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The Modern Art of Reading Computed Tomography Images of the Lungs: Quantitative CT.

Authors :
Herth, Felix J.F.
Kirby, Miranda
Sieren, Jered
Herth, Jonas
Schirm, Joshua
Wood, Susan
Schuhmann, Maren
Source :
Respiration. Jan2018, Vol. 95 Issue 1, p8-17. 10p. 1 Color Photograph, 2 Diagrams, 1 Chart.
Publication Year :
2018

Abstract

Lung diseases are increasing in prevalence and overall burden worldwide. To stem the tide, more and more national and international guidelines are recommending the use of various diagnostic algorithms that are disease specific. There is growing consensus among the respiratory community that although patient histories and lung function testing are the minimum required for clinical examinations, these tests alone are not sufficient for disease characterization. Therefore, the use of computed tomography (CT) imaging is increasing used in clinical decision making for lung diseases. Lung diseases affect various components of lung, including the small airways, lung parenchyma, the interstitial space and the pulmonary vasculature. Quantitative CT (QCT) methods are emerging and are increasingly available using commercial software to quantify the underlying disease components, and a growing body of evidence suggests that QCT is an important tool in the clinical setting to help accurately and reproducibly detect where the disease is located in the lung, and to quantify the extent and overall severity for several lung diseases. Furthermore, this growing body of evidence has promoted the use of thoracic QCT to the point that it is now considered by many as an indispensable technology for longitudinal analysis and intervention trials. Many QCT imaging measurements are available to the respiratory physician, and the aim of this review is to introduce and describe pulmonary QCT imaging measurements and methodologies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00257931
Volume :
95
Issue :
1
Database :
Academic Search Index
Journal :
Respiration
Publication Type :
Academic Journal
Accession number :
127634206
Full Text :
https://doi.org/10.1159/000480435