Quantitative biomarkers allow the diagnosis of head and neck paraganglioma on multiparametric MRI.


Journal

European journal of radiology
ISSN: 1872-7727
Titre abrégé: Eur J Radiol
Pays: Ireland
ID NLM: 8106411

Informations de publication

Date de publication:
Oct 2021
Historique:
received: 27 04 2021
revised: 03 08 2021
accepted: 11 08 2021
pubmed: 12 9 2021
medline: 29 9 2021
entrez: 11 9 2021
Statut: ppublish

Résumé

The aim of this study is to identify quantitative MR biomarkers in head and neck paragangliomas. The study was approved by an institutional review board. A retrospective review of patients with head and neck paragangliomas (HNPGL) evaluated by time-resolved MRA sequences between 2009 and 2019 was performed. A control group investigated during the same period was analyzed, including nerve sheath tumors and metastatic lymph nodes from squamous cell carcinomas or undifferentiated nasopharyngeal cancer (UCNT). A gold standard was obtained for all cases. Semi-quantitative parameters of enhancement were extracted from time-intensity curves on time-resolved MRA sequences and diffusion weighted imaging/DWI was assessed for each lesion. Sixty head and neck paragangliomas (HNPGLs) were included from 50 patients. The control group consisted of 30 parapharyngeal space lesions (27 patients), which included nerve sheath tumors (n = 12) and metastatic lymph nodes (n = 18) from squamous cell carcinomas or UCNT. PGLs showed a shorter time-to-peak value compared to other groups, measured at 25.0 +/- 29 sec. The wash-in and wash-out ratios were also significantly higher for PGLs, respectively measured at 5.34 ± 2.99 (p < 0,001) and 1.24 ± 0.80 (p < 0.001). On DWI sequences, the mean ADC value for PGLs (1.17 ± 0.19 10^-3 mm2/s) was significantly different than the other tumor groups (p < 0.001). HNPGLs were clearly distinguishable from other tumors on classification with regression tree based on TTP and ADC values. These distinct group features were also consistent on principal component analysis. Our study identifies a multiparametric signature for disease subtyping, providing a strong impetus for switching from qualitative to quantitative analysis of deep soft-tissue tumors of the neck.

Identifiants

pubmed: 34508941
pii: S0720-048X(21)00392-2
doi: 10.1016/j.ejrad.2021.109911
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

109911

Informations de copyright

Copyright © 2021. Published by Elsevier B.V.

Auteurs

Emina Arsovic (E)

Department of Nuclear Medicine, La Timone University Hospital, CERIMED, Aix-Marseille University, France.

Marion Montava (M)

Department of Head and Neck Surgery, Conception Hospital, Aix-Marseille Univ, France.

Nicolas Fakhry (N)

Department of Head and Neck Surgery, Conception Hospital, Aix-Marseille Univ, France.

Jean-Pierre Lavieille (JP)

Department of Head and Neck Surgery, Conception Hospital, Aix-Marseille Univ, France.

Karel Pacak (K)

Section on Medical Neuroendocrinology, Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD), National Institutes of Health, Bethesda, MD 20892, USA.

David Taïeb (D)

Department of Nuclear Medicine, La Timone University Hospital, CERIMED, Aix-Marseille University, France.

Arthur Varoquaux (A)

Department of Medical Imaging, Conception University Hospital, Aix-Marseille Univ, France; Center for Magnetic Resonance in Biology and Medicine, UMR 7339, La Timone University Hospital, Aix-Marseille Univ, France. Electronic address: Arthur.VAROQUAUX@ap-hm.fr.

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