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Related Experiment Video

Updated: May 7, 2026

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Structural Phenotype of High-Frequency Recurrent Facial Palsy.

Yeso Choi1, Il-Seok Park1, Sung Jun Han1

  • 1Department of Otorhinolaryngology, Hallym University College of Medicine, Dong-Tan Sacred Heart Hospital, Hwaseong-si, Korea.

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PubMed
Summary

Recurrent facial palsy is linked to specific anatomical traits, particularly bony exostosis. Identifying these structural changes with HRCT can predict patients at risk for repeated episodes.

Keywords:
bony exostosisfallopian canalgeniculate ganglionhigh‐resolution computed tomographyrecurrent facial palsy

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Area of Science:

  • Otolaryngology
  • Neurosurgery
  • Radiology

Background:

  • Recurrent peripheral facial palsy suggests an underlying anatomical predisposition.
  • High-frequency recurrence necessitates identification of associated anatomical phenotypes.

Purpose of the Study:

  • To identify the anatomical phenotype associated with three or more recurrences of peripheral facial palsy.
  • Utilize high-resolution computed tomography (HRCT) for anatomical assessment.

Main Methods:

  • Retrospective analysis of 63 patients with recurrent facial palsy and 62 controls.
  • Quantification of four HRCT parameters: geniculate ganglion (GG) enlargement, labyrinthine segment (LS) constriction, intracanalicular bony exostosis, and greater superficial petrosal nerve (GSPN) thickening.
  • Evaluation of inter-parameter correlations.

Main Results:

  • Intracanalicular bony exostosis was the strongest predictor of recurrence (39.7% vs. 9.7%, OR: 7.39).
  • GG enlargement and GSPN thickening were more prevalent in the recurrent group (p < 0.01) and positively correlated (ρ = 0.58).
  • 63.5% of the recurrent group showed at least one structural or secondary finding (p < 0.001).

Conclusions:

  • High-frequency recurrent facial palsy is associated with a structural phenotype.
  • Fixed bony constraints, such as exostosis, can worsen chronic inflammation in the GG and GSPN.
  • HRCT identification of these features aids in predicting recurrence risk and planning surgical decompression.