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01.11.2010 | Original

Extrapolation from ten sections can make CT-based quantification of lung aeration more practicable

verfasst von: A. W. Reske, A. P. Reske, H. A. Gast, M. Seiwerts, A. Beda, U. Gottschaldt, C. Josten, D. Schreiter, N. Heller, H. Wrigge, M. B. Amato

Erschienen in: Intensive Care Medicine | Ausgabe 11/2010

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Abstract

Purpose

Clinical applications of quantitative computed tomography (qCT) in patients with pulmonary opacifications are hindered by the radiation exposure and by the arduous manual image processing. We hypothesized that extrapolation from only ten thoracic CT sections will provide reliable information on the aeration of the entire lung.

Methods

CTs of 72 patients with normal and 85 patients with opacified lungs were studied retrospectively. Volumes and masses of the lung and its differently aerated compartments were obtained from all CT sections. Then only the most cranial and caudal sections and a further eight evenly spaced sections between them were selected. The results from these ten sections were extrapolated to the entire lung. The agreement between both methods was assessed with Bland–Altman plots.

Results

Median (range) total lung volume and mass were 3,738 (1,311–6,768) ml and 957 (545–3,019) g, the corresponding bias (limits of agreement) were 26 (−42 to 95) ml and 8 (−21 to 38) g, respectively. The median volumes (range) of differently aerated compartments (percentage of total lung volume) were 1 (0–54)% for the nonaerated, 5 (1–44)% for the poorly aerated, 85 (28–98)% for the normally aerated, and 4 (0–48)% for the hyperaerated subvolume. The agreement between the extrapolated results and those from all CT sections was excellent. All bias values were below 1% of the total lung volume or mass, the limits of agreement never exceeded ±2%.

Conclusion

The extrapolation method can reduce radiation exposure and shorten the time required for qCT analysis of lung aeration.

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Coxson HO, Mayo J, Lam S, Santyr G, Parraga G, Sin DD (2009) New and current clinical imaging techniques to study chronic obstructive pulmonary disease. Am J Respir Crit Care Med 180:588–597CrossRefPubMed

Daly M, Miller PR, Carr JJ, Gayzik FS, Hoth JJ, Meredith JW, Stitzel JD (2008) Traumatic pulmonary pathology measured with computed tomography and a semiautomated analytic method. Clin Imaging 32:346–354CrossRefPubMed

Gattinoni L, Caironi P, Pelosi P, Goodman LR (2001) What has computed tomography taught us about the acute respiratory distress syndrome? Am J Respir Crit Care Med 164:1701–1711PubMed

Gattinoni L, Caironi P, Cressoni M, Chiumello D, Ranieri VM, Quintel M, Russo S, Patroniti N, Cornejo R, Bugedo G (2006) Lung recruitment in patients with the acute respiratory distress syndrome. N Engl J Med 354:1775–1786CrossRefPubMed

Caironi P, Cressoni M, Chiumello D, Ranieri M, Quintel M, Russo SG, Cornejo R, Bugedo G, Carlesso E, Russo R, Caspani L, Gattinoni L (2010) Lung opening and closing during ventilation of acute respiratory distress syndrome. Am J Respir Crit Care Med 181:578–586CrossRefPubMed

Sumikawa H, Johkoh T, Yamamoto S, Takahei K, Ueguchi T, Ogata Y, Matsumoto M, Fujita Y, Natsag J, Inoue A, Tsubamoto M, Mihara N, Honda O, Tomiyama N, Hamada S, Nakamura H (2006) Quantitative analysis for computed tomography findings of various diffuse lung diseases using volume histogram analysis. J Comput Assist Tomogr 30:244–249CrossRefPubMed

Madani A, Keyzer C, Gevenois PA (2004) Computed tomography assessment of lung structure and function in pulmonary emphysema. Eur Respir Mon 30:145–160CrossRef

Perez A 4th, Coxson HO, Hogg JC, Gibson K, Thompson PF, Rogers RM (2005) Use of CT morphometry to detect changes in lung weight and gas volume. Chest 128:2471–2477CrossRefPubMed

Washko GR, Martinez FJ, Hoffman EA, Loring SH, Estepar RS, Diaz A, Sciurba FC, Silverman EK, Han M, Decamp M, Reilly JJ, NETT Research Group (2010) Physiologic and computed tomographic predictors of outcome from lung volume reduction surgery. Am J Respir Crit Care Med 181:494–500CrossRefPubMed

10.

Patroniti N, Bellani G, Maggioni E, Manfio A, Marcora B, Pesenti A (2005) Measurement of pulmonary edema in patients with acute respiratory distress syndrome. Crit Care Med 33:2547–2554CrossRefPubMed

11.

Rouby JJ, Puybasset L, Nieszkowska A, Lu Q (2003) Acute respiratory distress syndrome: lessons from computed tomography of the whole lung. Crit Care Med 31(Suppl):S285–S295CrossRefPubMed

12.

Caironi P, Carlesso E, Gattinoni L (2006) Radiological imaging in acute lung injury and acute respiratory distress syndrome. Semin Respir Crit Care Med 27:404–415CrossRefPubMed

13.

Fernandez-Bustamante A, Easley RB, Fuld M, Mulreany D, Hoffman EA, Simon BA (2009) Regional aeration and perfusion distribution in a sheep model of endotoxemic acute lung injury characterized by functional computed tomography imaging. Crit Care Med 37:2402–2411CrossRefPubMed

14.

Malbouisson LM, Muller JC, Constantin JM, Lu Q, Puybasset L, Rouby JJ, CT Scan ARDS Study Group (2001) Computed tomography assessment of positive end-expiratory pressure-induced alveolar recruitment in patients with acute respiratory distress syndrome. Am J Respir Crit Care Med 163:1444–1450PubMed

15.

Borges JB, Okamoto VN, Matos GF, Caramez MP, Arantes PR, Barros F, Souza CE, Victorino JA, Kacmarek RM, Barbas CS, Carvalho CR, Amato MB (2006) Reversibility of lung collapse and hypoxemia in early acute respiratory distress syndrome. Am J Respir Crit Care Med 174:268–278CrossRefPubMed

16.

Terragni PP, Rosboch G, Tealdi A, Corno E, Menaldo E, Davini O, Gandini G, Herrmann P, Mascia L, Quintel M, Slutsky AS, Gattinoni L, Ranieri VM (2007) Tidal hyperinflation during low tidal volume ventilation in acute respiratory distress syndrome. Am J Respir Crit Care Med 175:160–166CrossRefPubMed

17.

Grasso S, Stripoli T, Sacchi M, Trerotoli P, Staffieri F, Franchini D, De Monte V, Valentini V, Pugliese P, Crovace A, Driessen B, Fiore T (2009) Inhomogeneity of lung parenchyma during the open lung strategy: a computed tomography scan study. Am J Respir Crit Care Med 180:415–423CrossRefPubMed

18.

Chiumello D, Cressoni M, Polli F, Cozzi P, Lazzerini M, Raimondi N, Fumagalli R, Radrizzani D, Gattinoni L (2006) Is it possible to reduce the exposition to ionizing radiation for lung computed tomography scan analysis? Crit Care 10(Suppl 1):P9CrossRef

19.

Reske AW, Hepp P, Heine C, Schmidt K, Seiwerts M, Gottschaldt U, Reske AP (2007) Analysis of the nonaerated lung volume in combinations of single computed tomography sections—is extrapolation to the entire lung feasible? Crit Care 11(Suppl 2):P206CrossRef

20.

Lu Q, Malbouisson LM, Mourgeon E, Goldstein I, Coriat P, Rouby JJ (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 27:1504–1510CrossRefPubMed

21.

Puybasset L, Cluzel P, Gusman P, Grenier P, Preteux F, Rouby JJ, CT Scan ARDS Study Group (2000) Regional distribution of gas and tissue in acute respiratory distress syndrome. I. Consequences for lung morphology. Intensive Care Med 26:857–869CrossRefPubMed

22.

Schreiter D, Reske A, Stichert B, Seiwerts M, Bohm SH, Kloeppel R, Josten C (2004) Alveolar recruitment in combination with sufficient positive end-expiratory pressure increases oxygenation and lung aeration in patients with severe chest trauma. Crit Care Med 32:968–975CrossRefPubMed

23.

Cornejo R, Diaz JC, Repetto C, Suarez P, Arellano D, Rouliez K, Diaz G, Romero C, Mezzano E, Riquelme AB, Ramos C (2009) Comparison of potentially recruitable lung (PRL) in supine versus prone position. Preliminary data. Intensive Care Med 35(Suppl 1):S126

24.

Rylander C, Högman M, Perchiazzi G, Magnusson A, Hedenstierna G (2004) Oleic acid lung injury: a morphometric analysis using computed tomography. Acta Anaesthesiol Scand 48:1123–1129CrossRefPubMed

25.

Wrigge H, Zinserling J, Neumann P, Muders T, Magnusson A, Putensen C, Hedenstierna G (2005) Spontaneous breathing with airway pressure release ventilation favors ventilation in dependent lung regions and counters cyclic alveolar collapse in oleic-acid-induced lung injury: a randomized controlled computed tomography trial. Crit Care 9:R780–R789CrossRefPubMed

26.

Simon BA (2000) Non-invasive imaging of regional lung function using X-ray computed tomography. J Clin Monit 16:433–442CrossRef

27.

Rylander C, Tylén U, Rossi-Norrlund R, Herrmann P, Quintel M, Bake B (2005) Uneven distribution of ventilation in acute respiratory distress syndrome. Crit Care 9:R165–R171CrossRefPubMed

28.

Reske AW, Gast HA, Seiwerts M, Kahn T, Gottschaldt U, Schreiter D, Josten C, Amato MBP, Reske AP (2009) Evaluation of a method to quicken the CT-based quantification of lung aeration for the entire lung. Intensive Care Med 35(Suppl 1):P302

29.

Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476):307–310PubMed

30.

Dewitte K, Fierens C, Stöckl D, Thienpont LM (2002) Application of the Bland–Altman plot for interpretation of method-comparison studies: a critical investigation of its practice. Clin Chem 48:799–801PubMed

31.

Madani A, De Maertelaer V, Zanen J, Gevenois PA (2007) Pulmonary emphysema: radiation dose and section thickness at multidetector CT quantification—comparison with macroscopic and microscopic morphometry. Radiology 243:250–257CrossRefPubMed

32.

Zaporozhan J, Ley S, Weinheimer O, Eberhardt R, Tsakiris I, Noshi Y, Herth F, Kauczor HU (2006) Multi-detector CT of the chest: influence of dose onto quantitative evaluation of severe emphysema: a simulation study. J Comput Assist Tomogr 30:460–468CrossRefPubMed

33.

Sluimer I, Schilham A, Prokop M, van Ginneken B (2006) Computer analysis of computed tomography scans of the lung: a survey. IEEE Trans Med Imaging 25:385–405CrossRefPubMed

34.

Ley-Zaporozhan J, Ley S, Unterhinninghofen R, Weinheimer O, Saito Y, Kauczor HU, Szabo G (2008) Quantification of lung volume at different tidal volumes and positive end-expiratory pressures in a porcine model by using retrospective respiratory gated 4D-computed tomography. Invest Radiol 43:461–469CrossRefPubMed

35.

Markstaller K, Arnold M, Döbrich M, Heitmann K, Karmrodt J, Weiler N, Uthmann T, Eberle B, Thelen M, Kauczor HU (2001) A software tool for automatic image-based ventilation analysis using dynamic chest CT-scanning in healthy and in ARDS lungs. Rofo 173:830–835PubMed

36.

David M, Karmrodt J, Bletz C, David S, Herweling A, Kauczor HU, Markstaller K (2005) Analysis of atelectasis, ventilated, and hyperinflated lung during mechanical ventilation by dynamic CT. Chest 128:3757–3770CrossRefPubMed

37.

Gattinoni L, Pelosi P, Vitale G, Pesenti A, D’Andrea L, Mascheroni D (1991) Body position changes redistribute lung computed-tomographic density in patients with acute respiratory failure. Anesthesiology 74:15–23CrossRefPubMed

38.

Gattinoni L, Pelosi P, Crotti S, Valenza F (1995) 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 151:1807–1814PubMed

39.

Zinserling J, Wrigge H, Neumann P, Muders T, Magnusson A, Hedenstierna G, Putensen C (2005) Methodologic aspects of attenuation distributions from static and dynamic thoracic CT techniques in experimental acute lung injury. Chest 128:2963–2970CrossRefPubMed

40.

Gattinoni L, Pesenti A, Bombino M, Baglioni S, Rivolta M, Rossi F, Rossi G, Fumagalli R, Marcolin R, Mascheroni D, Torresin A (1988) Relationships between lung computed tomographic density, gas exchange, and PEEP in acute respiratory failure. Anesthesiology 69:824–832CrossRefPubMed

41.

Hedenstierna G, Strandberg A, Brismar B, Lundquist H, Svensson L, Tokics L (1985) Functional residual capacity, thoraco-abdominal dimensions and central blood volume during general anesthesia with muscle paralysis and mechanical ventilation. Anesthesiology 62:247–254CrossRefPubMed

42.

Reske AW, Busse H, Amato MB, Jaekel M, Kahn T, Schwarzkopf P, Schreiter D, Gottschaldt U, Seiwerts M (2008) Image reconstruction affects computer tomographic assessment of lung hyperinflation. Intensive Care Med 34:2044–2053CrossRefPubMed

43.

Stolk J, Dirksen A, van der Lugt AA, Hutsebaut J, Mathieu J, de Ree J, Reiber JH, Stoel BC (2001) Repeatability of lung density measurements with low-dose computed tomography in subjects with alpha-1-antitrypsin deficiency-associated emphysema. Invest Radiol 36:648–651CrossRefPubMed

44.

Borges JB, Janot GF, Okamoto VN, Caramez MP, Barros F, Souza CE, Carvalho CRR, Amato MBP (2003) Is there a true cephalocaudal lung gradient in ARDS? Am J Respir Crit Care Med 167(Suppl):A740

45.

Vieira SR, Nieszkowska A, Lu Q, Elman M, Sartorius A, Rouby JJ (2005) Low spatial resolution computed tomography underestimates lung overinflation resulting from positive pressure ventilation. Crit Care Med 33:741–749CrossRefPubMed

46.

Wedegärtner U, Yamamura J, Nagel HD, Aldefeld D, Brinkmann C, Popovych S, Buchert R, Weber C, Adam G (2007) Image quality of thickened slabs in multislice CT chest examinations: postprocessing vs direct reconstruction. Rofo 179:373–379PubMed

Titel: Extrapolation from ten sections can make CT-based quantification of lung aeration more practicable
verfasst von: A. W. Reske
A. P. Reske
H. A. Gast
M. Seiwerts
A. Beda
U. Gottschaldt
C. Josten
D. Schreiter
N. Heller
H. Wrigge
M. B. Amato
Publikationsdatum: 01.11.2010
Verlag: Springer-Verlag
Erschienen in: Intensive Care Medicine / Ausgabe 11/2010
Print ISSN: 0342-4642
Elektronische ISSN: 1432-1238
DOI: https://doi.org/10.1007/s00134-010-2014-2

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Extrapolation from ten sections can make CT-based quantification of lung aeration more practicable