Quantitative biomarkers allow the diagnosis of head and neck paraganglioma on multiparametric MRI. Issue 143 (October 2021)

• Record Type: Journal Article
• Authors: Arsovic, Emina; Montava, Marion; Fakhry, Nicolas; Lavieille, Jean-Pierre; Pacak, Karel; Taïeb, David; Varoquaux, Arthur
• Is Part Of: European journal of radiology. Issue 143(2021)
• Publication Date: 2021-10
• Subjects: Paragangliomas -- Neck tumors -- MRA -- DWI -- Biomarkers -- Multiparametric imaging; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2021.109911
• Languages: English
• ISSNs: 0720-048X

Abstract

Abstract: Purpose: The aim of this study is to identify quantitative MR biomarkers in head and neck paragangliomas. Methods: 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. Results: 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. Conclusion: 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.