Altered Voxel-wise Brain Network Degree Centrality And Subcortical Nuclei Volume In Amyotrophic Lateral Sclerosis

BackgroundALS is a fairly rare degenerative disorder characterized by loss of upper and lower motor neurons.In recent,many studies have shown progressive lesions due to ALS are not limited to the upper and lower motor neurons,but spread to multiple systems including the prefrontal cortex,temporal lobe,parietal lobe and the basal ganglia involvement.there are many non-motor symptoms in ALS patients.The extrapyramidal symptoms in ALS has become a hot issue in recent years,Neuroimaging studies have found evidence of extrapyramidal involvement in ALS.The rsfMRI studies of ALS reported significantly decreased functional connectivity within the sensorimotor network and in brain networks related to cognition and behaviour,while other studies have identified regions of increased functional connectivity,including somatosensory and extra-motor areas.As these studies are based on networkwise functional connectivity analysis using seed-based correlation analysis or independent component analysis,none of these studies fully characterize the brain’s functional connectome of ALS.The majority of structural MRI studies implementing VBM and SBM techniques have found grey matter atrophy in the motor cortex of patients with ALS,while few volumetric changes involving the deep grey nuclei have been described in the ALS literature despite a reasonably large number of structural MRI studies.Recently,the graph theory-based network analysis was applied to characterize the functional relationships of a given node(voxel)within the entire connectivity matrix of full-brain functional connectome.The voxel-wise degree centrality(DC),a class of graph theory-based network measures assessing functional importance degree,has been widely used to detect changes in resting-state functional networks.FMRIB’s Integrated Registration and Segmentation Tool(FIRST),as a part of the FMRIB Software Library(FSL),is a model-based segmentation/registration tool.FIRST uses a shape model obtained from manually segmented images to guide the segmentation of the subcortical structures and can be used to esteem the volumetric alterations of subcortical structuresObjectiveIn the present study,the voxel-wise degree centrality(DC)measures of graph theory-based network is used to explore changes of whole brain resting-state functional networks in ALS patients,FSL-FIRST MR volumetric analysis is applied to assessment volumetric alterations of subcortical structures,While relationship between the extrapyramidal symptoms and the alterations of whole brain function network changes and subcortical structures’ volume in ALS are investigated to further more knowledge about ALS non-motor symptoms.Materials and MethodsⅠ.The voxel-wise DC analysis of graph theory-based network in resting state.ParticipantsAccording to the El Escorial criteria,forty-three sporadic ALS patients(30 definite,13 probable)were recruited consecutively from the Department of Neurology at Southwest Hospital in Chongqing,excluding family history of motor neuron diseases,clinical diagnosis of frontotemporal dementia and cognitive impairment,brain injury,epilepsy,or a neurologic disease and significant respiratory failure.Disease severity was assessed using the ALS Functional Rating Scale-Revised(ALSFRS-R).Forty-four age-and sex-matched healthy volunteers,with no history of neurological or psychiatric disorders and a normal neurological examination,were recruited from the local community served as HC.All the participants were right-handed.MRI acquisitionThe MRI data were acquired with a 3.0T Siemens Tim Trio whole-body MRI system.Whole-brain functional scans were collected in 36 axial slices by using an echo-planar imaging(EPI)sequence.Three dimensional T1-weighted anatomical images were acquired in a sagittal orientation using the following volumetric 3D magnetization-prepared rapid gradient–echo sequence.Data processingAll preprocessing steps and DC calculation were performed using the Data Processing Assistant for Resting-State fMRI(DPARSF2.3)based on the Statistical Parametric Mapping(SPM8)program and the Resting-State f MRI Data Analysis Toolkit(REST1.8).To exclude artifactual correlations from non-gray matter voxels,the voxel-wise DC analyses were restricted to a predefined gray matter mask that included tissue with gray matter probabilities more than 20%.Within the study mask,individual network centrality maps were created in a voxel-wise style.First,the preprocessed functional data sets were subjected to voxel-based whole-brain correlation analysis.The time course of each voxel within the gray matter mask from each participant was correlated with the time course of every other voxel,which generated a correlation matrix.An undirected adjacency matrix was then obtained by thresholding each correlation at r > 0.25.Then,the DC was computed as the sum of the weights of the significant correlations(weighted)or the number of significant connections(binarized)for each voxel.Finally,by subtracting the mean DC across the entire brain and then dividing by the standard deviation of the whole-brain DC,these individual-level voxel-wise DC maps were standardized into a z-score.A smoothing kernel of 4mm was applied.Statistical AnalysisTwo samples t-tests were performed to examine the differences between the DC measures of ALS group and HC group by REST1.8.Statistical significance was set at a voxel-wise p < 0.01 in conjunction with cluster wise Alpha Sim(rmm = 5,clusters =18)to correct for multiple comparisons.Pearson correlations(two-sided)were calculated between ALSFRS-R score and z-score of altered DC’s areas in ALS group with each patient’s age and gender as covariates.Ⅱ.Subcortical structure volumetric analysis in ALSParticipantsAccording to the revised El Escorial criteria.twenty-five patients(17 men,8 female)with the diagnosis of sporadic probable or definite ALS were consecutively recruited from the Department of Neurology at Southwest Hospital in Chongqing.Excluding history of family motor neuron diseases and clinical diagnosis of frontotemporal dementia and cognitive impairment,presence of other major systemic,psychiatric,or neurological illnesses.Clinical status of the patients was assessed by the ALS Functional Rating Scale-Revised(ALSFRS-R).Disease duration was calculated from symptom onset to scanning date in months,and the rate of disease progression was then determined as:(48 – ALSFRS-R)/disease duration.Twenty-five normal controls with no previous history of neurological or psychiatric diseases were recruited from the local community.All the participants were right-handed.MRI acquisition and Data processingMRI data scans were obtained on a 3.0 T Siemens Tim Trio(Siemens,Erlangen,Germany)with an eight-channel head coil.Anatomical image datasets were acquired for subcortical nuclei volumetric analysis with a standard T1-weighted high resolution anatomical scan using a magnetization prepared rapid gradient echo(MP-RAGE)sequence.Volume estimation for 7 bilateral subcortical structures including the nucleus accumbens,amygdala,caudate,hippocampus,pallidum,putamen,and thalamus,was performed by using FIRST Version 1.2 based on FSL Version 4.1.5(FMRIB Software Library).To reduce the effects of inter-individual variability in head size,individual total intracranial volume(TIV)was obtained with the SIENAX tool from the corresponding T1-weighted image.Statistical AnalysisAll statistical analyses were performed with the SPSS 17.0 software.Statistical differences in the subcortical nuclei volume between the groups were estimated by a multivariate analysis of covariance(MANCOVA)model with each participant’s age,gender,education years,and TIV as covariates.The MANCOVA model was defined by 1 between-subject factor and 14 dependent variables(each bilateral of the subcortical nuclei).The Bonferroni method was applied for multiple comparison correction.P value less than 0.05 was considered as significant.Pearson correlations(two-sided)were calculated between ALSFRS-R score and volume of altered subcortical structure in ALS group with each patient’s age and gender and education years as covariates.ResultsⅠ.In the present work,centrality analyses were performed for both binary and weighted graphs representing the functional connectome.Compared to the HC group in the weighted DC,significant increases of DC in ALS group were found in the left cerebellum posterior lobes,bilateral cerebellum crus,bilateral occipital poles(Brodmann area(BA)18/19),right orbital frontal lobe(BA11)and bilateral prefrontal lobes(BA8/9);significant decreases of DC in ALS group were found in the bilateral primary motor cortex(BA4/6),bilateral sensory motor region(BA3/5),right prefrontal lobe(BA45),left precuneus(BA5),bilateral lateral temporal lobes(BA48),left middle cingulate cortex(BA23),and bilateral visual processing cortex(BA17/18/37)(Figure1B,C;Table 3).The findings obtained from the binarized networks were similar to those obtained from the weighted networks.Correlation analysis shows that DC’s z-scores of Right inferior Occipital gyrus(area7,BA18)is negative correlated with the ALSFRS-R scores in both the binarized(p = 0.039,r =-0.0341)and weighted networks(p = 0.038,r =-0.342)of ALS group.Ⅱ.Subcortical structure volumetric analysis based on FSL-FIRST revealed a significant decreased volume in the bilateral thalamus(left p = 0.021,right p = 0.006),left hippocampus(p = 0.034),and right amygdala(p = 0.019)in ALS patients compared with controls.There was no significantly correlations between and volume of altered subcortical structure and ALSFRS-R score in ALS patients.ConclusionThe voxel-wise DC analysis of graph theory-based network in resting state confirm that the abnormal network DC in ALS patients was located in multiple brain regions including cortex related to motor function(the primary motor and cerebellum)and extra-motor areas(somatosensory,limbic system and visual areas),The alterd DC in right inferior occipital gyrus can probably be used to assess severity of ALS.Subcortical structure volumetric analysis revealed the subcortical structures are recruited in ALS patients.our study in vivo using MRI support the concept that ALS is a multi-system disorder and involve subcortical structures.the present work further more knowledge about ALS non-motor symptoms.