Structural Imaging Measures of Brain Aging

被引:0
|
作者
Samuel N. Lockhart
Charles DeCarli
机构
[1] University of California at Davis,Department of Neurology and Center for Neuroscience
来源
Neuropsychology Review | 2014年 / 24卷
关键词
Aging; Brain imaging; Cognition;
D O I
暂无
中图分类号
学科分类号
摘要
During the course of normal aging, biological changes occur in the brain that are associated with changes in cognitive ability. This review presents data from neuroimaging studies of primarily “normal” or healthy brain aging. As such, we focus on research in unimpaired or nondemented older adults, but also include findings from lifespan studies that include younger and middle aged individuals as well as from populations with prodromal or clinically symptomatic disease such as cerebrovascular or Alzheimer’s disease. This review predominantly addresses structural MRI biomarkers, such as volumetric or thickness measures from anatomical images, and measures of white matter injury and integrity respectively from FLAIR or DTI, and includes complementary data from PET and cognitive or clinical testing as appropriate. The findings reveal highly consistent age-related differences in brain structure, particularly frontal lobe and medial temporal regions that are also accompanied by age-related differences in frontal and medial temporal lobe mediated cognitive abilities. Newer findings also suggest that degeneration of specific white matter tracts such as those passing through the genu and splenium of the corpus callosum may also be related to age-related differences in cognitive performance. Interpretation of these findings, however, must be tempered by the fact that comorbid diseases such as cerebrovascular and Alzheimer’s disease also increase in prevalence with advancing age. As such, this review discusses challenges related to interpretation of current theories of cognitive aging in light of the common occurrence of these later-life diseases. Understanding the differences between “Normal” and “Healthy” brain aging and identifying potential modifiable risk factors for brain aging is critical to inform potential treatments to stall or reverse the effects of brain aging and possibly extend cognitive health for our aging society.
引用
收藏
页码:271 / 289
页数:18
相关论文
共 50 条
  • [21] Reorganization of brain structural networks in aging: A longitudinal study
    Coelho, Ana
    Fernandes, Henrique M.
    Magalhaes, Ricardo
    Moreira, Pedro S.
    Marques, Paulo
    Soares, Jose M.
    Amorim, Liliana
    Portugal-Nunes, Carlos
    Castanho, Teresa
    Santos, Nadine Correia
    Sousa, Nuno
    JOURNAL OF NEUROSCIENCE RESEARCH, 2021, 99 (05) : 1354 - 1376
  • [22] Imaging of the aging brain and development of MRI signal abnormalities
    Chabriat, H.
    Jouvent, E.
    REVUE NEUROLOGIQUE, 2020, 176 (09) : 661 - 669
  • [23] Dopamine and cognitive functioning:: Brain imaging findings in Huntington's disease and normal aging
    Bäckman, L
    Farde, L
    SCANDINAVIAN JOURNAL OF PSYCHOLOGY, 2001, 42 (03) : 287 - 296
  • [24] Ranking Diffusion Tensor Measures of Brain Aging & Alzheimer's Disease
    Zavaliangos-Petropulu, Artemis
    Nir, Talia M.
    Thomopoulos, Sophia I.
    Jahanshad, Neda
    Reid, Robert I.
    Bernstein, Matthew A.
    Borowski, Bret
    Jack, Clifford R., Jr.
    Weiner, Michael W.
    Thompson, Paul M.
    14TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION PROCESSING AND ANALYSIS, 2018, 10975
  • [25] Structural MRI-Based Measures of Accelerated Brain Aging do not Moderate the Acute Antidepressant Response in Late-Life Depression
    Ahmed, Ryan
    Ryan, Claire
    Christman, Seth
    Elson, Damian
    Bermudez, Camilo
    Landman, Bennett A.
    Szymkowicz, Sarah M.
    Boyd, Brian D.
    Kang, Hakmook
    Taylor, Warren D.
    AMERICAN JOURNAL OF GERIATRIC PSYCHIATRY, 2022, 30 (09): : 1015 - 1025
  • [26] Motor control and aging: Links to age-related brain structural, functional, and biochemical effects
    Seidler, Rachael D.
    Bernard, Jessica A.
    Burutolu, Taritonye B.
    Fling, Brett W.
    Gordon, Mark T.
    Gwin, Joseph T.
    Kwak, Youngbin
    Lipps, David B.
    NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 2010, 34 (05): : 721 - 733
  • [27] Inter- and intra-individual variation in brain structural-cognition relationships in aging
    Patel, Raihaan
    Mackay, Clare E.
    Jansen, Michelle G.
    Devenyi, Gabriel A.
    O'Donoghue, M. Clare
    Kivimaeki, Mika
    Singh-Manoux, Archana
    Zsoldos, Eniko
    Ebmeier, Klaus P.
    Chakravarty, M. Mallar
    Suri, Sana
    NEUROIMAGE, 2022, 257
  • [28] Inter- and intra-individual variation in brain structural-cognition relationships in aging
    Patel, Raihaan
    Mackay, Clare E.
    Jansen, Michelle G.
    Devenyi, Gabriel A.
    O'Donoghue, M. Clare
    Kivimaki, Mika
    Singh-Manoux, Archana
    Zsoldos, Eniko
    Ebmeier, Klaus P.
    Chakravarty, M. Mallar
    Suri, Sana
    NEUROIMAGE, 2022, 257
  • [29] Structural brain aging in inbred mice: potential for genetic linkage
    Jucker, M
    Bondolfi, L
    Calhoun, ME
    Long, JM
    Ingram, DK
    EXPERIMENTAL GERONTOLOGY, 2000, 35 (9-10) : 1383 - 1388
  • [30] MRI assessment of whole-brain structural changes in aging
    Guo, Hui
    Siu, William
    D'Arcy, Ryan C. N.
    Black, Sandra E.
    Grajauskas, Lukas A.
    Singh, Sonia
    Zhang, Yunting
    Rockwood, Kenneth
    Song, Xiaowei
    CLINICAL INTERVENTIONS IN AGING, 2017, 12 : 1251 - 1270