Reliability and prognostic value of radiomic features are highly dependent on choice of feature extraction platform.


Journal

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

Informations de publication

Date de publication:
Nov 2020
Historique:
received: 26 02 2020
accepted: 14 05 2020
revised: 28 03 2020
pubmed: 3 6 2020
medline: 25 3 2021
entrez: 3 6 2020
Statut: ppublish

Résumé

To investigate the effects of Image Biomarker Standardisation Initiative (IBSI) compliance, harmonisation of calculation settings and platform version on the statistical reliability of radiomic features and their corresponding ability to predict clinical outcome. The statistical reliability of radiomic features was assessed retrospectively in three clinical datasets (patient numbers: 108 head and neck cancer, 37 small-cell lung cancer, 47 non-small-cell lung cancer). Features were calculated using four platforms (PyRadiomics, LIFEx, CERR and IBEX). PyRadiomics, LIFEx and CERR are IBSI-compliant, whereas IBEX is not. The effects of IBSI compliance, user-defined calculation settings and platform version were assessed by calculating intraclass correlation coefficients and confidence intervals. The influence of platform choice on the relationship between radiomic biomarkers and survival was evaluated using univariable cox regression in the largest dataset. The reliability of radiomic features calculated by the different software platforms was only excellent (ICC > 0.9) for 4/17 radiomic features when comparing all four platforms. Reliability improved to ICC > 0.9 for 15/17 radiomic features when analysis was restricted to the three IBSI-compliant platforms. Failure to harmonise calculation settings resulted in poor reliability, even across the IBSI-compliant platforms. Software platform version also had a marked effect on feature reliability in CERR and LIFEx. Features identified as having significant relationship to survival varied between platforms, as did the direction of hazard ratios. IBSI compliance, user-defined calculation settings and choice of platform version all influence the statistical reliability and corresponding performance of prognostic models in radiomics. • Reliability of radiomic features varies between feature calculation platforms and with choice of software version. • Image Biomarker Standardisation Initiative (IBSI) compliance improves reliability of radiomic features across platforms, but only when calculation settings are harmonised. • IBSI compliance, user-defined calculation settings and choice of platform version collectively affect the prognostic value of features.

Identifiants

pubmed: 32483644
doi: 10.1007/s00330-020-06957-9
pii: 10.1007/s00330-020-06957-9
pmc: PMC7553896
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

6241-6250

Subventions

Organisme : Cancer Research UK
ID : C147/A18083
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C147/A25254
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C19221/A22746
Pays : United Kingdom

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Auteurs

Isabella Fornacon-Wood (I)

Division of Cancer Sciences, University of Manchester, Manchester, UK. Isabella.fornacon-wood@postgrad.manchester.ac.uk.

Hitesh Mistry (H)

Division of Cancer Sciences, University of Manchester, Manchester, UK.

Christoph J Ackermann (CJ)

Department of Medical Oncology, Spital STS AG, Thun, Switzerland.

Fiona Blackhall (F)

Division of Cancer Sciences, University of Manchester, Manchester, UK.
Department of Medical Oncology, The Christie Hospital NHS Foundation Trust, Manchester, UK.

Andrew McPartlin (A)

Department of Clinical Oncology, The Christie Hospital NHS Foundation Trust, Manchester, UK.

Corinne Faivre-Finn (C)

Division of Cancer Sciences, University of Manchester, Manchester, UK.
Department of Clinical Oncology, The Christie Hospital NHS Foundation Trust, Manchester, UK.

Gareth J Price (GJ)

Division of Cancer Sciences, University of Manchester, Manchester, UK.

James P B O'Connor (JPB)

Division of Cancer Sciences, University of Manchester, Manchester, UK.
Department of Diagnostic Radiology, The Christie Hospital NHS Foundation Trust, Manchester, UK.

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