Study On Damage Of White Matter Motor Pathway In Stroke Patients Based On Fiber Bundle Optimal Matching Algorithm

In recent years,in order to study the integrity and development of white matter structure,quantitative analysis of diffusion tensor imaging(DTI)data has attracted the attention of more and more researchers.DTI is a non-invasive magnetic resonance imaging technique capable of detecting the diffusion of water molecules in vivo,and is a commonly used method in current brain science research.As a magnetic resonance functional imaging method that has emerged in recent years,DTI can simulate the reconstruction of the diffusion trajectory of water molecules with special diffusion characteristics in the brain,and the post-processing images can clearly show the direction and shape of the white matter fiber bundle.According to the DTI,the diffusion characteristic image can be calculated.The image can quantitatively analyze the fine structure of the white matter.It is a more accurate neuroimaging basis for clinical diagnosis and disease assessment,which is helpful for clinicians to choose appropriate treatment plans and judge the therapeutic effect.In the current DTI analysis method,based on the Tract Based Spatial Statistics(TBSS),a pioneering method for voxel analysis of DTI data has been widely used in many DTI studies.However,the reliability and interpretability of TBSS has been challenged in many ways.In 2016,Wang et al.proposed a new DTI statistical analysis method based on the map-based fiber bundle space matching statistical method.This method does not rely on the registration between images,and gets rid of the main source of error in TBSS-the "skeletonization" process.In this paper,Ground truth is firstly used to detect the correct rate of fiber bundle matching for the case where the number of templates and individual fiber bundles are the same or different.The results show that when the number of templates is different from the number of individual fibers,the matching accuracy rate fluctuates greatly.After further analysis,this study added the “intermediate template” and fiber bundle clustering steps in the method flow,and the method was optimized and improved to solve more DTI analysis problems that could not be registered.A more accurate quantitative analysis of the fiber bundle is achieved.Finally,this study will use the improved map-based fiber bundle spatial matching statistical method to study the white matter characteristics of patients with lacunar infarction to explore the damage mechanism of white matter motor pathway in patients with lacunar infarction.Ischemic stroke is a common disease that currently threatens human life,with high morbidity,disability,and mortality,and is prone to recurrence.In brain diseases similar to stroke,traditional image-based analysis methods are not suitable for the analysis of this disease due to morphological abnormalities in the brain.In this paper,the results of the analysis of patients with lacunar infarction were compared with other similar studies to verify the feasibility of the fiber bundle spatial matching statistical model.It is proved that the DTI statistical model has the advantage of directly showing the damage of the local white matter fiber bundle.At the same time,we will also explore the abnormalities of white matter structure in patients with lacunar infarction,and try to provide a scientific theoretical basis for the clinical diagnosis and treatment of similar ischemic stroke diseases.