Respiration Therapy

  • Klaus Markstaller
Part of the Medical Radiology book series (MEDRAD)


Artificial ventilation is provided under circumstances in which a sufficient gas exchange cannot be secured by the patient’s own respiratory function. Artificial ventilation might be supportive or completely controlled by the respirator. Within the last few years a large variety of different respiratory modes have been established in critical care medicine, clinical anesthesia and pneumonology to offer optimal ventilatory support under any circumstances. The challenge of artificial ventilation increases dramatically when the lung itself is affected of the patient’s disease. In critical care medicine, the acute respiratory distress syndrome (ARDS) is one of the most important diseases which influence the outcome of these critically ill patients. ARDS represents a syndrome which is defined by an inhomogeneous distribution of ventilation and perfusion (V/P) followed by low oxygenation (oxygenation index, PaO2/FIO2 200) without cardiac dysfunction (wedge pressure 18 mmHg).


Acute Lung Injury Acute Respiratory Distress Syndrome Electrical Impedance Tomography Respir Crit Acute Respiratory Distress Syndrome Patient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Amato MB, Barbas CS et al. (1998) Effect of a protective-ventilation strategy on mortality in the acute respiratory distress syndrome. N Engl J Med 338:347–354PubMedCrossRefGoogle Scholar
  2. Barber DC (1989) A review of image reconstruction techniques for electrical impedance tomography. Med Phys 16:162–169PubMedCrossRefGoogle Scholar
  3. Baumgardner JE, Markstaller K et al. (2002) Effects of respiratory rate, plateau pressure, and positive end-expiratory pressure on PaO2 oscillations after saline lavage. Am J Respir Crit Care Med 166:1556–1562PubMedCrossRefGoogle Scholar
  4. Benumof J (1995) Anesthesia for thoracic surgery. Saunders, PhiladelphiaGoogle Scholar
  5. Bersten AD, Edibam C et al. (2002) Incidence and mortality of acute lung injury and the acute respiratory distress syndrome in three Australian States. Am J Respir Crit Care Med 165:443–448PubMedGoogle Scholar
  6. Brochard L (2001) Watching what PEEP really does. Am J Respir Crit Care Med 163:1291–1292PubMedGoogle Scholar
  7. Brunet F, Jeanbourquin D et al. (1995) Should mechanical ventilation be optimized to blood gases, lung mechanics, or thoracic CT scan? Am J Respir Crit Care Med 152:524–530PubMedGoogle Scholar
  8. Crotti S, Mascheroni D et al. (2001) Recruitment and derecruitment during acute respiratory failure: a clinical study. Am J Respir Crit Care Med 164:131–140PubMedGoogle Scholar
  9. Dambrosio M, Roupie E et al. (1997) Effects of positive end-expiratory pressure and different tidal volumes on alveolar recruitment and hyperinflation. Anesthesiology 87:495–503PubMedCrossRefGoogle Scholar
  10. De Durante G, Turco M del et al. (2002) ARDSNet lower tidal volume ventilatory strategy may generate intrinsic positive end-expiratory pressure in patients with acute respiratory distress syndrome. Am J Respir Crit Care Med 165:271–1274Google Scholar
  11. Dreyfuss D, Saumon G (1998) Ventilator-induced lung injury: lessons from experimental studies. Am J Respir Crit Care Med 157:294–323PubMedGoogle Scholar
  12. Dreyfuss D, Saumon G (2001) Pressure-volume curves: searching for the Grail or laying patients with adult respiratory distress syndrome on Procrustes’ bed? Am J Respir Crit Care Med 163:2–3PubMedGoogle Scholar
  13. Esteban A, Anzueto A et al. (2002) Characteristics and outcomes in adult patients receiving mechanical ventilation: a 28-day international study. JAMA 287:345–355PubMedCrossRefGoogle Scholar
  14. Frerichs I (2000) Electrical impedance tomography (EIT) in applications related to lung and ventilation: a review of experimental and clinical activities. Physiol Meas 2121: Rl-21CrossRefGoogle Scholar
  15. Frerichs I, Hahn G et al. (1996) Gravity-dependent phenomena in lung ventilation determined by functional EIT. Physiol Meas 17[Suppl 4A]:A149–A157PubMedCrossRefGoogle Scholar
  16. Frerichs I, Schiffmann H et al. (2001) Non-invasive radiation-free monitoring of regional lung ventilation in critically ill infants. Intensive Care Med 27:1385–1394PubMedCrossRefGoogle Scholar
  17. Frerichs I, Hinz J et al. (2002) Detection of local lung air content by electrical impedance tomography compared with electron beam CT. J Appl Physiol 93:660–666PubMedGoogle Scholar
  18. Gattinoni L, Mascheroni D et al. (1986a) Morphological response to positive end expiratory pressure in acute respiratory failure. Computerized tomography study. Intensive Care Med 12:137–142Google Scholar
  19. Gattinoni L, Presenti A et al. (1986b) Adult respiratory distress syndrome profiles by computed tomography. J Thorac Imaging 1:25–30PubMedCrossRefGoogle Scholar
  20. Gattinoni L, Bombino M et al. (1994) Lung structure and function in different stages of severe adult respiratory distress syndrome. JAMA 271:1772–1779PubMedCrossRefGoogle Scholar
  21. Gattinoni L, Caironi P et al. (2001) What has computed tomography taught us about the acute respiratory distress syndrome? Am J Respir Crit Care Med 164:1701–1711PubMedGoogle Scholar
  22. Hahn G, Sipinkova I et al. (1995) Changes in the thoracic impedance distribution under different ventilatory conditions. Physiol Meas 16[Suppl A]:A161–A173PubMedCrossRefGoogle Scholar
  23. Hahn G, Frerichs I et al. (1996) Local mechanics of the lung tissue determined by functional EIT. Physiol Meas 17[Suppl 4A]:A159–A166PubMedCrossRefGoogle Scholar
  24. Harris RS, Hess DR et al. (2000) An objective analysis of the pressure-volume curve in the acute respiratory distress syndrome. Am J Respir Crit Care Med 161:432–439PubMedGoogle Scholar
  25. Heussel CP, Hafner B et al. (2001) Paired inspiratory/expiratory spiral CT and continuous respiration cine CT in the diagnosis of tracheal instability. Eur Radiol 11:982–989PubMedCrossRefGoogle Scholar
  26. Hickling KG (2001) Best compliance during a decrementai, but not incremental, positive end-expiratory pressure trial is related to open-lung positive end-expiratory pressure: a mathematical model of acute respiratory distress syndrome lungs. Am J Respir Crit Care Med 163:69–78PubMedGoogle Scholar
  27. Hubmayr RD (2002) Perspective on lung injury and recruitment. A skeptical look at the Opening and Collapse Story. Am J Respir Crit Care Med 165:1647–1653CrossRefGoogle Scholar
  28. International Consensus Conferences in Intensive Care Medicine (1999) Ventilator-associated lung injury in ARDS. American Thoracic Society, European Society of Intensive Care Medicine, Societe de Reanimation Langue Francaise. Intensive Care Med 25:1444–1452CrossRefGoogle Scholar
  29. Karmrodt J, Markstaller K et al. (2002) Determination of different coexisting pulmonary time constants in human ARDS by dynamic CT. Intensive Care Med 28:S141Google Scholar
  30. Kunst PW, Vonk Noordegraaf A et al. (1998) Influences of lung parenchyma density and thoracic fluid on ventilatory EIT measurements. Physiol Meas 19:27–34PubMedCrossRefGoogle Scholar
  31. Kunst PW, Bohm SH et al. (2000a) Regional pressure volume curves by electrical impedance tomography in a model of acute lung injury. Crit Care Med 28:178–183PubMedCrossRefGoogle Scholar
  32. Kunst PW, Vazquez de Anda G et al. (2000b) Monitoring of recruitment and derecruitment by electrical impedance tomography in a model of acute lung injury. Crit Care Med 28:3891–3895PubMedCrossRefGoogle Scholar
  33. Lu Q, Malbouisson LM et al. (2001) Assessment of PEEP-induced reopening of collapsed lung regions in acute lung injury: are one or three CT sections representative of the entire lung? Intensive Care Med 27:1504–1510PubMedCrossRefGoogle Scholar
  34. Lumb A (2000) Nunn’s applied respiratory physiology. Butterworth Heinemann, OxfordGoogle Scholar
  35. Markstaller K, Kauczor HU et al. (1999) Multi-rotation CT during continuous ventilation: comparison of different density areas in healthy lungs and in the ARDS lavage model. Rofo Fortschr Geb Rontgenstr Neuen Bildgeb Verfahr 170:575–80PubMedCrossRefGoogle Scholar
  36. Markstaller K, Arnold M et al. (2001a) A software tool for automatic image-based ventilation analysis using dynamic chest CT-scanning in healthy and in ARDS lungs. Rofo Fortschr Geb Rontgenstr Neuen Bildgeb Verfahr 173: 830–835PubMedCrossRefGoogle Scholar
  37. Markstaller K, Eberle B et al. (2001b) Temporal dynamics of lung aeration determined by dynamic CT in a porcine model of ARDS. Br J Anaesth 87:459–468PubMedCrossRefGoogle Scholar
  38. Markstaller K, Kauczor HU et al. (2003) Lung density distribution in dynamic CT correlates with oxygenation in ventilated pigs with lavage ARDS. Br J Anaesth in pressGoogle Scholar
  39. Maunder RJ, Shuman WP et al. (1986) Preservation of normal lung regions in the adult respiratory distress syndrome. Analysis by computed tomography. JAMA 255:2463–2465PubMedCrossRefGoogle Scholar
  40. Mull RT (1984) Mass estimates by computed tomography: physical density from CT numbers. AJR Am J Roentgenol 143:1101–1104PubMedGoogle Scholar
  41. Neumann P, Berglund JE et al. (1998a) Dynamics of lung collapse and recruitment during prolonged breathing in porcine lung injury. J Appl Physiol 85:1533–1543PubMedGoogle Scholar
  42. Neumann P, Berglund JE et al. (1998b) Effect of different pressure levels on the dynamics of lung collapse and recruitment in oleic acid-induced lung injury. Am J Respir Crit Care Med 158:1636–1643PubMedGoogle Scholar
  43. Pelosi P, Goldner M et al. (2001) Recruitment and derecruitment during acute respiratory failure: an experimental study. Am J Respir Crit Care Med 164:122–130PubMedGoogle Scholar
  44. Puybasset L, Cluzel P et al. (2000) Regional distribution of gas and tissue in acute respiratory distress syndrome. I. Consequences for lung morphology. CT Scan ARDS Study Group. Intensive Care Med 26:857–869PubMedCrossRefGoogle Scholar
  45. Rommelsheim K, Lackner K et al. (1983) Respiratory distress syndrome of the adult in the computer tomograph. Anasthesiol Intensivther Notfallmed 18:59–64CrossRefGoogle Scholar
  46. Rothen HU, Neumann P et al. (1999) Dynamics of re-expansion of atelectasis during general anaesthesia. Br J Anaesth 82:551–556PubMedCrossRefGoogle Scholar
  47. Rouby JJ, Puybasset L et al. (2003) Acute respiratory distress syndrome: lessons from computed tomography of the whole lung. Crit Care Med 3131 [Suppl]:S285-S295CrossRefGoogle Scholar
  48. Slutsky AS, Ranieri VM (2000) Mechanical ventilation: lessons from the ARDSNet trial. Respir Res 1:73–77PubMedCrossRefGoogle Scholar
  49. Tagliabue M, Casella TC et al. (1994) CT and chest radiography in the evaluation of adult respiratory distress syndrome. Acta Radiol 35:230–234PubMedGoogle Scholar
  50. Tagliabue P, Giannatelli F et al. (1998) Lung CT scan in ARDS: are three sections representative of the entire lung? Intensive Care Med 24[Suppl 1]:93Google Scholar
  51. The Acute Respiratory Distress Syndrome Network (2000) Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. N Engl J Med 342: 1301–1308CrossRefGoogle Scholar
  52. Tokics L, Hedenstierna G et al. (1987) Lung collapse and gas exchange during general anesthesia: effects of spontaneous breathing, muscle paralysis, and positive end-expiratory pressure. Anesthesiology 66:157–167PubMedCrossRefGoogle Scholar
  53. Tokics L, Hedenstierna G et al. (1996) V/Q distribution and correlation to atelectasis in anesthetized paralyzed humans. J Appl Physiol 81:1822–1833PubMedGoogle Scholar
  54. Vieira SR, Puybasset L et al. (1998) A lung computed tomographic assessment of positive end-expiratory pressure-induced lung overdistension. Am J Respir Crit Care Med 158:1571–1577PubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Klaus Markstaller
    • 1
  1. 1.Department of AnesthesiologyJohannes Gutenberg University Medical SchoolMainzGermany

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