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Geometric Microstructural Characteristics of White Matter Differentiate Patients With Facial Dyskinesias and Palsy

  • Hua Zhu
  • , Aocai Yang
  • , Jixin Luan
  • , Manxi Xu
  • , Bing Liu
  • , Kuan Lv
  • , Pianpian Hu
  • , Amir Shmuel
  • , Haogang Zhu
  • , Zhen Yuan
  • , Ni Shu
  • , Jian Cheng*
  • , Guolin Ma*
  • *Corresponding author for this work
  • Beihang University
  • China-Japan Friendship Hospital
  • McGill University
  • University of Macau
  • Beijing Normal University

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: The heterogeneous and homogeneous clinical manifestations of peripheral facial palsy (FP), hemifacial spasm (HFS), and Meige's syndrome (MS) complicate the differentiation of diagnoses for these facial motor diseases. To comprehensively investigate the white matter microstructural characteristics in patients with facial dyskinesias and palsy using geometric and integrity metrics in DTI. Material and Methods: In this prospective study conducted from September 2020 to January 2022, patients with FP, HFS, and MS, as well as sex-matched healthy control subjects, underwent 3.0 T MRI. Geometric metrics (i.e., splay, bend, twist, and total distortion) based on “Director Field Analysis” and fractional anisotropy (FA) and mean diffusivity (MD) were calculated from DTI data. Cross-sectional tract-based spatial statistics were performed among FP, HFS, MS patients, and healthy controls. The correlation between disease severity and DTI metrics was evaluated. Additionally, the geometric microstructural properties combining FA and MD were used to classify FP, HFS, and MS patients using machine learning methods. Results: Geometric metrics and FA/MD were widely altered across white matter in FP and HFS patients compared with healthy controls. However, in MS patients only DFA metrics were significantly altered. FA and DFA values strongly correlated with the severity of facial movement disorder in FP patients. Combing conventional FA/MD value with DFA metrics enabled the diagnostic differentiation of FP and HFS from MS. Conclusion: Our findings demonstrated that the geometric microstructural information of white matter fibers could provide novel insight into the underlying pathological changes in facial dyskinesias and palsy.

Original languageEnglish
Article numbere70733
JournalCNS Neuroscience and Therapeutics
Volume32
Issue number2
DOIs
StatePublished - Feb 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Meige's syndrome
  • diffusion tensor imaging
  • facial palsy
  • facial paralysis

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