Quantitative CT Indexes in Idiopathic Pulmonary Fibrosis: Relationship with Physiologic Impairment

PURPOSE: To determine whether measurements of skewness, kurtosis, and mean lung attenuation on thin-section computed tomographic (CT) histograms in patients with idiopathic pulmonary fibrosis (IPF) correlate with pulmonary physiologic abnormality in a nonspirometrically controlled multicenter study.

MATERIALS AND METHODS: The authors analyzed baseline digital thin-section CT data from 144 patients with IPF who enrolled in a double-blind placebo-controlled clinical effectiveness trial of interferon beta 1a in the treatment of IPF. All patients underwent thin-section CT in the supine position at full inspiration. The lungs were isolated by using a semiautomated thresholding technique, with an upper threshold of −200 HU. An attenuation correction algorithm was used. Pulmonary function tests (PFTs) included forced vital capacity, total lung capacity, forced expiratory volume in 1 second, and diffusing lung capacity. Univariate and multiple correlation and regression statistical analyses were used to determine relationships between histogram features and results of PFTs.

RESULTS: Moderate correlations existed between histogram features and PFT results. Kurtosis showed the greatest degree of correlation with physiologic abnormality (r = 0.53, P < .01). Strength of correlation increased with exclusion of suboptimal scans but did not change significantly after application of an attenuation correction algorithm. Attenuations for lungs, gas, and soft tissue varied considerably between scanner manufacturers. Kurtosis alone provided predictions of pulmonary function that were virtually as good as those from all histogram features combined.

CONCLUSION: Thin-section CT histograms of the lungs were found to correlate with results of PFTs in patients with IPF, which supports the claim that histogram features can be used as valid indexes of IPF in a multiinstitutional nonspirometrically controlled study.

© RSNA, 2003

References

  • 1 Hartley PG, Galvin JR, Hunninghake GW, et al. High-resolution CT-derived measures of lung density are valid indexes of interstitial lung disease. J Appl Physiol 1994; 76:271-277. Crossref, MedlineGoogle Scholar
  • 2 Lynch DA, Gamsu G. Imaging of diffuse parenchymal lung diseases. In: Schwarz MI, King TE, eds. Interstitial lung disease. 3rd ed. Hamilton, Ontario, Canada: Decker, 1998; 95-96. Google Scholar
  • 3 Behr J, Mehnert F, Beinert T, et al. Evaluation of interstitial lung disease by quantitative high-resolution computed tomography. Am Rev Respir Dis 1992; 145(suppl):A191. Google Scholar
  • 4 Uppaluri R, Mitsa T, Sonka M, Hoffman EA, McLennan G. Quantification of pulmonary emphysema from lung computed tomography images. Am J Respir Crit Care Med 1997; 156:248-254. Crossref, MedlineGoogle Scholar
  • 5 American Thoracic Society. Idiopathic pulmonary fibrosis: diagnosis and treatment. International consensus statement. American Thoracic Society (ATS) and the European Respiratory Society (ERS). Am J Respir Crit Care Med 2000; 161(2 pt 1):646-664. Google Scholar
  • 6 Crapo RO, Morris AH, Clayton PD, Nixon CR. Lung volumes in healthy nonsmoking adults. Bull Eur Physiopathol Respir 1982; 18:419-425. MedlineGoogle Scholar
  • 7 Crapo RO, Morris AH. Standardized single breath normal values for carbon monoxide diffusing capacity. Am Rev Respir Dis 1981; 123:185-189. MedlineGoogle Scholar
  • 8 Goldman HL, Becklake MR. Respiratory function tests: normal values at median altitude and the prediction of normal results. Am Rev Thorac Pulm Dis 1969; 79:457-467. Google Scholar
  • 9 Coxson HO, Hogg JC, Mayo JR, et al. Quantification of idiopathic pulmonary fibrosis using computed tomography and histology. Am J Respir Crit Care Med 1997; 155:1649-1656. Crossref, MedlineGoogle Scholar
  • 10 Kalender WA, Fichte H, Bautz W, Skalej M. Semiautomatic evaluation procedures for quantitative CT of the lung. J Comput Assist Tomogr 1991; 15:248-255. Crossref, MedlineGoogle Scholar
  • 11 Rienmuller RK, Behr J, Kalender WA, et al. Standardized quantitative high resolution CT in lung disease. J Comput Assist Tomogr 1991; 15:742-749. Crossref, MedlineGoogle Scholar
  • 12 Beinert T, Behr J, Mehnert F, et al. Spirometrically controlled quantitative CT for assessing diffuse parenchymal lung disease. J Comput Assist Tomogr 1995; 19:924-931. Crossref, MedlineGoogle Scholar
  • 13 Kauczor HU, Heussel CP, Fischer B, et al. Assessment of lung volumes using helical CT at inspiration and expiration: comparison with pulmonary function tests. AJR Am J Roentgenol 1998; 171:1091-1095. Crossref, MedlineGoogle Scholar
  • 14 Rodriguez LH, Vargas PF, Raff U, et al. Automated discrimination and quantification of idiopathic pulmonary fibrosis from normal lung parenchyma using generalized fractal dimensions in high-resolution computed tomography images. Acad Radiol 1995; 2:10-18. Crossref, MedlineGoogle Scholar
  • 15 Uppaluri R, Hoffman EA, Sonka M, et al. Interstitial lung disease: a quantitative study using the adaptive multiple feature method. Am J Respir Crit Care Med 1999; 159:519-525. Crossref, MedlineGoogle Scholar

Article History

Published in print: Aug 2003