Can alternative PET reconstruction schemes improve the prognostic value of radiomic features in non-small cell lung cancer?


Journal

Methods (San Diego, Calif.)
ISSN: 1095-9130
Titre abrégé: Methods
Pays: United States
ID NLM: 9426302

Informations de publication

Date de publication:
04 2021
Historique:
received: 14 09 2020
revised: 09 11 2020
accepted: 11 11 2020
pubmed: 17 11 2020
medline: 3 11 2021
entrez: 16 11 2020
Statut: ppublish

Résumé

To evaluate the potential benefit of using alternative reconstruction schemes of PET images for the prognostic value of radiomic features. Patients (n=91) with non-small cell lung cancer were prospectively included. All had a PET/CT examination before treatment. Three different PET images were reconstructed for each patient: the standard clinical protocol (i.e., 4×4×4 mm The 3 reconstructions led to different distributions for most of the features. The larger shifts and standard deviations of differences was observed between 200G5 and 400G1, which was also confirmed through linear mixed models. However, these relatively important differences in distributions did not translate into a significant impact on the stratification power of the features in terms of prognosis, although a trend in decreasing prognostic value could be observed (smaller number of features with HR above 2, overall lower HR values). Most prognostic features displayed high correlation with either volume or SUV Using smaller voxels or less strong filtering options in the reconstruction settings of PET images compared to the standard clinical protocols led to different distributions of the resulting radiomic features. However, the hierarchy between patients according to these distributions remained overall the same and therefore the resulting stratification power of the radiomic features was not significantly altered. These results should be compared to those obtained in the context of other pathologies where radiomic features displaying lower correlation with volume or SUV

Identifiants

pubmed: 33197567
pii: S1046-2023(20)30251-6
doi: 10.1016/j.ymeth.2020.11.002
pii:
doi:

Substances chimiques

Radiopharmaceuticals 0
Fluorodeoxyglucose F18 0Z5B2CJX4D

Types de publication

Journal Article Observational Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

73-83

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Olena Tankyevych (O)

LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France; Nuclear medicine department, CHU Milétrie, Poitiers, France.

Florent Tixier (F)

LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France.

Nils Antonorsi (N)

Nuclear medicine department, CHU Milétrie, Poitiers, France.

Anas Filali Razzouki (A)

Nuclear medicine department, CHU Milétrie, Poitiers, France.

Raphael Mondon (R)

Nuclear medicine department, CHU Milétrie, Poitiers, France.

Thomas Pinto-Leite (T)

Nuclear medicine department, CHU Milétrie, Poitiers, France.

Dimitris Visvikis (D)

LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France.

Mathieu Hatt (M)

LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France. Electronic address: hatt@univ-brest.fr.

Catherine Cheze Le Rest (C)

LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France; Nuclear medicine department, CHU Milétrie, Poitiers, France.

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Classifications MeSH