Novelties in imaging in pulmonary fibrosis and nodules. A narrative review.


Journal

Pulmonology
ISSN: 2531-0437
Titre abrégé: Pulmonology
Pays: Spain
ID NLM: 101723786

Informations de publication

Date de publication:
Historique:
received: 23 09 2019
accepted: 25 09 2019
pubmed: 11 11 2019
medline: 12 11 2020
entrez: 11 11 2019
Statut: ppublish

Résumé

In recent months two major fields of interest in pulmonary imaging have stood out: pulmonary fibrosis and pulmonary nodules. New guidelines have been released to define pulmonary fibrosis and subsequent studies have proved the value of these changes. In addition, new recommendations for classification of pulmonary nodules have been released. Radiological images are of major interest for automated and standardized analysis and so in both cases software tools using artificial intelligence were developed for visualization and quantification of the disease. These tools have been validated by human readers and demonstrated their capabilities. This review summarizes the new recommendations for classification of pulmonary fibrosis and nodules and reviews the capabilities of radiomics within these two entities.

Identifiants

pubmed: 31706882
pii: S2531-0437(19)30179-5
doi: 10.1016/j.pulmoe.2019.09.009
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

39-44

Informations de copyright

Copyright © 2019 Sociedade Portuguesa de Pneumologia. Published by Elsevier España, S.L.U. All rights reserved.

Auteurs

S Ley (S)

Chirurgisches Klinikum München Süd, Am Isarkanal 30, 81379 München, Germany. Electronic address: ley@radiologie-ley.de.

J Ley-Zaporozhan (J)

Chirurgisches Klinikum München Süd, Am Isarkanal 30, 81379 München, Germany.

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Classifications MeSH