. Acta Anaesthesiol Scand 1998, 42:721-726.
• [10]Zhao Z, Steinmann D, Frerichs I, Guttmann J, Moller K: PEEP titration guided by ventilation homogeneity: a feasibility study using electrical impedance tomography. Crit Care 2010, 14:R8. BioMed Central Full Text
• [11]Dargaville PA, Rimensberger PC, Frerichs I: Regional tidal ventilation and compliance during a stepwise vital capacity manoeuvre. Intensive Care Med 2010, 36(11):1953-1961.
• [12]Bodenstein M, Wang H, Boehme S, Vogt A, Kwiecien R, David M, Markstaller K: Influence of crystalloid and colloid fluid infusion and blood withdrawal on pulmonary bioimpedance in an animal model of mechanical ventilation. Physiol Meas 2012, 33:1225-1236.
• [13]Polak AG, Mroczka J: Nonlinear model for mechanical ventilation of human lungs. Comput Biol Med 2006, 36:41-58.
• [14]David M, Karmrodt J, Bletz C, David S, Herweling A, Kauczor HU, Markstaller K: Analysis of atelectasis, ventilated, and hyperinflated lung during mechanical ventilation by dynamic CT. Chest 2005, 128:3757-3770.
• [15]Markstaller K, Kauczor HU, Weiler N, Karmrodt J, Doebrich M, Ferrante M, Thelen M, Eberle B: Lung density distribution in dynamic CT correlates with oxygenation in ventilated pigs with lavage ARDS. Br J Anaesth 2003, 91:699-708.
• [16]Ferrario D, Grychtol B, Adler A, Sola J, Bohm SH, Bodenstein M: Toward Morphological Thoracic EIT: Major Signal Sources Correspond to Respective Organ Locations in CT. IEEE Trans Bio-Med Eng 2012, 59:3000-3008.
• [17]Grychtol B, Lionheart WR, Bodenstein M, Wolf GK, Adler A: Impact of model shape mismatch on reconstruction quality in electrical impedance tomography. IEEE Trans Med Imag 2012, 31:1754-1760.
• [18]Frerichs I, Bodenstein M, Dudykevych T, Hinz J, Hahn G, Hellige G: Effect of lower body negative pressure and gravity on regional lung ventilation determined by EIT. Physiol Meas 2005, 26:S27-S37.
• [19]Frerichs I, Dudykevych T, Hinz J, Bodenstein M, Hahn G, Hellige G: Gravity effects on regional lung ventilation determined by functional EIT during parabolic flights. J Appl Physiol 2001, 91:39-50.