Study Report on White Matter Microstructure Changes in Adult-Onset Idiopathic Focal Cervical Dystonia Patients

Scientists are dedicated to studying Adult-Onset Idiopathic Focal Cervical Dystonia (AOIFCD), the most common type of idiopathic dystonia in adults. This condition primarily manifests as abnormal neck muscle postures, often accompanied by head tremors in some patients. Existing neuroimaging studies have indicated that key motor networks may be affected by this disorder. However, previous measurement methods lacked specificity for the underlying pathophysiological differences, so the authors aim to further understand the potential mechanisms through the study of the microstructure of host white matter motor pathways.

This paper, co-authored by Claire L. Maciver, Derek Jones, and Katy Green from the Cardiff University Brain Research Imaging Centre, was published in the 2024 issue of Neurology. The research team also included Konrad Szewczyk-Krolikowski from North Bristol NHS Trust and Chantal M.W. Tax from University Medical Center Utrecht. The study findings were also presented at a journal conference in August 2024.

Research Methods

Participant Recruitment and Ethical Approval

Participants were recruited through the Wales Movement Disorder Research Network, under research numbers 14/WA/0017 and IRAS ID 146495. Clinical phenotype data were collected using the Global Dystonia Registry and Non-Motor Symptoms Study. All participants signed written informed consent, and the brain imaging study was approved by the Cardiff University School of Medicine Ethics Committee (number ¹⁸⁄₃₀).

Clinical Phenotype Identification

On the day of scanning, all participants underwent detailed video-recorded clinical examinations and were scored using the Burke-Fahn-Marsden Dystonia Scale (BFMDRS) and the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS). Non-motor phenotype data, including questionnaires on psychiatric symptoms, sleep quality, pain, and quality of life, were also collected. The Cambridge Neuropsychological Test Automated Battery (CANTAB) was used to assess cognitive function.

MRI Data Acquisition and Preprocessing

All imaging data were collected on a 3T Connectom scanner (Siemens Healthcare) using a 32-channel head coil, with a scan time of approximately 45 minutes for white matter assessment. Image processing included denoising, artifact correction, contrast balancing, gradient nonlinearity correction, and more.

In data analysis, the latest TractSeg algorithm was used to segment the white matter bundles of interest, applying the preprocessed diffusion data to multiple layers, bins, and directions. Various parameter calculation models (e.g., FA, MK, NODDI, SM) were then used for computation and parameter estimation.

Data Analysis and Statistics

The authors used RStudio for statistical analysis, applying regression models to compare disease status with various parameters, while including age, gender, and handedness as covariates. To correct for multiple comparisons, the Bonferroni correction method was used, along with Pearson correlation analysis to explore the association between clinical phenotypic features and significant diffusion parameters.

Research Results

Participant Characteristics

Data from 76 participants (including 50 AOIFCD patients and 30 healthy controls) were generated, with 4 patients excluded due to imaging or other reasons. The detailed demographic characteristics of the participants, such as age, gender, and handedness, were similar and showed no significant differences.

Tractography and Tractometry Results

In the white matter tractography results, there were no significant differences between the AOIFCD group and the control group. In contrast, Tractometry analysis revealed some significant local differences, mainly involving the anterior thalamic radiation, thalamic-premotor tracts, and striatum-premotor tracts. Specifically, the anterior thalamic radiation showed lower FA values, lower RK values, and higher ODI values, indicating possible significant microstructural changes in this region. The thalamic-premotor tracts showed higher MK and lower Neurite Density Index (NDI) in the middle segment, while the distal segment showed increased ODI and decreased f-values, suggesting increased fiber dispersion. The proximal segment of the striatum-premotor tracts showed lower f-values, indicating possible reduced axonal density in this region.

Clinical Correlation Study

Pearson correlation analysis revealed significant correlations between various imaging parameters and clinical phenotype features. For example, there was a negative correlation between the ODI in the middle segment of the left anterior thalamic radiation and the total score on the sleep disturbance questionnaire, reflecting a close link between the two. These findings suggest that changes in white matter microstructure may be closely related to various clinical features in AOIFCD patients.

Research Conclusions and Significance

This study found multiple local microstructural differences in white matter motor pathways in adult-onset idiopathic focal cervical dystonia patients using ultra-high diffusion gradient MRI, revealing abnormalities in the anterior thalamic radiation, thalamic-premotor tracts, and striatum-premotor tracts. The results emphasize the close relationship between subtle changes in white matter microstructure and AOIFCD-related symptoms, and also suggest that this disease may involve overuse or underuse of specific motor pathways, leading to imbalances and triggering abnormal muscle activity.

The highlight of this study is the application of high-resolution, ultra-high diffusion gradient MRI technology, which provides a higher signal-to-noise ratio and more accurate model parameter estimation, offering a new perspective for studying the potential mechanisms of AOIFCD. Future research should further validate these findings, particularly through large-scale cohort studies and pathological control experiments, to further clarify the histological changes underlying the observed imaging differences.