Christoph Knoll, Juliane Doehler, Alicia Northall, Stefanie Schreiber, Johanna Rotta, Hendrik Mattern, Esther Kuehn
{"title":"Age-related differences in human cortical microstructure depend on the distance to the nearest vein.","authors":"Christoph Knoll, Juliane Doehler, Alicia Northall, Stefanie Schreiber, Johanna Rotta, Hendrik Mattern, Esther Kuehn","doi":"10.1093/braincomms/fcae321","DOIUrl":null,"url":null,"abstract":"<p><p>Age-related differences in cortical microstructure are used to understand the neuronal mechanisms that underlie human brain ageing. The cerebral vasculature contributes to cortical ageing, but its precise interaction with cortical microstructure is poorly understood. In a cross-sectional study, we combine venous imaging with vessel distance mapping to investigate the interaction between venous distances and age-related differences in the microstructural architecture of the primary somatosensory cortex, the primary motor cortex and additional areas in the frontal cortex as non-sensorimotor control regions. We scanned 18 younger adults and 17 older adults using 7 Tesla MRI to measure age-related changes in longitudinal relaxation time (T1) and quantitative susceptibility mapping (QSM) values at 0.5 mm isotropic resolution. We modelled different cortical depths using an equi-volume approach and assessed the distance of each voxel to its nearest vein using vessel distance mapping. Our data reveal a dependence of cortical quantitative T1 values and positive QSM values on venous distance. In addition, there is an interaction between venous distance and age on quantitative T1 values, driven by lower quantitative T1 values in older compared to younger adults in voxels that are closer to a vein. Together, our data show that the local venous architecture explains a significant amount of variance in standard measures of cortical microstructure and should be considered in neurobiological models of human brain organisation and cortical ageing.</p>","PeriodicalId":93915,"journal":{"name":"Brain communications","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11443451/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/braincomms/fcae321","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Age-related differences in cortical microstructure are used to understand the neuronal mechanisms that underlie human brain ageing. The cerebral vasculature contributes to cortical ageing, but its precise interaction with cortical microstructure is poorly understood. In a cross-sectional study, we combine venous imaging with vessel distance mapping to investigate the interaction between venous distances and age-related differences in the microstructural architecture of the primary somatosensory cortex, the primary motor cortex and additional areas in the frontal cortex as non-sensorimotor control regions. We scanned 18 younger adults and 17 older adults using 7 Tesla MRI to measure age-related changes in longitudinal relaxation time (T1) and quantitative susceptibility mapping (QSM) values at 0.5 mm isotropic resolution. We modelled different cortical depths using an equi-volume approach and assessed the distance of each voxel to its nearest vein using vessel distance mapping. Our data reveal a dependence of cortical quantitative T1 values and positive QSM values on venous distance. In addition, there is an interaction between venous distance and age on quantitative T1 values, driven by lower quantitative T1 values in older compared to younger adults in voxels that are closer to a vein. Together, our data show that the local venous architecture explains a significant amount of variance in standard measures of cortical microstructure and should be considered in neurobiological models of human brain organisation and cortical ageing.