Effects of age on tissues and regions of the cerebrum and cerebellum

Abstract

Normal volunteers, aged 30 to 99 years, were studied with MRI. Age was related to estimated volumes of: gray matter, white matter, and CSF of the cerebrum and cerebellum; gray matter, white matter, white matter abnormality, and CSF within each cerebral lobe; and gray matter of eight subcortical structures. The results were: 1) Age-related losses in the hippocampus were significantly accelerated relative to gray matter losses elsewhere in the brain. 2) Among the cerebral lobes, the frontal lobes were disproportionately affected by cortical volume loss and increased white matter abnormality. 3) Loss of cerebral and cerebellar white matter occurred later than, but was ultimately greater than, loss of gray matter. It is estimated that between the ages of 30 and 90 volume loss averages 14% in the cerebral cortex, 35% in the hippocampus, and 26% in the cerebral white matter. Separate analyses were conducted in which genetic risk associated with the Apolipoprotein E ⑀4 allele was either overrepresented or underrepresented among elderly participants. Accelerated loss of hippocampal volume was observed with both analyses and thus does not appear to be due to the presence of at-risk subjects. MR signal alterations in the tissues of older individuals pose challenges to the validity of current methods of tissue segmentation, and should be considered in the interpretation of the results.

MRI-based volumetry of head compartments: Normative values of healthy adults

“…It is also well known that the brain volume decreases with age in our sample by À113 ml/50 years (8.2%), which is similar to studies based on autopsy (Debakan and Sadowsky, 1978;Miller et al, 1980;Svennerholm et al, 1997) and MRI data (Blatter et al, 1995;Jernigan et al, 2001). This loss is more pronounced in the males than females and in the gray than the white matter compartment.…”

“…Following some initial studies using cranial computed tomography (CCT) (Abbott et al, 2000;Hahn et al, 1984;Schwartz et al, 1985), MRI quickly became the method of choice for data collection because MRI allows discriminating between several tissue types (Caviness et al, 1995(Caviness et al, , 1999Kennedy et al, 2003). Several studies focused on the determination of brain compartments and their gender differences (Allen et al, 2002(Allen et al, , 2003Blatter et al, 1995;Filipek et al, 1989Filipek et al, , 1994Sato et al, 2003;Schlaepfer et al, 1995) and changes of compartment volumes with age (Blatter et al, 1995;Courchesne et al, 2000;Ge et al, 2002;Giedd et al, 1996;Harris et al, 1994;Jernigan et al, 2001;Pfefferbaum et al, 1994;Resnick et al, 2003) and tried to find MRI-detectable discriminators of healthy and pathological aging in neurodegenerative diseases (Edland et al, 2002;Jenkins et al, 2000;Wolf et al, 2003Wolf et al, , 2004. Often these studies include a small sample size or a few parameters only.…”

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

“…The simplest and perhaps most intuitive type of analysis then requires the parcellation of the gray and white matter volumes into lobes, or sometimes into finer subdivisions, for regional quantification of tissue volumes (Fig. 2, panels 2a and 2b; see e.g., Giedd et al, 1999;Jernigan et al, 2001;Kennedy et al, 1998, for this type of approach). These brain volume measures can then be compared using standard statistical techniques, such as analysis of variance or multiple regression.…”

Non-treatment-seeking heavy drinkers: Effects of chronic cigarette smoking on brain structure

“…Studies with healthy adult controls generally reveal a linear decline of neocortical GM volume with increasing age (e.g., Courchesne et al, 2000;Jernigan et al, 2001). We used multivariate analysis of covariance (MANCOVA) with age as a covariate to control for age-volume relationships in all group comparisons.…”