Literature DB >> 9386288

CT lung densitometry: dependence of CT number histograms on sample volume and consequences for scan protocol comparability.

G J Kemerink1, H H Kruize, R J Lamers, J M van Engelshoven.   

Abstract

PURPOSE: Our goals were to determine the dependence of CT number histograms of the lung on section thickness and reconstruction filter and to evaluate the consequences for scan protocol conformity required for universally comparable densitometry of the lungs.
METHOD: The effects of section thickness and reconstruction filter were parameterized with the CT's sample volume [V approximately (section thickness x in-plane resolution2)]. In a study of 31 patients, we determined as a function of V the following CT number histogram parameters: percentiles P(10) and P(90), pixel indexes PI(-905) and PI(-950), and standard deviation.
RESULTS: Patient histogram parameters depended strongly on sample volume. Large differences were found between protocols using 1 and 10 mm sections. For small variations in somewhat larger sample volumes (> 8 mm3), discrepancies were much smaller.
CONCLUSION: To obtain comparable histogram parameters, nearly identical sample volumes (> or = 8 mm3) should be used. When this condition is satisfied, available data suggest that universally comparable densitometry is feasible.

Entities:  

Mesh:

Year:  1997        PMID: 9386288     DOI: 10.1097/00004728-199711000-00018

Source DB:  PubMed          Journal:  J Comput Assist Tomogr        ISSN: 0363-8715            Impact factor:   1.826


  11 in total

1.  Quantification of emphysema: a composite physiologic index derived from CT estimation of disease extent.

Authors:  Sujal R Desai; David M Hansell; Amanda Walker; Sharon L S MacDonald; François Chabat; Athol U Wells
Journal:  Eur Radiol       Date:  2006-08-29       Impact factor: 5.315

2.  Quantification of Perinodular Emphysema in High-risk Patients Offers No Benefit in Lung Nodule Risk-Stratification of Malignancy Potential.

Authors:  William H Amundson; Eric J Swanson; Ashley Petersen; Brian J Bell; Charles Hatt; Chris H Wendt
Journal:  J Thorac Imaging       Date:  2020-03       Impact factor: 3.000

3.  Equating quantitative emphysema measurements on different CT image reconstructions.

Authors:  Seth T Bartel; Andrew J Bierhals; Thomas K Pilgram; Cheng Hong; Kenneth B Schechtman; Susan H Conradi; David S Gierada
Journal:  Med Phys       Date:  2011-08       Impact factor: 4.071

4.  Accurate measurement of small airways on low-dose thoracic CT scans in smokers.

Authors:  Barbara A Lutey; Susan H Conradi; Jeffrey J Atkinson; Jie Zheng; Kenneth B Schechtman; Robert M Senior; David S Gierada
Journal:  Chest       Date:  2013-05       Impact factor: 9.410

5.  Quantitative CT assessment of emphysema and airways in relation to lung cancer risk.

Authors:  David S Gierada; Preethi Guniganti; Blake J Newman; Mark T Dransfield; Paul A Kvale; David A Lynch; Thomas K Pilgram
Journal:  Radiology       Date:  2011-09-07       Impact factor: 11.105

6.  The effects of iterative reconstruction and kernel selection on quantitative computed tomography measures of lung density.

Authors:  Alfonso Rodriguez; Frank N Ranallo; Philip F Judy; Sean B Fain
Journal:  Med Phys       Date:  2017-05-12       Impact factor: 4.071

7.  Effects of CT section thickness and reconstruction kernel on emphysema quantification relationship to the magnitude of the CT emphysema index.

Authors:  David S Gierada; Andrew J Bierhals; Cliff K Choong; Seth T Bartel; Jon H Ritter; Nitin A Das; Cheng Hong; Thomas K Pilgram; Kyongtae T Bae; Bruce R Whiting; Jason C Woods; James C Hogg; Barbara A Lutey; Richard J Battafarano; Joel D Cooper; Bryan F Meyers; G Alexander Patterson
Journal:  Acad Radiol       Date:  2010-02       Impact factor: 3.173

8.  Fully automatic quantitative assessment of emphysema in computed tomography: comparison with pulmonary function testing and normal values.

Authors:  C P Heussel; F J F Herth; J Kappes; R Hantusch; S Hartlieb; O Weinheimer; H U Kauczor; R Eberhardt
Journal:  Eur Radiol       Date:  2009-05-21       Impact factor: 5.315

9.  Image reconstruction affects computer tomographic assessment of lung hyperinflation.

Authors:  Andreas W Reske; Harald Busse; Marcelo B P Amato; Matthias Jaekel; Thomas Kahn; Peter Schwarzkopf; Dierk Schreiter; Udo Gottschaldt; Matthias Seiwerts
Journal:  Intensive Care Med       Date:  2008-06-08       Impact factor: 17.440

10.  Automated texture-based quantification of centrilobular nodularity and centrilobular emphysema in chest CT images.

Authors:  Shoshana B Ginsburg; David A Lynch; Russell P Bowler; Joyce D Schroeder
Journal:  Acad Radiol       Date:  2012-10       Impact factor: 3.173

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