FMRI Study Of Spontaneous Brain Activity In Patients With Parkinson’s Disease Based On Dynamic And Static Low Freque Ncy Amplitude Fluctuation Algorithm

Background and purposeParkinson’s disease（PD）is the most common progressive neurodegenerative disease after Alzheimer’s disease.It is now considered to be a systemic disease characterized by impaired motor and non-motor functions.The impaired motor function,being still the typical clinical symptoms of PD and relieved by levodopa treatment,is believed to be caused by the significant loss of dopaminergic neurons in the nigra striatum pathway,including bradykinesia,static tremor,rigidity,and postural and gait abnormalities.The non-motor function impairment that does not respond to levodopa treatment can show symptoms of multiple system dysfunction which are atypical and the related mechanisms of which are unclear,which brings some challenges to the clinical diagnosis and treatment of PD.At present,although there are a series of hypotheses about the pathogenesis of PD,the pathogenesis of PD is still not clear.In order to deepen the understanding of PD,that evaluating the disease progression and optimizing the treatment plan is of great value to study the pathophysiological mechanism of PD.Resting state functional magnetic resonance imaging（RS-fMRI）can be used to detect the spontaneous brain activity,which has become an accepted method to explore functional neuroanatomy in the past ten years.RS-fMRI has been widely used to study the effects of neurodegenerative diseases on the brain,and many related studies have attempted to reveal the functional abnormalities of key brain regions related to the pathophysiology of PD.In this study,dynamic low frequency fluctuation amplitude（dALFF）and low frequency fluctuation amplitude（ALFF）methods were used to conduct RS-fMRI data analysis to explore the brain regions with local spontaneous neural activity changes in PD patients,and further reveal the possible pathophysiological mechanism.In addition,the correlation analysis between the signal values of the brain regions with statistical differences and the scores of the clinical scale were conducted to explore the value of the two analysis methods in evaluating the disease progression and cognitive impairment of PD patients.Materials and methods1.74PD patients and 83 healthy controls with gender,age and head movement matching were included in this study.According to Hoehn-Yahr（H-Y）grading score,PD patients were further divided into 30 patients with early stage（H-Y grading≤2）and 44 patients with advanced stage（H-Y grading>2）.The subjects’ MRI data were collected on Siemens 3.0T Prisma magnetic resonance device with a 64-channel head-and-neck combined coil.All PD patients were evaluated by H-Y,UPDRS and MMSE clinical scales.2.Based on MATLAB platform,preprocessing of RS-fMRI data and the calculation of ALFF were conducted by DPARSF 4.3 Advanced Edition module in the brain image data preprocessing and analysis tool kit dpabi.dALFF was calculated by Dynamic BC.3.Statistical analysis:ANCOVA analysis and pair-wise comparison between groups were performed on SPM12 with gender,age and average head movement as covariables.The results were corrected by GRF correction（voxel threshold PVoxel<0.005,cluster threshold Pcluster<0.05,double-tail）,and the brain regions with differences between the three groups and between each two groups were obtained.The extraction of Signal values in the brain regions with statistical differences between the three groups was based on the ROI Signal Extractor in the DPABI/Utilities module.Based on SPSS 25,Spearman correlation analysis was performed to analyze the correlation between the signal values of brain regions with statistical differences among the three groups and clinical scale scores（the test level a was 0.05,and the difference was statistically significant when P<0.05）.Results1.Compared with the healthy control group,the dALFF time variability in the Cerebelum_45L,Vermis₃ and Vermis₄₅ was decreased in the early PD group,the ALFF values in Temporal_Inf_L,SupraMarginal_R and Caudate_L were increased,and the ALFF values in Supp_Motor_Area_R were decreased.The temporal variability of dALFF in the Olfactory_L,Rectus_R,Pallidum_L,Insula_R,pontine,Cerebelum_45L,Vermis₃ and Vermis₄₅ and the ALFF value in Supp_Motor_Area_R in the advanced stage PD group were higher than that in early PD group.Compared with healthy controls,dALFF time variability of the middle-late PD group in Temporal_Inf_L,Temporal_Inf_R,Temporal_Sup_R,Insula_R,Frontal_Med_Orb_R,Fusiform_L,Rectus_L,Rectus_R,Olfactory_L,Putamen_L,Caudate_R,Pallidum_L,Thalamus_R,pontine,Cerebelum_45L,Vermis₃ and Vermis₄₅ and the ALFF value of Temporal_Inf_L,Olfactory_L,Rectus_L,SupraMarginal_R,Caudate_L were increased.2.Among the brain regions with statistical differences in dALFF time variability among the three groups,the signal values of Frontal_Med_Orb_R,Rectus_L,Rectus_R,Putamen_L and Caudate_R were significantly negatively correlated with the H-Y grading score（P<0.05）,with the signal values of Frontal_Med_Orb_R correlated with UPDRS score,while the signal values of the other brain regions were no significant correlation with the scores of all clinical scales（P>0.05）.The signal values of the brain regions with statistical differences in ALFF among the three groups were no significant correlation with the scores of all clinical scales（P>0.05）.Conclusions1.Patients with Parkinson’s disease have already shown static and dynamic changes in local spontaneous brain activity at an early stage,and the range of altered brain regions gradually expands with the progression of the disease.2.dALFF time variability is more sensitive to the detection of local spontaneous brain activity changes in PD patients than ALFF,and the combination of the two indexes can provide similar and complementary information for the interpretation of the possible pathophysiological mechanism of PD3.To a certain extent,dALFF time variability can be used to evaluate the severity of PD.