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Accuracy of low-dose computed tomography (CT) for detecting and characterizing the most common CT-patterns of pulmonary disease.

Publication ,  Journal Article
Christe, A; Charimo-Torrente, J; Roychoudhury, K; Vock, P; Roos, JE
Published in: Eur J Radiol
March 2013

PURPOSE: To assess the ability of low-dose CT to detect and characterize the most common CT patterns of pulmonary disease. METHODS AND MATERIALS: Sixty patients with nodules, consolidations or interstitial disease were scanned using a low-dose (128 mm × 0.6 mm, 40 reference mAs, 120 kVp) and standard-dose CT protocol (150 reference mAs, 120 kVp). Two radiologists with 3 and 10 years of thoracic imaging experience searched both exams in consensus for the most commonly observed CT patterns according to the Fleischner Society criteria, which consisted of 46 different subgroups of ground-glass opacities, nodules, interstitial and airspace diseases. The standard of reference was established by consensus of a panel of two experienced chest radiologists (9 and 12 years of experience). RESULTS: The lung segments (1080) showed 813 nodules, 596 ground-glass opacities, 74 airspace and 575 interstitial diseases and 64 normal segments. In particular, air-space disease and nodules were unaffected by the increase in noise. However, the sensitivity to detect ground-glass opacities, ground-glass nodules and interstitial opacities decreased significantly, from 89% to 77%, 86% to 68% and 91% to 71%, respectively (all p-values <0.00001). Using iterative reconstruction instead of the applied filtered back projection sensitivity for ground-glass nodules rose to the sensitivity of standard-dose CT in an additional phantom study. CONCLUSION: A low-dose CT of 40 mAs/120 kVp is feasible for detecting solid nodules, airspace, airways and pleural disease. For diagnosing pathologies consisting of ground-glass opacities or interstitial opacities, higher tube current or iterative reconstruction is required.

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Published In

Eur J Radiol

DOI

EISSN

1872-7727

Publication Date

March 2013

Volume

82

Issue

3

Start / End Page

e142 / e150

Location

Ireland

Related Subject Headings

  • Tomography, X-Ray Computed
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiography, Thoracic
  • Radiation Protection
  • Radiation Dosage
  • Observer Variation
  • Nuclear Medicine & Medical Imaging
  • Middle Aged
  • Male
 

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Christe, A., Charimo-Torrente, J., Roychoudhury, K., Vock, P., & Roos, J. E. (2013). Accuracy of low-dose computed tomography (CT) for detecting and characterizing the most common CT-patterns of pulmonary disease. Eur J Radiol, 82(3), e142–e150. https://doi.org/10.1016/j.ejrad.2012.09.025
Christe, Andreas, Jaled Charimo-Torrente, Kingshuk Roychoudhury, Peter Vock, and Justus E. Roos. “Accuracy of low-dose computed tomography (CT) for detecting and characterizing the most common CT-patterns of pulmonary disease.Eur J Radiol 82, no. 3 (March 2013): e142–50. https://doi.org/10.1016/j.ejrad.2012.09.025.
Christe A, Charimo-Torrente J, Roychoudhury K, Vock P, Roos JE. Accuracy of low-dose computed tomography (CT) for detecting and characterizing the most common CT-patterns of pulmonary disease. Eur J Radiol. 2013 Mar;82(3):e142–50.
Christe, Andreas, et al. “Accuracy of low-dose computed tomography (CT) for detecting and characterizing the most common CT-patterns of pulmonary disease.Eur J Radiol, vol. 82, no. 3, Mar. 2013, pp. e142–50. Pubmed, doi:10.1016/j.ejrad.2012.09.025.
Christe A, Charimo-Torrente J, Roychoudhury K, Vock P, Roos JE. Accuracy of low-dose computed tomography (CT) for detecting and characterizing the most common CT-patterns of pulmonary disease. Eur J Radiol. 2013 Mar;82(3):e142–e150.
Journal cover image

Published In

Eur J Radiol

DOI

EISSN

1872-7727

Publication Date

March 2013

Volume

82

Issue

3

Start / End Page

e142 / e150

Location

Ireland

Related Subject Headings

  • Tomography, X-Ray Computed
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiography, Thoracic
  • Radiation Protection
  • Radiation Dosage
  • Observer Variation
  • Nuclear Medicine & Medical Imaging
  • Middle Aged
  • Male