Age-related Changes Of Brain Structures In Normal Adults:Based On T1WIs And HARDI Data Study

PurposeTo explore the relationships between age and cerebral structure in normal aging,we used voxel-based morphometry(VBM)method and the surface-based morphometry(SBM)method to analyze the T1-weighted images data.The human brain,along with age increase,will appear to show changes of brain,such as the decline of gray matter volume(GMV),thinning of cortical thickness,decrease of gyrification indices(GI),and changes in the complexity of the cortex.To investigate the relationships between age and white matter tracts(WMT)in normal aging,we processed the high angular resolution diffusion imaging(HARDI)data based on diffusion tensor imaging(DTI),generalized q-sampling(GQI)and diffusion connectometry methods,respectively.And compare these methods differences in reflecting the changes of adults brain WMT in normal aging.Materials and MethodWe obtained the high-resolution T1-weighted images and high angular resolution diffusion imaging(HARDI)images data of 50 normal adults(27 females)aged 21–71 years.The CAT 12 software was used to analyze the T1-weighted data,using VBM and SBM methods.The former can obtain the GMV of the cerebral structure and the latter can obtain the cortical thickness,GI,and cortical complexity of the cerebral cortex.Linear regression was used to analyze the changing trend of GMV,cortical thickness,GI,and cortical complexity with age.These data were analyzed using DTI and GQI to obtain fractional anisotropy(FA),QA,fiber numbers,and fiber lengths for tract analysis and using q-space diffeomorphic reconstruction(QSDR)for the connectometry analysis.Associations between FA,QA,and fiber numbers and lengths and age were analyzed using Pearson's correlation coefficients.The diffusion connectometry analysis was conducted using a multiple linear regression analysis,including age and gender as factors.Uncorrected P-value/false discovery rate(FDR)(corrected for multiple comparisons)< 0.05 was considered statistically significant.We compared differences of DTI,GQI,and connectometry analysis to reflect WMT changes in aging.ResultsVBM analysis showed that the extensive GMV structure of the brain decreased with age,mainly in the frontal lobe,temporal lobe,parietal lobe,insular lobe,and subcutaneous hippocampus,parahippocampal gyrus,thalamus,and other structures;minor changes in the occipital lobe.The results of SBM analysis showed that the areas of thinning of the cortex were mainly in the frontal lobe,temporal lobe,precuneus,precentral gyrus,postcentral gyrus,paracentral gyrus,and lingual gyrus.In several regions,thinning was only present in was in the insula and part of the frontal lobe;the cortical complexity negatively correlated with age was mainly in the frontal lobe.More regional changes were detected in FA related to age than changes in QA(17 > 6 regions,P < 0.05).Fewer regional changes in fiber numbers and more changes of fiber lengths were observed for DTI than for GQI(5 < 8/10 > 7 regions,P < 0.05).However,DTI and GQI analyses revealed consistent results in some regions,including the genu of the corpus callosum(GCC),body of the corpus callosum(BCC),fornix(Fx),and anterior coronal radiation(ACR)(P < 0.05).The connectometry analysis showed more tract changes associated with age at an FDR of 0.05,which partially overlapped with the FA and QA.ConclusionThe GMV,cortical thickness,GI index of most regions in the brain structure showed negative correlation with age.VBM and SBM methods can detect changes in brain cortical structures,and may assist early identification of normal aging changes and age-related diseases.GQI and connectometry provide more information about age-related tracts;they can partialy complement the DTI findings and show more changes of WMT characteristics.