Quantitative Computed Tomography: What Clinical Questions Can it Answer in Chronic Lung Disease?
Chronic lung disease
Functional CT
Quantitative CT
Journal
Lung
ISSN: 1432-1750
Titre abrégé: Lung
Pays: United States
ID NLM: 7701875
Informations de publication
Date de publication:
08 2022
08 2022
Historique:
received:
01
04
2022
accepted:
07
06
2022
pubmed:
26
6
2022
medline:
11
8
2022
entrez:
25
6
2022
Statut:
ppublish
Résumé
Quantitative computed tomography (QCT) has recently gained an important role in the functional assessment of chronic lung disease. Its capacity in diagnostic, staging, and prognostic evaluation in this setting is similar to that of traditional pulmonary function testing. Furthermore, it can demonstrate lung injury before the alteration of pulmonary function test parameters, and it enables the classification of disease phenotypes, contributing to the customization of therapy and performance of comparative studies without the intra- and inter-observer variation that occurs with qualitative analysis. In this review, we address technical issues with QCT analysis and demonstrate the ability of this modality to answer clinical questions encountered in daily practice in the management of patients with chronic lung disease.
Identifiants
pubmed: 35751660
doi: 10.1007/s00408-022-00550-1
pii: 10.1007/s00408-022-00550-1
pmc: PMC9378468
mid: NIHMS1825756
doi:
Types de publication
Journal Article
Review
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
447-455Subventions
Organisme : NCATS NIH HHS
ID : KL2 TR001429
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI135128
Pays : United States
Organisme : NIBIB NIH HHS
ID : U01 EB024501
Pays : United States
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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