Research On Brain White Matter Pathways Impairments Mechanism Of Dysmenorrhea Based On Parameterized Statistical Model Of Fiber Tracts

Diffusion tensor imaging(DTI)can non-invasively probe the diffusion motion of water molecules in vivo,which is a magnetic resonance imaging technique and widely used in brain science research.According to diffusion tensor direction information,researchers can restore information about the orientation and integrity of white matter fiber bundles by measuring the anisotropic diffusion of water molecules in white matter tracts.Then they can easily understand the local structure details of tracts.By analyzing DTI data in regions of specific white matter tracts,people can correctly learn the effect of disease on white matter fiber pathways and effectively diagnose white matter damage caused by fiber tracts abnormalities.Voxel-based analysis(VBA)and tract based spatial statistics(TBSS)are the common research methods of DTI diffusion properties.While voxel-based analysis is strongly influenced by registration method.Moreover,the arbitrariness of the choice of spatial smoothing extent has not yet been resolved.So it cannot be widely applied to the actual data analysis.Stephen M.Smith,a professor from University of Oxford,presented a new method called TBSS in 2006 that aims to solve above issues.TBSS takes the idea of “group mean skeleton”.Then each subject's fractional anisotropy(FA)data is projected onto the mean FA skeleton in such a way that each skeleton voxel takes the FA value from the local centre of the nearest relevant tract,realizing precise statistical analysis between group.But TBSS method only analyzes white matter fiber tracts within skeleton—not including white matter structure out of skeleton.In this paper,we propose a method called parameterized statistical model of fiber tracts based on diffusion tensor template,aiming to overcome the limitation and shortcoming of above methods.This model wants to solve individual comparison difficulty caused by brain white matter morphological differences among different population,as well as corresponding problem about the local position of white matter fiber bundles.Five steps as follows: performing whole brain deterministic tractography based on tensor atlas of healthy population,extraction and definition of fiber bundle regions of interest,prototype fiber calculation and discretization,bundle arc length parameterization,establishing parameterized statistical model of fiber tracts based on diffusion tensor template.Primary dysmenorrhea(PD),as characterized by painful menstrual cramps without organic causes,often accompanies symptoms such as sadness and irritability,headaches and dizziness,nausea and vomiting.Initial studies on damage of PD patients' brain structure suggested that dysmenorrhea women's cerebral white matter appeared abnormal changes during Ovulation time.It reminds us that periodic,continuous dysmenorrhea will affect brain white matter structure.In this article,we will verify the feasibility of the template-based parameterization statistical model of fiber bundles by comparing with previous PD studies,proving that the statistical model has the advantage of accurately locating the local white matter damage position.At the same time,we will explore the local damage characteristics of the white matter pathways in the brain of PD patients,analyze the pathogenesis of PD,and try to provide a reliable scientific basis for clinical diagnosis and prediction of diseases.