Comparison of patient stratification by computed tomography radiomics and hypoxia positron emission tomography in head-and-neck cancer radiotherapy.

CT-Imaging Imaging biomarkers Machine Learning PET-Imaging Quantitative Imaging Radiomics

Journal

Physics and imaging in radiation oncology
ISSN: 2405-6316
Titre abrégé: Phys Imaging Radiat Oncol
Pays: Netherlands
ID NLM: 101704276

Informations de publication

Date de publication:
Jul 2020
Historique:
received: 19 03 2020
revised: 21 07 2020
accepted: 21 07 2020
entrez: 12 10 2020
pubmed: 13 10 2020
medline: 13 10 2020
Statut: ppublish

Résumé

Hypoxia Positron-Emission-Tomography (PET) as well as Computed Tomography (CT) radiomics have been shown to be prognostic for radiotherapy outcome. Here, we investigate the stratification potential of CT-radiomics in head and neck cancer (HNC) patients and test if CT-radiomics is a surrogate predictor for hypoxia as identified by PET. Two independent cohorts of HNC patients were used for model development and validation, HN1 (n = 149) and HN2 (n = 47). The training set HN1 consisted of native planning CT data whereas for the validation cohort HN2 also hypoxia PET/CT data was acquired using [ The best performing CT-radiomics signature included two features with nearest-neighbour classification (AUC = 0.76 ± 0.09), whereas AUC was 0.59 for external validation. In contrast, [ No direct correlation of patient stratification using [

Sections du résumé

BACKGROUND AND PURPOSE OBJECTIVE
Hypoxia Positron-Emission-Tomography (PET) as well as Computed Tomography (CT) radiomics have been shown to be prognostic for radiotherapy outcome. Here, we investigate the stratification potential of CT-radiomics in head and neck cancer (HNC) patients and test if CT-radiomics is a surrogate predictor for hypoxia as identified by PET.
MATERIALS AND METHODS METHODS
Two independent cohorts of HNC patients were used for model development and validation, HN1 (n = 149) and HN2 (n = 47). The training set HN1 consisted of native planning CT data whereas for the validation cohort HN2 also hypoxia PET/CT data was acquired using [
RESULTS RESULTS
The best performing CT-radiomics signature included two features with nearest-neighbour classification (AUC = 0.76 ± 0.09), whereas AUC was 0.59 for external validation. In contrast, [
CONCLUSIONS CONCLUSIONS
No direct correlation of patient stratification using [

Identifiants

pubmed: 33043157
doi: 10.1016/j.phro.2020.07.003
pii: S2405-6316(20)30037-3
pmc: PMC7536307
doi:

Types de publication

Journal Article

Langues

eng

Pagination

52-59

Informations de copyright

© 2020 The Author(s).

Déclaration de conflit d'intérêts

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: DT and DZ declare institutional collaborations including financial support with the companies Siemens Healthineers (2014–2019), Elekta AB, Philips and PTW Freiburg without any direct relation to this study. In the past 5 years, MB attended an advisory board meeting of MERCK KGaA (Darmstadt), for which the University of Dresden received a travel grant. He further received funding for his research projects and for educational grants to the University of Dresden by Teutopharma GmbH (2011–2015), IBA (2016), Bayer AG (2016–2018), Merck KGaA (2014–2030), Medipan GmbH (2014–2018). For the German Cancer Research Center (DKFZ, Heidelberg) MB is on the supervisory boards of HI-STEM gGmbH (Heidelberg). MB, as former chair of OncoRay (Dresden) and present CEO and Scientific Chair of the German Cancer Research Center (DKFZ, Heidelberg), signed/signs contracts for his institute(s) and for the staff for research funding and/or collaborations with a multitude of companies worldwide. MB confirms that none of the above funding sources were involved in the design of this study, the preparation of this paper, the materials used, or the collection, analysis, and interpretation of data.

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Auteurs

Jairo A Socarrás Fernández (JA)

Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany.

David Mönnich (D)

Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany.

Sara Leibfarth (S)

Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany.

Stefan Welz (S)

Department of Radiation Oncology, University of Tübingen, Germany.

Alex Zwanenburg (A)

OncoRay National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany.

Stefan Leger (S)

OncoRay National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany.

Steffen Löck (S)

OncoRay National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.

Christina Pfannenberg (C)

Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany.

Christian La Fougère (C)

Department of Nuclear Medicine, University of Tübingen, Germany.

Gerald Reischl (G)

Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Germany.

Michael Baumann (M)

OncoRay National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
German Cancer Research Center DKFZ, Heidelberg, Germany.

Daniel Zips (D)

Department of Radiation Oncology, University of Tübingen, Germany.
German Cancer Consortium (DKTK), partner Site Tübingen, Tübingen, Germany.

Daniela Thorwarth (D)

Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany.
German Cancer Consortium (DKTK), partner Site Tübingen, Tübingen, Germany.

Classifications MeSH