Multi-detector row CT and postprocessing techniques in the assessment of diffuse lung disease.

Details

Serval ID
serval:BIB_46299980AE73
Type
Article: article from journal or magazin.
Collection
Publications
Title
Multi-detector row CT and postprocessing techniques in the assessment of diffuse lung disease.
Journal
Radiographics
Author(s)
Beigelman-Aubry C., Hill C., Guibal A., Savatovsky J., Grenier P.A.
ISSN
1527-1323 (Electronic)
ISSN-L
0271-5333
Publication state
Published
Issued date
2005
Volume
25
Number
6
Pages
1639-1652
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
Many acute and chronic lung diseases are characterized by diffuse infiltration of the lung parenchyma. High-resolution computed tomography (CT) has been widely accepted as the imaging standard of reference for the assessment of these diseases. However, only approximately 10% of the lung parenchyma is scanned with high-resolution CT, and characteristic foci of disease may be missed. With use of the established characteristic high-resolution CT patterns, multi-detector row chest CT has revolutionized the evaluation of diffuse lung disease. Multi-detector row CT generates isotropic volumetric high-resolution data, allowing contiguous three-dimensional (3D) visualization of the lung parenchyma, with the capacity to create high-quality two-dimensional (2D) and 3D reformatted images. Minimum intensity projection is the postprocessing technique of choice for the detection and characterization of most patterns of diffuse lung disease. Maximum intensity projection (MIP) allows the detection and characterization of micronodules; the recognition of enlarged pulmonary veins, which is extremely useful in the diagnosis of pulmonary edema and the assessment of mosaic perfusion; and differentiation between perilymphatic, miliary, and centrilobular distribution. MIP can also help differentiate between constrictive bronchiolitis and mixed emphysema. Two-dimensional reformatted images are now of equal importance with the 2D axial images in diagnosing specific diffuse lung diseases. In the future, 3D reformatted images may be used to help quantify these disorders.
Keywords
Adult, Aged, Aged, 80 and over, Female, Humans, Image Processing, Computer-Assisted, Lung Diseases/radiography, Male, Middle Aged, Tomography, X-Ray Computed/methods
Pubmed
Web of science
Create date
31/08/2011 12:46
Last modification date
20/08/2019 13:51
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