Diagnostic Challenges and Imaging Considerations for Intraparotid Facial Nerve Schwannoma: A Case Report and Literature Review.
Jeton LuzhaMarkus KoppMarco WiesmüllerLava TahaRobin RuppKonstantinos MantsopoulosMichael KochHeinrich IroMatti SievertPublished in: The American journal of case reports (2024)
BACKGROUND A mass in the parotid gland usually indicates parotid gland neoplasia. Warthin tumors or pleomorphic adenomas are common differential diagnoses. Less frequently, other differential diagnoses and sites of origin are considered. Schwannomas are rare, benign tumors in the head and neck region. Even more rarely, these tumors occur in the intraparotid course of the facial nerve. In the following, we report about 2 patients in whom a mass in the right parotid gland was found incidentally during magnetic resonance imaging (MRI). CASE REPORT We reviewed data from the literature on intraparotid facial nerve schwannomas (IPFNS) and compared them with those from our cases. The focus was on data such as clinical history, clinical symptoms, electroneurography, and various imaging modalities, such as ultrasonography and MRI combined with diffusion-weighted imaging. CONCLUSIONS It is challenging to distinguish facial nerve schwannomas from other neoplasms. Patient's history, clinical symptoms, MRI examination with diffusion-weighted imaging, and high-resolution ultrasound imaging are decisive factors for diagnosis and should be performed when IPFNS is suspected. Diagnosis and therapy for IPFNS remain challenging. A wait-and-scan approach could be an option for patients with small tumors and good facial nerve function. On the other hand, patients with advanced tumors associated with limited facial nerve function can benefit from surgical approaches or stereotactic radiosurgery.
Keyphrases
- diffusion weighted imaging
- contrast enhanced
- magnetic resonance imaging
- high resolution
- computed tomography
- case report
- peripheral nerve
- soft tissue
- end stage renal disease
- magnetic resonance
- chronic kidney disease
- electronic health record
- mass spectrometry
- ejection fraction
- machine learning
- depressive symptoms
- sleep quality