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Quantitative Biomarkers Allow the Diagnosis of Head and Neck Paraganglioma on Multiparametric MRI.

European journal of radiology(2021)

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摘要
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(boolean AND)-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.
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关键词
Paragangliomas,Neck tumors,MRA,DWI,Biomarkers,Multiparametric imaging
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