MR imaging of the superior cervical ganglion and inferior ganglion of the vagus nerve: Structures that can mimic pathologic retropharyngeal lymph nodes

Abstract

Background and Purpose: The superior cervical ganglion and inferior ganglion of the vagus nerve can mimic pathologic retropharyngeal lymph nodes. We studied the cross-sectional anatomy of the superior cervical ganglion and inferior ganglion of the vagus nerve to evaluate how they can be differentiated from the retropharyngeal lymph nodes. MATERIALS AND METHODS: This retrospective study consists of 2 parts. Cohort 1 concerned the signal intensity of routine neck MR imaging with 2D sequences, apparent diffusion coefficient, and contrast enhancement of the superior cervical ganglion compared with lymph nodes with or without metastasis in 30 patients. Cohort 2 used 3D neurography to assess the morphology and spatial relationships of the superior cervical ganglion, inferior ganglion of the vagus nerve, and the retropharyngeal lymph nodes in 50 other patients. RESULTS: All superior cervical ganglions had homogeneously greater enhancement and lower signal on diffusion-weighted imaging than lymph nodes. Apparent diffusion coefficient values of the superior cervical ganglion (1.80 ± 0.28× 10 -3 mm2/s) were significantly higher than normal and metastatic lymph nodes (0.86 ±; 0.10 -3 mm 2 /s, P < .001). Ten and 13 of 60 superior cervical ganglions were hypointense on T2-weighted images and had hyperintense spots on both T1- A nd T2-weighted images, respectively. The latter was considered fat tissue. The largest was the superior cervical ganglion, followed in order by the retropharyngeal lymph node and the inferior ganglion of the vagus nerve (P < .001 to = .001). The retropharyngeal lymph node, superior cervical ganglion, and inferior ganglion of the vagus nerve formed a line from anteromedial to posterolateral. CONCLUSIONS: The superior cervical ganglion and the inferior ganglion of the vagus nerve can be almost always differentiated from retropharyngeal lymph nodes on MR imaging by evaluating the signal, size, and position.