Research on the neuroimaging functional network of patients with spinocerebellar ataxia type 3
10.3760/cma.j.cn112149-20230926-00238
- VernacularTitle:脊髓小脑共济失调3型患者神经影像功能网络的MRI研究
- Author:
Xingang WANG
1
;
Hui CHEN
;
Ru WEN
;
Chen LIU
Author Information
1. 陆军军医大学第一附属医院放射科，重庆 400038
- Keywords:
Spinocerebellar ataxias;
Magnetic resonance imaging;
Brain networks;
Graph theory
- From:
Chinese Journal of Radiology
2024;58(7):713-720
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the abnormalities of functional brain networks and their relationship with behavioral scale scores in patients with spinal cerebellar ataxia (SCA) type 3 using MRI.Methods:The study was a cross-sectional study. Clinical and imaging data of 52 patients with SCA type 3 (SCA type 3 group) and 55 normal control group admitted to the First Affiliated Hospital of Army Medical University from May 2017 to May 2023 were prospectively analyzed. All participants underwent structural and resting-state functional MRI. Graph theory analysis assessed global and nodal properties of brain network connectivity, including clustering coefficient (Cp), characteristic path length (Lp), normalized clustering coefficient (γ), normalized characteristic path length (λ), small-world index (σ), global efficiency (Eglob), local efficiency (Eloc), assortativity, and nodal efficiency. The area under the curve (AUC) for global attribute parameters was calculated and a two-sample t-test was used to compare the AUC values of the global attribute parameters between the 2 groups, and corrected for false discovery rate correction (FDR). A two-sample t-test was used to compare the node efficiencies of the 2 groups, corrected for network-based statistics (NBS), and the brain regions with significant differences in node efficiencies between the 2 groups were selected as the brain regions of interest, and a two-sample t-test was used to compare the differences in resting state functional connectivity (rsFC) values between the brain regions of interest and other brain regions in the SCA type 3 group and the normal control group, corrected for NBS. Spearman test was used to correlate significantly different rsFC values ( P<0.01) between the 2 groups and their clinical behavioral scores. Results:Compared with the normal control group, the AUC value of Cp for brain network connectivity was significantly increased in the SCA type 3 group ( Z=2.05, P=0.043), whereas the differences in γ, λ, σ, Eglob, Eloc, Lp, and homozygosity were not statistically significant between the 2 groups (all P>0.05). The SCA type 3 group had significantly lower nodal efficiency in the left precuneus ( t=-2.16, NBS corrected P=0.033) and left inferotemporal gyrus ( t=-2.25, NBS corrected P=0.027), and significantly higher nodal efficiency in the right lentiform nucleus ( t=2.05, NBS corrected P=0.043) and left middle temporal gyrus ( t=2.25, NBS corrected P=0.027) compared to normal control group. Significant alterations in rsFC values were found between multiple brain regions in SCA type 3 patients, correlating with clinical data and behavioral assessment scores. Conclusions:SCA type 3 patients exhibit specific alterations in brain functional networks, including changes in clustering coefficient and nodal efficiency. Furthermore, rsFC between brain regions correlates with behavioral abnormalities.
