Literature DB >> 23122673

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

Andreas Christe1, Jaled Charimo-Torrente, Kingshuk Roychoudhury, Peter Vock, Justus E Roos.   

Abstract

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.
Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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Year:  2012        PMID: 23122673     DOI: 10.1016/j.ejrad.2012.09.025

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  17 in total

1.  Inter- and intrascanner variability of pulmonary nodule volumetry on low-dose 64-row CT: an anthropomorphic phantom study.

Authors:  X Xie; M J Willemink; Y Zhao; P A de Jong; P M A van Ooijen; M Oudkerk; M J W Greuter; R Vliegenthart
Journal:  Br J Radiol       Date:  2013-07-24       Impact factor: 3.039

2.  Ultra-low-dose CT with model-based iterative reconstruction (MBIR): detection of ground-glass nodules in an anthropomorphic phantom study.

Authors:  Cristiano Rampinelli; Daniela Origgi; Vittoria Vecchi; Luigi Funicelli; Sara Raimondi; Paul Deak; Massimo Bellomi
Journal:  Radiol Med       Date:  2015-02-06       Impact factor: 3.469

Review 3.  [HRCT technique with low-dose protocols for interstitial lung diseases].

Authors:  J Ley-Zaporozhan; S Ley
Journal:  Radiologe       Date:  2014-12       Impact factor: 0.635

4.  Feasibility of low-dose CT with spectral shaping and third-generation iterative reconstruction in evaluating interstitial lung diseases associated with connective tissue disease: an intra-individual comparison study.

Authors:  Xiaoli Xu; Xin Sui; Lan Song; Yao Huang; Yingqian Ge; Zhengyu Jin; Wei Song
Journal:  Eur Radiol       Date:  2019-02-08       Impact factor: 5.315

5.  CT image quality in sinogram affirmed iterative reconstruction phantom study - is there a point of diminishing returns?

Authors:  Juan C Infante; Yu Liu; Cynthia K Rigsby
Journal:  Pediatr Radiol       Date:  2016-11-28

6.  T2 mapping of CT remodelling patterns in interstitial lung disease.

Authors:  Maria T A Buzan; Monika Eichinger; Michael Kreuter; Hans-Ulrich Kauczor; Felix J Herth; Arne Warth; Carmen Monica Pop; Claus Peter Heussel; Julien Dinkel
Journal:  Eur Radiol       Date:  2015-06-03       Impact factor: 5.315

7.  Observer Performance for Detection of Pulmonary Nodules at Chest CT over a Large Range of Radiation Dose Levels.

Authors:  Joel G Fletcher; David L Levin; Anne-Marie G Sykes; Rebecca M Lindell; Darin B White; Ronald S Kuzo; Vighnesh Suresh; Lifeng Yu; Shuai Leng; David R Holmes; Akitoshi Inoue; Matthew P Johnson; Rickey E Carter; Cynthia H McCollough
Journal:  Radiology       Date:  2020-09-29       Impact factor: 11.105

8.  Diagnostic validation of a deep learning nodule detection algorithm in low-dose chest CT: determination of optimized dose thresholds in a virtual screening scenario.

Authors:  Alan A Peters; Adrian T Huber; Verena C Obmann; Johannes T Heverhagen; Andreas Christe; Lukas Ebner
Journal:  Eur Radiol       Date:  2022-01-21       Impact factor: 5.315

9.  Optimal dose levels in screening chest CT for unimpaired detection and volumetry of lung nodules, with and without computer assisted detection at minimal patient radiation.

Authors:  Andreas Christe; Zsolt Szucs-Farkas; Adrian Huber; Philipp Steiger; Lars Leidolt; Justus E Roos; Johannes Heverhagen; Lukas Ebner
Journal:  PLoS One       Date:  2013-12-26       Impact factor: 3.240

10.  Feasible Dose Reduction in Routine Chest Computed Tomography Maintaining Constant Image Quality Using the Last Three Scanner Generations: From Filtered Back Projection to Sinogram-affirmed Iterative Reconstruction and Impact of the Novel Fully Integrated Detector Design Minimizing Electronic Noise.

Authors:  Lukas Ebner; Felix Knobloch; Adrian Huber; Julia Landau; Daniel Ott; Johannes T Heverhagen; Andreas Christe
Journal:  J Clin Imaging Sci       Date:  2014-07-31
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