Literature DB >> 31773233

Textural features of hypoxia PET predict survival in head and neck cancer during chemoradiotherapy.

A Sörensen1, M Carles2, H Bunea2, L Majerus2, C Stoykow3, N H Nicolay2,4, N E Wiedenmann2, P Vaupel2,4, P T Meyer3,4, A L Grosu2,4, M Mix3,5.   

Abstract

PURPOSE: The aim of this study was to investigate whether textural features of tumour hypoxia, assessed with serial [18F]fluoromisonidazole (FMISO)-PET, were able to predict clinical outcome in patients with head and neck squamous cell carcinoma (HNSCC, T1-4, N+, M0) during chemoradiotherapy (CRT).
METHODS: In a preliminary evaluation of a prospective trial, tumour hypoxia was evaluated in 29 patients via serial FMISO-PET before and during CRT. All patients received an initial [18F]fluorodeoxyglucose (FDG)-PET before CRT, and tumour regions were defined on this FDG-PET. The first-order metrics tumour-to-background ratio (TBRmean, TBRmax, TBRpeak), coefficient of variation, total lesion uptake and integral non-uniformity were calculated for all scans. Further, 3 second-order (textural) features from two grey-level matrices were calculated, as well as differential non-uniformity (udiff). Prognostic value was examined by median split for group separation (GS) in Kaplan-Meier estimates and correlated with overall survival (OS), quantified via log-rank tests (p ≤ 0.05) and group-relative hazard ratios (HR).
RESULTS: Within a median follow-up of 29.6 months (95% CI: 16.8-48.0 months), no first-order metrics predicted OS with a significant GS (all p > 0.05) on any FMISO-PET scan. Only udiff before and in week 2 during CRT (p = 0.03, HR = 10.8 and p = 0.05, HR = 5.2) and non-uniformity from grey-level run length matrix in week 2 separated prognostic groups (p = 0.05, HR = 5.3); lower values were correlated with better OS. Further, the decrease in udiff from before CRT to week 2 was correlated with better OS (p = 0.04, HR = 9.4). FDG-PET before CRT did not predict outcome in any measure.
CONCLUSIONS: Textural features on FMISO-PET scans before CRT, in week 2 and, to a limited degree, the change of features during CRT, were able to identify head and neck squamous cell carcinoma patients with better OS, suggesting that a higher homogeneity of the degree of hypoxia in tumours could correlate with a better outcome after CRT.

Entities:  

Keywords:  CRT; FDG; FMISO; HNSCC; Hypoxia; Radiomics

Mesh:

Substances:

Year:  2019        PMID: 31773233     DOI: 10.1007/s00259-019-04609-9

Source DB:  PubMed          Journal:  Eur J Nucl Med Mol Imaging        ISSN: 1619-7070            Impact factor:   9.236


  34 in total

1.  Residual tumour hypoxia in head-and-neck cancer patients undergoing primary radiochemotherapy, final results of a prospective trial on repeat FMISO-PET imaging.

Authors:  Steffen Löck; Rosalind Perrin; Annekatrin Seidlitz; Anna Bandurska-Luque; Sebastian Zschaeck; Klaus Zöphel; Mechthild Krause; Jörg Steinbach; Jörg Kotzerke; Daniel Zips; Esther G C Troost; Michael Baumann
Journal:  Radiother Oncol       Date:  2017-08-23       Impact factor: 6.280

2.  Spatial distribution of FMISO in head and neck squamous cell carcinomas during radio-chemotherapy and its correlation to pattern of failure.

Authors:  Sebastian Zschaeck; Robert Haase; Nasreddin Abolmaali; Rosalind Perrin; Kristin Stützer; Steffen Appold; Jörg Steinbach; Jörg Kotzerke; Daniel Zips; Christian Richter; Volker Gudziol; Mechthild Krause; Klaus Zöphel; Michael Baumann
Journal:  Acta Oncol       Date:  2015-09-23       Impact factor: 4.089

3.  Exploratory prospective trial of hypoxia-specific PET imaging during radiochemotherapy in patients with locally advanced head-and-neck cancer.

Authors:  Daniel Zips; Klaus Zöphel; Nasreddin Abolmaali; Rosalind Perrin; Andrij Abramyuk; Robert Haase; Steffen Appold; Jörg Steinbach; Jörg Kotzerke; Michael Baumann
Journal:  Radiother Oncol       Date:  2012-09-27       Impact factor: 6.280

4.  Analysis of relation between hypoxia PET imaging and tissue-based biomarkers during head and neck radiochemotherapy.

Authors:  Martin-Immanuel Bittner; Nicole Wiedenmann; Sabine Bucher; Michael Hentschel; Michael Mix; Gerta Rücker; Wolfgang A Weber; Philipp T Meyer; Martin Werner; Anca-Ligia Grosu; Gian Kayser
Journal:  Acta Oncol       Date:  2016-09-03       Impact factor: 4.089

5.  A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities.

Authors:  M Vallières; C R Freeman; S R Skamene; I El Naqa
Journal:  Phys Med Biol       Date:  2015-06-29       Impact factor: 3.609

6.  Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer.

Authors:  Florent Tixier; Catherine Cheze Le Rest; Mathieu Hatt; Nidal Albarghach; Olivier Pradier; Jean-Philippe Metges; Laurent Corcos; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2011-02-14       Impact factor: 10.057

7.  18F-FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort.

Authors:  Mathieu Hatt; Mohamed Majdoub; Martin Vallières; Florent Tixier; Catherine Cheze Le Rest; David Groheux; Elif Hindié; Antoine Martineau; Olivier Pradier; Roland Hustinx; Remy Perdrisot; Remy Guillevin; Issam El Naqa; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2014-12-11       Impact factor: 10.057

8.  A contrast-oriented algorithm for FDG-PET-based delineation of tumour volumes for the radiotherapy of lung cancer: derivation from phantom measurements and validation in patient data.

Authors:  Andrea Schaefer; Stephanie Kremp; Dirk Hellwig; Christian Rübe; Carl-Martin Kirsch; Ursula Nestle
Journal:  Eur J Nucl Med Mol Imaging       Date:  2008-07-26       Impact factor: 9.236

Review 9.  Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis.

Authors:  Sugama Chicklore; Vicky Goh; Musib Siddique; Arunabha Roy; Paul K Marsden; Gary J R Cook
Journal:  Eur J Nucl Med Mol Imaging       Date:  2012-10-13       Impact factor: 9.236

10.  Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis.

Authors:  Fanny Orlhac; Michaël Soussan; Jacques-Antoine Maisonobe; Camilo A Garcia; Bruno Vanderlinden; Irène Buvat
Journal:  J Nucl Med       Date:  2014-02-18       Impact factor: 10.057

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  6 in total

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

Authors:  Jairo A Socarrás Fernández; David Mönnich; Sara Leibfarth; Stefan Welz; Alex Zwanenburg; Stefan Leger; Steffen Löck; Christina Pfannenberg; Christian La Fougère; Gerald Reischl; Michael Baumann; Daniel Zips; Daniela Thorwarth
Journal:  Phys Imaging Radiat Oncol       Date:  2020-07

2.  Radiomic model for differentiating parotid pleomorphic adenoma from parotid adenolymphoma based on MRI images.

Authors:  Le-le Song; Shun-Jun Chen; Wang Chen; Zhan Shi; Xiao-Dong Wang; Li-Na Song; Dian-Sen Chen
Journal:  BMC Med Imaging       Date:  2021-03-20       Impact factor: 1.930

3.  Evolution of the hypoxic compartment on sequential oxygen partial pressure maps during radiochemotherapy in advanced head and neck cancer.

Authors:  Marta Lazzeroni; Ana Ureba; Nicole Wiedenmann; Nils H Nicolay; Michael Mix; Benedikt Thomann; Dimos Baltas; Iuliana Toma-Dasu; Anca L Grosu
Journal:  Phys Imaging Radiat Oncol       Date:  2021-02-11

Review 4.  The Role of Imaging Biomarkers to Guide Pharmacological Interventions Targeting Tumor Hypoxia.

Authors:  Bernard Gallez
Journal:  Front Pharmacol       Date:  2022-07-15       Impact factor: 5.988

Review 5.  The Biological Meaning of Radiomic Features.

Authors:  Michal R Tomaszewski; Robert J Gillies
Journal:  Radiology       Date:  2021-01-05       Impact factor: 11.105

Review 6.  Application of radiomics and machine learning in head and neck cancers.

Authors:  Zhouying Peng; Yumin Wang; Yaxuan Wang; Sijie Jiang; Ruohao Fan; Hua Zhang; Weihong Jiang
Journal:  Int J Biol Sci       Date:  2021-01-01       Impact factor: 6.580

  6 in total

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