Statistical Shape Analysis of Corpus Callosum in Vaginismus

Aim. Vaginismus is the presence spasm of the muscles in the vagina not allowing sexual intercourse or any interactions in the absence of any disease. Neurological diseases can cause degenerative changes in brain structures such as the corpus callosum (CC), the main white matter structure that connects the hemispheres. Studies have shown that abnormalities in the CC, which acts as a conduit for sensory information transmission. The aim of this study is to evaluate the corpus callosum of patients with vaginismus with statistical shape analysis (SSA) using magnetic resonance imaging (MRI) images and compare it with healthy controls. Material and Methods. Ten female patients diagnosed with vaginismus in the psychiatry outpatient clinic and healthy individuals who met the study criteria, had no psychiatric diagnosis, were equal in number and age were selected as the control group. Mid-sagittal T1-weighted MRI images of each individual were obtained, and the corpus callosum was marked with software on each selected image using standard anatomical landmarks, and data were collected. The mean of 'Procrustes' landmark points was calculated and shape deformations were evaluated using thin plate spline (TPS) analysis. Results. A significant slightly difference was found in terms of corpus callosum areas in the mid-sagittal images of patients with vaginismus and controls. Maximum CC deformation was observed in almost all regions markings in those with vaginismus. In the evaluation of allometry, multivariate regression test was used for the relationship between size and shape and a statistically significant model was obtained for CC. Conclusion. CC analysis with SSA using MRI images revealed significant differences between patients and healthy subjects. The study findings highlighted the abnormal distribution of white matter in the corpus callosum and the variable subregional nature of CC in vaginismus patients. This study may help future studies in terms of vaginismus etiology, diagnosis and treatment options.