Quantitative biomarkers allow the diagnosis of head and neck paraganglioma on multiparametric MRI.
Biomarkers
DWI
MRA
Multiparametric imaging
Neck tumors
Paragangliomas
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
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
109911Informations de copyright
Copyright © 2021. Published by Elsevier B.V.