Diffusion Tensor Imaging Of White Matter Microstructural Damage And Structural Network Changes In Cerebral Small Vessel Disease

Cerebral small vessel disease(CSVD)is the general term for intracranial vascular disease based on a variety of pathophysiological processes,mainly involving arterioles,capillaries and venules.It is one of the most common diseases in middle-aged and senior people,and can cause a range of symptoms including cognitive impairment,gait disturbance,mood disturbance and urinary and bowel disorders.CSVD can cause up to 45%of dementia and 25%of ischemic stroke.The diagnosis of CSVD is highly dependent on neuroimaging magnetic resonance examinations,and its main features include presumed vascular white matter hyperintensity,enlarged perivascular space,cerebral microbleeds(CMBs),presumed vascular lacunae,recent small subcortical infarct and brain atrophy.The prevalence of these diseases is increasing with the aging of the population,and they have become an important problem affecting human health and longevity.Diffusion tensor imaging(DTI),as one of the non-invasive imaging techniques,has been widely used in the diagnosis of neuropsychiatric diseases.It can reveal the microstructural features of the brain white matter(WM)tracts and map the brain WM structural connectivity in vivo by reconstructing the major WM tracts.Previous neuroimaging studies have pointed to extensive cerebral WM damage in CSVD patients,but their main imaging features and severity vary,and there may also be differences in WM damage within CSVD patients.Therefore,this study aims to investigate the alterations of cerebral WM microstructure and structural network in CSVD patients,and to reveal the possible neural mechanisms of cognitive impairment in CSVD patients from multiple perspectives.Chapter 1 TBSS study of white matter microstructural damage in cerebral small vessel disease patients with cerebral microbleedsObjectives:To investigate the damage of WM microstructure in CSVD patients with CMBs and the neural mechanism by which CMBs influence cognitive decline in CSVD patients.Materials and Methods:Forty-nine CSVD patients with CMBs(CSVD-c,age:64.33±7.70 years,male-female ratio:30/19),114 CSVD patients without CMBs(CSVD-n,age:63.41± 7.06 years,male-female ratio:58/56)and 83 age-and sex-matched healthy controls(HC,age:61.39±8.70 years,male-female ratio:35/49)were recruited.All subjects underwent DTI,susceptibility weighted imaging(SWI)and conventional sequences scanning.We performed tract-based spatial statistics(TBSS)method to obtain the diffusion indexes,including fractional anisotropy(FA),axial diffusivity(AD),radial diffusivity(RD)and mean diffusivity(MD)values.All participants were evaluated by the neuropsychological scale.One-way analysis of covariance(ANCOVA)with post hoc analysis was performed to compare the differences of diffusion indexes among three groups.The Pearson’s correlations analysis was carried out between mean diffusion index values extracted from different regions among groups and cognitive parameters.Results:Compared with the control and CSVD-n groups,the CSVD-c group showed significantly(P<0.05)lower FA values and higher AD,RD and MD values mainly in the cognitive and sensorimotor-related WM tracts.There was no significant difference in any diffusion metric between the CSVD-n and control groups.Furthermore,the altered diffusion indexes were significantly(P<0.05)correlated with cognitive parameters in CSVD patients.Conclusions:CSVD-c patients have extensive WM microstructural deterioration.The alterations of diffusion indexes in specific brain regions can explain the decline of cognitive function in CSVD patients.Moreover,CSVD-c patients have more severe WM microstructure damage and lower cognitive function,which helps us understand the neural mechanism of cognitive dysfunction in CSVD-c patients.Chapter 2 Graph theory study of altered white matter structural networks in patients with cerebral small vessel diseaseObjectives:To investigate the topologic alterations of WM structural networks in patients with different total burden of CSVD and the relationship of such connectivity with cognitive parameters.Materials and Methods:The Simens Healthcare Magnetom Skyra 3T MR scanner was applied to acquire DTI,SWI and conventional serial scan data from 67 CSVD patients with a severe burden(CSVD-s;age:64.16 ±5.48 years;male-female ratio:43/24),133 CSVD patients with a mild burden(CSVD-m;age:62.11 ±6.88 years;male-female ratio:70/63)and 89 age-,sex-and education-matched healthy controls(age:61.43±9.54 years;male-female ratio:40/49).Probabilistic diffusion tractography was used to investigate the whole-brain WM structural connectivity in all subjects.The structural networks were constructed by estimating interregional connectivity probability,and the network global and regional properties were characterized using graph theory analysis.All participants were evaluated by the neuropsychological scale.ANCOVA with post hoc analysis was used for between-group comparisons of these network metrics,and Pearson’s correlations between the network metrics and cognitive parameters were also assessed for all groups.Results:Both the CSVD and control groups showed efficient small-world organization in WM networks.However,compared with CSVD-m patients and controls,CSVD-s patients exhibited significantly(P<0.05)decreased local efficiency,with partially reorganized hub distributions.For regional properties,CSVD-s patients showed significantly(P<0.05)decreased nodal efficiency in the bilateral anterior cingulate gyrus(ACG),caudate nucleus,right opercular inferior frontal gyrus(IFGoperc),supplementary motor area(SMA),insula,left orbital superior frontal gyrus and angular gyrus.Intriguingly,global/local efficiency and nodal efficiency of the bilateral caudate nucleus,right IFGoperc,SMA and left angular gyrus showed significant correlations with cognitive parameters in the CSVD-s group,while only the left pallidum showed significant(P<0.001)correlations with cognitive metrics in the CSVD-m group.Conclusions:The decreased local specialization of structural networks in patients with different total burden of CSVD provides insights into understanding the brain structural alterations in relation to CSVD severity.Cognitive correlations with network efficiency suggest their potential use as neuroimaging biomarkers to assess the risk of CSVD.