Introduction.The main aim of our study was to compare diffusion tensor imaging (DTI) parameters in patients with myotonic dystrophy types 1 and 2 (DM1 and DM2).Clinical rationale for the study. To ascertain whether DTI could be used to assess the integrity of white matter tracts in the brain and identify any abnormalities or disruptions in connectivity between different brain regions in patients with DM. By providing a more detailed understanding of the structural changes in the brain associated with DM, could DTI potentially be used to develop more effective treatments for the cognitive and neurological symptoms of the disorder? Material and methods. We retrospectively compared MRI scans of 19 patients with DM1 to those of 23 healthy, matched controls, and of 16 patients with DM2 to those of 20 healthy, matched controls, and finally compared the DM1 and DM2 samples. Fraction anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) values were assessed using Tract Based Spatial Statistics (TBSS).Results. In patients with DM1, a statistically significant decrease in the values of the FA parameter was revealed in 45/48 white matter tracts compared to patients with DM2. There was no statistically significant decrease in the values of the FA parameter in patients with DM2 compared to DM1. The values of MD and RD were significantly higher in 47 tracts in DM1 patients compared to DM2 patients. AD values were significantly higher in all 48 tracts in DM1 patients compared to DM2 patients. There were no tracts with increased MD, AD, or RD values in DM2 patients compared to DM1.
Conclusions.Our results indicate diffuse disintegration of white matter pathways in DM patients, especially in the DM1 group. The damage to all types of fibres (association, commissural, and projection) may explain the diversity of clinical symptoms, which were more severe in the DM1 group of patients than in the DM2 group.Clinical implications. DTI in patients with DM may help us to understand the neural mechanisms underlying brain involvement during the disease. In future, it may help to identify biomarkers for disease progression and treatment response.