Radiomics in the evaluation of lung nodules: Intrapatient concordance between full-dose and ultra-low-dose chest computed tomography.


Journal

Diagnostic and interventional imaging
ISSN: 2211-5684
Titre abrégé: Diagn Interv Imaging
Pays: France
ID NLM: 101568499

Informations de publication

Date de publication:
Apr 2021
Historique:
received: 25 12 2020
revised: 19 01 2021
accepted: 19 01 2021
pubmed: 16 2 2021
medline: 19 8 2021
entrez: 15 2 2021
Statut: ppublish

Résumé

The purpose of this study was to retrospectively evaluate the quantitative and qualitative intrapatient concordance of pulmonary nodule risk assessment by commercially available radiomics software between full-dose (FD) chest-CT and ultra-low-dose (ULD) chest CT. Between July 2013 and September 2015, 68 patients (52 men and16 women; mean age, 65.5±10.6 [SD] years; range: 35-87 years) with lung nodules≥5mm and<30mm who underwent the same day FD chest CT (helical acquisition; 120kV; automated tube current modulation) and ULD chest CT (helical acquisition; 135kV; 10mA fixed) were retrospectively included. Each nodule on each acquisition was assessed by a commercial radiomics software providing a similarity malignancy index (mSI), classifying it as "benign-like" (mSI<0.1); "malignant-like" (mSI>0.9) or "undetermined" (0.1≤mSI≤0.9). Intrapatient qualitative agreement was evaluated with weighted Cohen-Kappa test and quantitative agreement with intraclass correlation coefficient (ICC). Ninety-nine lung nodules with a mean size of 9.14±4.3 (SD) mm (range: 5-25mm) in 68 patients (mean 1.46 nodule per patient; range: 1-5) were assessed; mean mSI was 0.429±0.331 (SD) (range: 0.001-1) with FD chest CT (22/99 [22%] "benign-like", 67/99 [68%] "undetermined" and 10/99 [10%] "malignant-like") and mean mSI was 0.487±0.344 (SD) (range: 0.002-1) with ULD chest CT (20/99 [20%] "benign-like", 59/99 [60%] "undetermined" and 20/99 [20%] "malignant-like"). Qualitative and quantitative agreement of FD chest CT with ULD chest CT were "good" with Kappa value of 0.60 (95% CI: 0.46-0.74) and ICC of 0.82 (95% CI: 0.73-0.87), respectively. A good agreement in malignancy similarity index can be obtained between ULD chest CT and FD chest CT using radiomics software. However, further studies must be done with more case material to confirm our results and elucidate the diagnostic capabilities of radiomics software using ULD chest CT for lung nodule characterization by comparison with FD chest CT.

Identifiants

pubmed: 33583753
pii: S2211-5684(21)00031-0
doi: 10.1016/j.diii.2021.01.010
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

233-239

Informations de copyright

Copyright © 2021 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Auteurs

Pierre-Alexis Autrusseau (PA)

Department of Diagnostic Imaging (Radio B), Hôpitaux Universitaires de Strasbourg, 67000 Strasbourg, France. Electronic address: pierrealexis.autrusseau@chru-strasbourg.fr.

Aïssam Labani (A)

Department of Diagnostic Imaging (Radio B), Hôpitaux Universitaires de Strasbourg, 67000 Strasbourg, France.

Pierre De Marini (P)

Department of Interventional Imaging (Radio A), Hôpitaux Universitaires de Strasbourg, 67000 Strasbourg, France.

Pierre Leyendecker (P)

Department of Diagnostic Imaging (Radio B), Hôpitaux Universitaires de Strasbourg, 67000 Strasbourg, France.

Cédric Hintzpeter (C)

Department of Diagnostic Imaging (Radio B), Hôpitaux Universitaires de Strasbourg, 67000 Strasbourg, France.

Anne-Claire Ortlieb (AC)

Department of Radiology, Institut Paoli-Calmettes, 13009 Marseille, France.

Michael Calhoun (M)

Mindshare Medical, 500, Yale Avenue North, 98109 Seattle, WA, USA.

Ilya Goldberg (I)

Mindshare Medical, 500, Yale Avenue North, 98109 Seattle, WA, USA.

Catherine Roy (C)

Department of Diagnostic Imaging (Radio B), Hôpitaux Universitaires de Strasbourg, 67000 Strasbourg, France.

Mickael Ohana (M)

Department of Diagnostic Imaging (Radio B), Hôpitaux Universitaires de Strasbourg, 67000 Strasbourg, France; IMAGeS Team, ICube Laboratory, 67412 Illkirch Graffenstaden, France.

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Classifications MeSH