Diffusion kurtosis imaging in assessment of structural brain network topology alteration and microstructural damage in patients with multiple sclerosis
10.3760/cma.j.cn112149-20221207-00980
- VernacularTitle:扩散峰度成像评估多发性硬化患者脑结构网络拓扑属性改变及其微结构损伤
- Author:
Zichun YAN
1
;
Shuang DING
;
Zhuowei SHI
;
Qiyuan ZHU
;
Feiyue YIN
;
Xiaohua WANG
;
Zeyun TAN
;
Yongmei LI
Author Information
1. 重庆医科大学附属第一医院放射科，重庆 400016
- Keywords:
Multiple sclerosis;
Structural brain network;
Diffusion kurtosis imaging;
Microstructural damage;
Cognitive function
- From:
Chinese Journal of Radiology
2023;57(11):1222-1230
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the changes in structural brain network topology and microstructural damage in patients with multiple sclerosis (MS), and to analyze its correlation with cognitive function.Methods:Clinical and imaging data of 114 patients with MS (MS group) diagnosed in the First Affiliated Hospital of Chongqing Medical University from May 2021 to September 2022 were analyzed retrospectively. In addition, 71 volunteers were recruited as a healthy control group (HC group) during the same period. All subjects were performed on cognitive assessment and 3D-T 1 magnetization-prepared rapid gradient echo, 3D-fluid-attenuated inversion recovery, and diffusion kurtosis imaging (DKI) scans. GRETNA software was used to obtain network topology attributes, and global attributes included global efficiency, local efficiency, and small-world attributes [clustering coefficient(Cp), shortest path length(Lp), normalized Cp(γ), normalized Lp, and small-world index (σ)]. Local attributes included betweenness centrality (BC), degree centrality (DC), nodal clustering coefficient (NCp), nodal efficiency, nodal local efficiency (NLe) and nodal shortest path length. The DKI parameter map generated by the post-processing software was used to extract the DKI parameter values of the brain region with abnormal local topology of the brain structure network. The differences of global attributes, local attributes and DKI parameter values [kurtosis fractional anisotropy (KFA), mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) values] were analyzed by independent sample t-test or Mann-Whitney U test, and corrected by false discovery rate (FDR). Spearman or Pearson correlation analysis was used to evaluate the correlation between abnormal brain structure network topology attributes and cognitive scale scores in the MS group. Results:Both the MS group and the HC group structure network showed small-world attributes, and the γ and σ values of the MS group were significantly lower than those in the HC group (FDR correction, P<0.05). Compared with the HC group, BC, DC, NCp and NLe broadly reduced in the MS group, mainly involving in bilateral frontal, temporal, precuneus, amygdala, and thalamus (FDR correction, P<0.05). After FDR correction, compared with the HC group, the KFA, MK, RK and AK values of 23 brain regions with abnormal local attributes of the network in the MS group were significantly changed in several brain regions (FDR correction, P<0.05). The correlation analysis showed, after FDR correction, the DC value of the right putamen in MS patients was positively correlated with the digit span test (DST) scores ( r=0.318 ,P=0.001). Conclusion:There are extensive changes in the structural brain network of MS patients, accompanied by varying degrees of microstructural damage, and the reduction of degree centrality in the basal ganglia putamen region is associated with cognitive impairment.
