In vivo stereological assessment of caudate volume in man: Effect of normal aging

doi:10.1016/0024-3205(90)90196-X

Life Sciences

Volume 47, Issue 15, 1990, Pages 1325-1329

https://doi.org/10.1016/0024-3205(90)90196-X Get rights and content

Abstract

Using intermediate weighted magnetic resonance imaging (MRI) and a systematic sampling stereological method in 39 normal volunteers aged 24–79 years old, we demonstrated a marked age-associated decline in caudate nuclei volume (r = −0.69, p < 0.0001). The mean absolute volume of the caudate nuclei in this study (9.4 cm³) was almost identical to that reported in a previous autopsy study and further confirms the validity of this stereological technique for use with MR images. This technique will provide a method for measuring the caudate and other nuclei $in vivo$ , from brain images and, as such, a research tool to correlate age-associated changes in cognitive, sensory and motor function with caudate nucleus volume and other brain regions.

References (20)

E.T. Rolls et al.
Behav. Brain Res.
(1983)
B. Kolb
Physiol. Behav.
(1977)
D. Denny-Brown
The Basal Ganglia and Their Relation to Disorders of Movement
(1962)
I. Divac et al.
J. Comp. Physiol. Psychol.
(1963)
D. Rogers et al.
Brain
(1987)
J.E. Doppelt et al.
J. Abnormal Social Psychology
(1955)
E.D. Caine et al.
Am. J. Psychiatry
(1983)
S.E. Folstein et al.
Adv. Neurol.
(1979)
H.J.G. Gundersen et al.
J. Microscopy
(1987)
L. Regeur et al.
J. Microscopy
(1989)

There are more references available in the full text version of this article.

Cited by (69)

Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques
2021, NeuroImage
Citation Excerpt :
The brain structures that most reliably exhibited age-related changes included the putamen, thalamus, and caudate nucleus, which are important structures involved in relaying a variety of information across the brain, in sensorimotor coordination, and in higher cognitive functions (Grahn et al., 2008; Sefcsik et al., 2009; Sherman and Guillery, 2002). A number of stereological and MRI studies have reported atrophy in subcortical regions associated with aging, specifically in the putamen (Bugiani et al., 1978), amygdala (Coffey et al., 1992; Fjell et al., 2013), hippocampus (Fjell et al., 2013; Nobis et al., 2019), caudate nucleus (Krishnan et al., 1990), substantia nigra (McGeer et al., 1977), thalamus (Sullivan et al., 2004; Fjell et al., 2013), and cerebellum (Andersen et al., 2003; Good et al., 2001; Torvik et al., 1986). Recent studies using large subject cohorts have also reported an age-related decrease in the hippocampal and temporal lobe volumes (Nobis et al., 2019).
Brain age prediction studies aim at reliably estimating the difference between the chronological age of an individual and their predicted age based on neuroimaging data, which has been proposed as an informative measure of disease and cognitive decline. As most previous studies relied exclusively on magnetic resonance imaging (MRI) data, we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves age prediction using a large cohort of healthy subjects (N = 613, age 18–88 years) from the Cam-CAN repository. To this end, we examined the performance of dimensionality reduction and multivariate associative techniques, namely Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), to tackle the high dimensionality of neuroimaging data. Using MEG features (mean absolute error (MAE) of 9.60 years) yielded worse performance when compared to using MRI features (MAE of 5.33 years), but a stacking model combining both feature sets improved age prediction performance (MAE of 4.88 years). Furthermore, we found that PCA resulted in inferior performance, whereas CCA in conjunction with Gaussian process regression models yielded the best prediction performance. Notably, CCA allowed us to visualize the features that significantly contributed to brain age prediction. We found that MRI features from subcortical structures were more reliable age predictors than cortical features, and that spectral MEG measures were more reliable than connectivity metrics. Our results provide an insight into the underlying processes that are reflective of brain aging, yielding promise for the identification of reliable biomarkers of neurodegenerative diseases that emerge later during the lifespan.
Sex-specific patterns of age-related cerebral atrophy in a nonhuman primate Microcebus murinus
2020, Neurobiology of Aging
Steadily aging populations result in a growing need for research regarding age-related brain alterations and neurodegenerative pathologies. By allowing a good translation of results to humans, nonhuman primates, such as the gray mouse lemur Microcebus murinus, have gained attention in this field. Our aim was to examine correlations between atrophy-induced brain alterations and age, with special focus on sex differences in mouse lemurs. For cerebral volumetric measurements, in vivo magnetic resonance imaging was performed on 59 animals (28♀♀/31♂♂) aged between 1.0 to 11.9 years. Volumes of different brain regions, cortical thicknesses, and ventricular expansions were evaluated. Analyses revealed significant brain atrophies with increasing age, particularly around the caudate nucleus, the thalamus, and frontal, parietal, and temporo-occipital regions. Especially old females showed a strong decline in cingulate cortex thickness and had higher values of ventricular expansion, whereas cortical thickness of the splenium and occipital regions decreased mainly in males. Our study, thus, provides first evidence for sex-specific, age-related brain alterations in a nonhuman primate, suggesting that mouse lemurs can help elucidating the mechanism underlying sex disparities in cerebral aging, for which there is mixed evidence in humans.
Trajectories of imaging markers in brain aging: the Rotterdam Study
2018, Neurobiology of Aging
Citation Excerpt :
The development of noninvasive imaging techniques has fueled research into the aging brain in healthy individuals. Since magnetic resonance imaging (MRI) was first introduced in biomedical research in the 1980s, several pioneers performed small studies using this novel technique to assess macrostructural brain changes in aging (Gur et al., 1991; Jernigan et al., 1990, 1991; Krishnan et al., 1990; Pfefferbaum et al., 1994; Sullivan et al., 1995). After approximately one decade, large cross-sectional studies and population-based studies followed to inform about, for example, sex differences and brain changes in a large sample of healthy volunteers, instead of specific control subjects (Coffey et al., 1998; Good et al., 2001; Mu et al., 1999).
With aging, the brain undergoes several structural changes. These changes reflect the normal aging process and are therefore not necessarily pathologic. In fact, better understanding of these normal changes is an important cornerstone to also disentangle pathologic changes. Several studies have investigated normal brain aging, both cross-sectional and longitudinal, and focused on a broad range of magnetic resonance imaging (MRI) markers. This study aims to comprise the different aspects in brain aging, by performing a comprehensive longitudinal assessment of brain aging, providing trajectories of volumetric (global and lobar; subcortical and cortical), microstructural, and focal (presence of microbleeds, lacunar or cortical infarcts) brain imaging markers in aging and the sequence in which these markers change in aging. Trajectories were calculated on 10,755 MRI scans that were acquired between 2005 and 2016 among 5286 persons aged 45 years and older from the population-based Rotterdam Study. The average number of MRI scans per participant was 2 scans (ranging from 1 to 4 scans), with a mean interval between MRI scans of 3.3 years (ranging from 0.2 to 9.5 years) and an average follow-up time of 5.2 years (ranging from 0.3 to 9.8 years). We found that trajectories of the different volumetric, microstructural, and focal markers show nonlinear curves, with accelerating change with advancing age. We found earlier acceleration of change in global and lobar volumetric and microstructural markers in men compared with women. For subcortical and cortical volumes, results show a mix of more linear and nonlinear trajectories, either increasing, decreasing, or stable over age for the subcortical and cortical volume and thickness. Differences between men and women are visible in several parcellations; however, the direction of these differences is mixed. The presence of focal markers show a nonlinear increase with age, with men having a higher probability for cortical or lacunar infarcts. The data presented in this study provide insight into the normal aging process in the brain, and its variability.
Brain atrophy in Alzheimer's Disease and aging
2016, Ageing Research Reviews
Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used in clinical routine and research field, largely contributing to our understanding of the pathophysiology of neurodegenerative disorders such as Alzheimer’s disease (AD). This review aims to provide a comprehensive overview of the main findings in AD and normal aging over the past twenty years, focusing on the patterns of gray and white matter changes assessed in vivo using MRI. Major progresses in the field concern the segmentation of the hippocampus with novel manual and automatic segmentation approaches, which might soon enable to assess also hippocampal subfields. Advancements in quantification of hippocampal volumetry might pave the way to its broader use as outcome marker in AD clinical trials. Patterns of cortical atrophy have been shown to accurately track disease progression and seem promising in distinguishing among AD subtypes. Disease progression has also been associated with changes in white matter tracts. Recent studies have investigated two areas often overlooked in AD, such as the striatum and basal forebrain, reporting significant atrophy, although the impact of these changes on cognition is still unclear. Future integration of different MRI modalities may further advance the field by providing more powerful biomarkers of disease onset and progression.
Subcortical volumetric changes across the adult lifespan: Subregional thalamic atrophy accounts for age-related sensorimotor performance declines
2015, Cortex
Even though declines in sensorimotor performance during healthy aging have been documented extensively, its underlying neural mechanisms remain unclear. Here, we explored whether age-related subcortical atrophy plays a role in sensorimotor performance declines, and particularly during bimanual manipulative performance (Purdue Pegboard Test). The thalamus, putamen, caudate and pallidum of 91 participants across the adult lifespan (ages 20–79 years) were automatically segmented. In addition to studying age-related changes in the global volume of each subcortical structure, local deformations within these structures, indicative of subregional volume changes, were assessed by means of recently developed shape analyses. Results showed widespread age-related global and subregional atrophy, as well as some notable subregional expansion. Even though global atrophy failed to explain the observed performance declines with aging, shape analyses indicated that atrophy in left and right thalamic subregions, specifically subserving connectivity with the premotor, primary motor and somatosensory cortical areas, mediated the relation between aging and performance decline. It is concluded that subregional volume assessment by means of shape analyses offers a sensitive tool with high anatomical resolution in the search for specific age-related associations between brain structure and behavior.
In vivo glutamate measured with magnetic resonance spectroscopy: Behavioral correlates in aging
2013, Neurobiology of Aging
Citation Excerpt :
These findings support the contention that lower striatal Glu levels might represent fewer or less effective corticostriatal projections. This interpretation is also supported by evidence for age-related striatal volume loss that has not been shown as attributable to loss of medium spiny neurons (Brabec et al., 2003; de Jong et al., 2010; Krishnan et al., 1990; Raz et al., 2003b). If striatal volume loss with age is not because of loss of medium spiny neurons, it might instead reflect volume loss because of fewer cortical glutamatergic fibers in the striatum.
Altered availability of the brain biochemical glutamate might contribute to the neural mechanisms underlying age-related changes in cognitive and motor functions. To investigate the contribution of regional glutamate levels to behavior in the aging brain, we used an in vivo magnetic resonance spectroscopy protocol optimized for glutamate detection in 3 brain regions targeted by cortical glutamatergic efferents—striatum, cerebellum, and pons. Data from 61 healthy men and women ranging in age from 20 to 86 years were used. Older age was associated with lower glutamate levels in the striatum, but not cerebellum or pons. Older age was also predictive of poorer performance on tests of visuomotor skills and balance. Low striatal glutamate levels were associated with high systolic blood pressure and worse performance on a complex visuomotor task, the Grooved Pegboard. These findings suggest that low brain glutamate levels are related to high blood pressure and that changes in brain glutamate levels might mediate the behavioral changes noted in normal aging.

View all citing articles on Scopus

View full text

In vivo stereological assessment of caudate volume in man: Effect of normal aging

Abstract

Behav. Brain Res.

Physiol. Behav.

The Basal Ganglia and Their Relation to Disorders of Movement

J. Comp. Physiol. Psychol.

Brain

J. Abnormal Social Psychology

Am. J. Psychiatry

Adv. Neurol.

J. Microscopy

J. Microscopy