Real-time effects of PEEP and tidal volume on regional ventilation and perfusion in experimental lung injury

João Batista Borges, John N Cronin, Douglas C Crockett, Göran Hedenstierna, Anders Larsson, Federico Formenti, João Batista Borges, John N Cronin, Douglas C Crockett, Göran Hedenstierna, Anders Larsson, Federico Formenti

Abstract

Background: Real-time bedside information on regional ventilation and perfusion during mechanical ventilation (MV) may help to elucidate the physiological and pathophysiological effects of MV settings in healthy and injured lungs. We aimed to study the effects of positive end-expiratory pressure (PEEP) and tidal volume (VT) on the distributions of regional ventilation and perfusion by electrical impedance tomography (EIT) in healthy and injured lungs.

Methods: One-hit acute lung injury model was established in 6 piglets by repeated lung lavages (injured group). Four ventilated piglets served as the control group. A randomized sequence of any possible combination of three VT (7, 10, and 15 ml/kg) and four levels of PEEP (5, 8, 10, and 12 cmH2O) was performed in all animals. Ventilation and perfusion distributions were computed by EIT within three regions-of-interest (ROIs): nondependent, middle, dependent. A mixed design with one between-subjects factor (group: intervention or control), and two within-subjects factors (PEEP and VT) was used, with a three-way mixed analysis of variance (ANOVA).

Results: Two-way interactions between PEEP and group, and VT and group, were observed for the dependent ROI (p = 0.035 and 0.012, respectively), indicating that the increase in the dependent ROI ventilation was greater at higher PEEP and VT in the injured group than in the control group. A two-way interaction between PEEP and VT was observed for perfusion distribution in each ROI: nondependent (p = 0.030), middle (p = 0.006), and dependent (p = 0.001); no interaction was observed between injured and control groups.

Conclusions: Large PEEP and VT levels were associated with greater pulmonary ventilation of the dependent lung region in experimental lung injury, whereas they affected pulmonary perfusion of all lung regions both in the control and in the experimental lung injury groups.

Keywords: Electrical impedance tomography; Mechanical ventilation; Pulmonary circulation; Respiratory distress syndrome, Adult; Ventilation-perfusion ratio.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Representative image of regional distribution of pulmonary ventilation as recorded by electrical impedance tomography (EIT) in one piglet from the control group. Three regions-of-interest (ROIs) of the same vertical height were constructed from top (anterior) to bottom (posterior) of the lung: nondependent, middle, and dependent ROI. In this ventilation map, lighter blue indicates greater ventilation than darker blue, with white representing the greatest ventilation. A = anterior; P = posterior; L = left; R = right
Fig. 2
Fig. 2
Arterial partial pressure of O2 and fraction of inspired oxygen ratio (PaO2/FIO2; a), mean airway pressure (b), and cardiac output (c) in the control (left, n = 4) and injured (right, n = 6) groups. PEEP = positive end-expiratory pressure. VT = tidal volume
Fig. 3
Fig. 3
Representative images of regional distribution of pulmonary ventilation (a) and perfusion (b) at two different PEEP and VT levels as recorded by electrical impedance tomography (EIT) in one piglet from the injured group. In the ventilation maps (a), lighter blue indicates greater ventilation than darker blue, with white representing the greatest ventilation. Similarly, in the perfusion maps (b), the lighter red indicates greater perfusion than darker red, with yellow indicating the greatest perfusion. The dotted line in the perfusion maps shows the contour of the corresponding ventilation map (i. e., the corresponding pulmonary ventilation area studied at the same point in time, hence under the same mechanical ventilation settings). PEEP = positive end-expiratory pressure. VT = tidal volume. A = anterior; P = posterior; L = left; R = right (all images)
Fig. 4
Fig. 4
Regional distribution of pulmonary ventilation in the control (left, n = 4) and injured (right, n = 6) groups. Larger PEEP levels were associated with greater percent increase in the ventilation of the dependent lung in the injured group than in the control group. Similarly, larger VT was associated with a greater percent increase in dependent lung ventilation in the injured group than in the control group. * indicates greater percent increase in the ventilation of the dependent lung region with larger PEEP in the injured than in the control group; † indicates greater percent increase in the ventilation of the dependent lung region with larger VT in the injured than in the control group. PEEP = positive end-expiratory pressure. VT = tidal volume
Fig. 5
Fig. 5
Regional distribution of pulmonary perfusion in the control (left, n = 4) and injured (right, n = 6) groups. Both larger PEEP and larger VT determined a significant perfusion change in each of the ROIs considered: nondependent (p = 0.030), middle (p = 0.006), and dependent (p = 0.001). PEEP = positive end-expiratory pressure. VT = tidal volume

References

    1. Retamal J, Hurtado D, Villarroel N, Bruhn A, Bugedo G, Amato MBP, Costa ELV, Hedenstierna G, Larsson A, Borges JB. Does regional lung strain correlate with regional inflammation in acute respiratory distress syndrome during nonprotective ventilation? An Experimental Porcine Study. Crit Care Med. 2018;46:e591–e599. doi: 10.1097/CCM.0000000000003072.
    1. Gattinoni L, Pelosi P, Crotti S, Valenza F. Effects of positive end-expiratory pressure on regional distribution of tidal volume and recruitment in adult respiratory distress syndrome. Am J Respir Crit Care Med. 1995;151:1807–1814. doi: 10.1164/ajrccm.151.6.7767524.
    1. Frerichs I, Amato MB, van Kaam AH, Tingay DG, Zhao Z, Grychtol B, Bodenstein M, Gagnon H, Bohm SH, Teschner E, Stenqvist O, Mauri T, Torsani V, Camporota L, Schibler A, Wolf GK, Gommers D, Leonhardt S, Adler A, group Ts Chest electrical impedance tomography examination, data analysis, terminology, clinical use and recommendations: consensus statement of the TRanslational EIT developmeNt stuDy group. Thorax. 2017;72:83–93. doi: 10.1136/thoraxjnl-2016-208357.
    1. Costa EL, Lima RG, Amato MB. Electrical impedance tomography. Curr Opin Crit Care. 2009;15:18–24. doi: 10.1097/MCC.0b013e3283220e8c.
    1. Blankman P, Hasan D, van Mourik MS, Gommers D. Ventilation distribution measured with EIT at varying levels of pressure support and Neurally Adjusted Ventilatory Assist in patients with ALI. Intensive Care Med. 2013;39:1057–1062. doi: 10.1007/s00134-013-2898-8.
    1. Morais CCA, Koyama Y, Yoshida T, Plens GM, Gomes S, Lima CAS, Ramos OPS, Pereira SM, Kawaguchi N, Yamamoto H, Uchiyama A, Borges JB, Vidal Melo MF, Tucci MR, Amato MBP, Kavanagh BP, Costa ELV, Fujino Y. High positive end-expiratory pressure renders spontaneous effort noninjurious. Am J Respir Crit Care Med. 2018;197:1285–1296. doi: 10.1164/rccm.201706-1244OC.
    1. Yoshida T, Fujino Y, Amato MB, Kavanagh BP. Fifty years of research in ARDS. Spontaneous Breathing during Mechanical Ventilation. Risks, Mechanisms, and Management. Am J Respir Crit Care Med. 2017;195:985–992. doi: 10.1164/rccm.201604-0748CP.
    1. Yoshida T, Nakahashi S, Nakamura MAM, Koyama Y, Roldan R, Torsani V, De Santis RR, Gomes S, Uchiyama A, Amato MBP, Kavanagh BP, Fujino Y. Volume-controlled ventilation does not prevent injurious inflation during spontaneous effort. Am J Respir Crit Care Med. 2017;196:590–601. doi: 10.1164/rccm.201610-1972OC.
    1. Yoshida T, Torsani V, Gomes S, De Santis RR, Beraldo MA, Costa EL, Tucci MR, Zin WA, Kavanagh BP, Amato MB. Spontaneous effort causes occult pendelluft during mechanical ventilation. Am J Respir Crit Care Med. 2013;188:1420–1427. doi: 10.1164/rccm.201303-0539OC.
    1. Yoshida T, Uchiyama A, Matsuura N, Mashimo T, Fujino Y. Spontaneous breathing during lung-protective ventilation in an experimental acute lung injury model: high transpulmonary pressure associated with strong spontaneous breathing effort may worsen lung injury. Crit Care Med. 2012;40:1578–1585. doi: 10.1097/CCM.0b013e3182451c40.
    1. Bachmann MC, Morais C, Bugedo G, Bruhn A, Morales A, Borges JB, Costa E, Retamal J. Electrical impedance tomography in acute respiratory distress syndrome. Crit Care. 2018;22:263. doi: 10.1186/s13054-018-2195-6.
    1. 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. doi: 10.1111/j.1399-6576.1998.tb05308.x.
    1. Borges João Batista, Suarez-Sipmann Fernando, Bohm Stephan H., Tusman Gerardo, Melo Alexandre, Maripuu Enn, Sandström Mattias, Park Marcelo, Costa Eduardo L. V., Hedenstierna Göran, Amato Marcelo. Regional lung perfusion estimated by electrical impedance tomography in a piglet model of lung collapse. Journal of Applied Physiology. 2012;112(1):225–236. doi: 10.1152/japplphysiol.01090.2010.
    1. Costa EL, Borges JB, Melo A, Suarez-Sipmann F, Toufen C, Jr, Bohm SH, Amato MB. Bedside estimation of recruitable alveolar collapse and hyperdistension by electrical impedance tomography. Intensive Care Med. 2009;35:1132–1137. doi: 10.1007/s00134-009-1447-y.
    1. 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. doi: 10.1164/rccm.200301-133OC.
    1. 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 Imaging. 2002;21:646–652. doi: 10.1109/TMI.2002.800585.
    1. Meier P, Zierler KL. On the theory of the indicator-dilution method for measurement of blood flow and volume. J Appl Physiol. 1954;6:731–744. doi: 10.1152/jappl.1954.6.12.731.
    1. Thompson HK, Jr, Starmer CF, Whalen RE, McIntosh HD. Indicator Transit Time Considered as a Gamma Variate. Circ Res. 1964;14:502–515. doi: 10.1161/01.RES.14.6.502.
    1. Borges JB, Okamoto VN, Matos GF, Caramez MP, Arantes PR, Barros F, Souza CE, Victorino JA, Kacmarek RM, Barbas CS, Carvalho CR, Amato MB. Reversibility of lung collapse and hypoxemia in early acute respiratory distress syndrome. Am J Respir Crit Care Med. 2006;174:268–278. doi: 10.1164/rccm.200506-976OC.
    1. Glenny R, Robertson HT. Distribution of perfusion. Compreh Physiol. 2011;1:245–262.
    1. Glenny RW, Polissar L, Robertson HT. Relative contribution of gravity to pulmonary perfusion heterogeneity. J Appl Physiol (1985) 1991;71:2449–2452. doi: 10.1152/jappl.1991.71.6.2449.
    1. Cronin JN, Crockett DC, Farmery AD, Hedenstierna G, Larsson A, Camporota L, Formenti F. Mechanical ventilation redistributes blood to poorly ventilated areas in experimental lung injury. Crit Care Med. 2020;48:e200–e208. doi: 10.1097/CCM.0000000000004141.
    1. Musch G, Bellani G, Vidal Melo MF, Harris RS, Winkler T, Schroeder T, Venegas JG. Relation between shunt, aeration, and perfusion in experimental acute lung injury. Am J Respir Crit Care Med. 2008;177:292–300. doi: 10.1164/rccm.200703-484OC.
    1. Hedenstierna G. Pulmonary perfusion during anesthesia and mechanical ventilation. Minerva Anestesiol. 2005;71:319–324.
    1. Formenti F, Bommakanti N, Chen R, Cronin JN, McPeak H, Holopherne-Doran D, Hedenstierna G, Hahn CEW, Larsson A, Farmery AD. Respiratory oscillations in alveolar oxygen tension measured in arterial blood. Sci Rep. 2017;7:7499. doi: 10.1038/s41598-017-06975-6.
    1. Formenti F, Chen R, McPeak H, Murison PJ, Matejovic M, Hahn CE, Farmery AD. Intra-breath arterial oxygen oscillations detected by a fast oxygen sensor in an animal model of acute respiratory distress syndrome. Br J Anaesth. 2015;114:683–688. doi: 10.1093/bja/aeu407.
    1. Crockett DC, Cronin JN, Bommakanti N, Chen R, Hahn CEW, Hedenstierna G, Larsson A, Farmery AD, Formenti F. Tidal changes in PaO2 and their relationship to cyclical lung recruitment/derecruitment in a porcine lung injury model. Br J Anaesth. 2019;122:277–285. doi: 10.1016/j.bja.2018.09.011.
    1. Permutt S, Howell JB, Proctor DF, Riley RL. Effect of lung inflation on static pressure-volume characteristics of pulmonary vessels. J Appl Physiol. 1961;16:64–70. doi: 10.1152/jappl.1961.16.1.64.
    1. Hedenstierna G, White FC, Mazzone R, Wagner PD. Redistribution of pulmonary blood flow in the dog with PEEP ventilation. J Appl Physiol Respir Environ Exerc Physiol. 1979;46:278–287.
    1. Moudgil R, Michelakis ED, Archer SL. Hypoxic pulmonary vasoconstriction. J Appl Physiol (1985) 2005;98:390–403. doi: 10.1152/japplphysiol.00733.2004.
    1. Benumof JL. Mechanism of decreased blood flow to atelectatic lung. J Appl Physiol Respir Environ Exerc Physiol. 1979;46:1047–1048.
    1. Lachmann B, Robertson B, Vogel J. In vivo lung lavage as an experimental model of the respiratory distress syndrome. Acta Anaesthesiol Scand. 1980;24:231–236. doi: 10.1111/j.1399-6576.1980.tb01541.x.
    1. Matute-Bello G, Frevert CW, Martin TR. Animal models of acute lung injury. Am J Physiol Lung Cell Mol Physiol. 2008;295:L379–L399. doi: 10.1152/ajplung.00010.2008.
    1. Petty TL, Reiss OK, Paul GW, Silvers GW, Elkins ND. Characteristics of pulmonary surfactant in adult respiratory distress syndrome associated with trauma and shock. Am Rev Respir Dis. 1977;115:531–536.
    1. Brown BH, Leathard A, Sinton A, McArdle FJ, Smith RW, Barber DC. Blood flow imaging using electrical impedance tomography. Clin Phys Physiol Meas. 1992;13(Suppl A):175–179. doi: 10.1088/0143-0815/13/A/034.
    1. Trautman ED, Newbower RS. A practical analysis of the electrical conductivity of blood. IEEE Trans Biomed Eng. 1983;30:141–154. doi: 10.1109/TBME.1983.325098.
    1. Cronin JN, Borges JB, Crockett DC, Farmery AD, Hedenstierna G, Larsson A, Tran MC, Camporota L, Formenti F. Dynamic single-slice CT estimates whole-lung dual-energy CT variables in pigs with and without experimental lung injury. Intensive Care Med Exp. 2019;7:59. doi: 10.1186/s40635-019-0273-y.

Source: PubMed

Sponsorit ja yhteistyökumppanit

Sairaudet

Huumeiden interventiot

3
Tilaa