How can we combat multicenter variability in MR radiomics? Validation of a correction procedure.

Computer-assisted methods Diagnostic imaging Image processing Magnetic resonance imaging Neoplasms

Journal

European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774

Informations de publication

Date de publication:
Apr 2021
Historique:
received: 02 04 2020
accepted: 10 09 2020
revised: 06 07 2020
pubmed: 26 9 2020
medline: 15 4 2021
entrez: 25 9 2020
Statut: ppublish

Résumé

Test a practical realignment approach to compensate the technical variability of MR radiomic features. T1 phantom images acquired on 2 scanners, FLAIR and contrast-enhanced T1-weighted (CE-T1w) images of 18 brain tumor patients scanned on both 1.5-T and 3-T scanners, and 36 T2-weighted (T2w) images of prostate cancer patients scanned in one of two centers were investigated. The ComBat procedure was used for harmonizing radiomic features. Differences in statistical distributions in feature values between 1.5- and 3-T images were tested before and after harmonization. The prostate studies were used to determine the impact of harmonization to distinguish between Gleason grades (GGs). In the phantom data, 40 out of 42 radiomic feature values were significantly different between the 2 scanners before harmonization and none after. In white matter regions, the statistical distributions of features were significantly different (p < 0.05) between the 1.5- and 3-T images for 37 out of 42 features in both FLAIR and CE-T1w images. After harmonization, no statistically significant differences were observed. In brain tumors, 41 (FLAIR) or 36 (CE-T1w) out of 42 features were significantly different between the 1.5- and 3-T images without harmonization, against 1 (FLAIR) or none (CE-T1w) with harmonization. In prostate studies, 636 radiomic features were significantly different between GGs after harmonization against 461 before. The ability to distinguish between GGs using radiomic features was increased after harmonization. ComBat harmonization efficiently removes inter-center technical inconsistencies in radiomic feature values and increases the sensitivity of studies using data from several scanners. • Radiomic feature values obtained using different MR scanners or imaging protocols can be harmonized by combining off-the-shelf image standardization and feature realignment procedures. • Harmonized radiomic features enable one to pool data from different scanners and centers without a substantial loss of statistical power caused by intra- and inter-center variability. • The proposed realignment method is applicable to radiomic features from different MR sequences and tumor types and does not rely on any phantom acquisition.

Identifiants

pubmed: 32975661
doi: 10.1007/s00330-020-07284-9
pii: 10.1007/s00330-020-07284-9
doi:

Types de publication

Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

2272-2280

Subventions

Organisme : Université Paris-Saclay
ID : ANR-11-IDEX-0003-02

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Auteurs

Fanny Orlhac (F)

Laboratoire d'Imagerie Translationnelle en Oncologie (LITO), Inserm, Institut Curie Centre de Recherche, Université Paris-Saclay, Bât 101B, rue Henri Becquerel, 91401, Orsay, France. orlhacf@gmail.com.
Université Côte d'Azur, Inria Sophia Antipolis - Méditerranée, Epione Project Team, 2004 route des Lucioles, BP 93, 06902, Sophia Antipolis Cedex, France. orlhacf@gmail.com.

Augustin Lecler (A)

Department of Neuroradiology, Fondation Ophtalmologique A. Rothschild, 29 rue Manin, 75019, Paris, France.

Julien Savatovski (J)

Department of Neuroradiology, Fondation Ophtalmologique A. Rothschild, 29 rue Manin, 75019, Paris, France.
Centre Imagerie Médicale Paris 13, 17 avenue d'Italie, 75013, Paris, France.

Jessica Goya-Outi (J)

Laboratoire d'Imagerie Translationnelle en Oncologie (LITO), Inserm, Institut Curie Centre de Recherche, Université Paris-Saclay, Bât 101B, rue Henri Becquerel, 91401, Orsay, France.

Christophe Nioche (C)

Laboratoire d'Imagerie Translationnelle en Oncologie (LITO), Inserm, Institut Curie Centre de Recherche, Université Paris-Saclay, Bât 101B, rue Henri Becquerel, 91401, Orsay, France.

Frédérique Charbonneau (F)

Department of Neuroradiology, Fondation Ophtalmologique A. Rothschild, 29 rue Manin, 75019, Paris, France.

Nicholas Ayache (N)

Université Côte d'Azur, Inria Sophia Antipolis - Méditerranée, Epione Project Team, 2004 route des Lucioles, BP 93, 06902, Sophia Antipolis Cedex, France.

Frédérique Frouin (F)

Laboratoire d'Imagerie Translationnelle en Oncologie (LITO), Inserm, Institut Curie Centre de Recherche, Université Paris-Saclay, Bât 101B, rue Henri Becquerel, 91401, Orsay, France.

Loïc Duron (L)

Department of Neuroradiology, Fondation Ophtalmologique A. Rothschild, 29 rue Manin, 75019, Paris, France.

Irène Buvat (I)

Laboratoire d'Imagerie Translationnelle en Oncologie (LITO), Inserm, Institut Curie Centre de Recherche, Université Paris-Saclay, Bât 101B, rue Henri Becquerel, 91401, Orsay, France.

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