100 research outputs found
Quantifying structural changes in the ageing brain from magnetic resonance imaging
Understanding the ageing process is of increasing importance to an ageing society and
one aspect of this is investigating what role the brain has in this process. Cognitive
ability declines as we age and it is one of the most distressing aspects of getting older.
Brain tissue deterioration is a significant contributor to lower cognitive ability in late
life but the underlying biological mechanisms in the brain are not yet fully
understood. One reason for this is the difficulty in obtaining accurate measures of
potential ageing-related brain biomarkers.
The chapters in this thesis explore the difficulties of quantifying brain changes in the
ageing brain from Magnetic Resonance Imaging (MRI), and how the changes
identified are related to cognition in later life. The data was acquired as part of the
second wave of the longitudinal Lothian Birth Cohort 1936 study in which 866 people
aged 73 years, returned for cognitive and medical assessment. At this stage of the
study 702 underwent MR imaging resulting in 627 complete datasets across all
testing. The entire data, a randomly chosen subset of 150 and 416 freely available data
were used to investigate global and regional measurement methods in older brains and
how the resultant measurements related to cognitive performance. Furthermore the
presence of early life cognitive data in the form of a general intelligence test sat at age
11, served as an indicator of cognitive ability prior to the potential influence of the
ageing process.
The chapters concerning global measures at first establish, that a measure of
intracranial volume (ICV) serves as both a way of correcting for individual
differences in brain size between participants and as a proxy premorbid measure of
brain size. The analysis, utilising freely available cross-sectional MRI data
(http://www.oasis-brains.org) revealed that ICV differed very little between 18-28
year olds and 84-96 year olds where as total brain tissue volume (TBV) differed by
14.1% between the two groups, which was more than twice the standard deviation
across the entire age range (18-96 years). Second a validated, reliable method for
measuring ICV was investigated using 150 people randomly chosen from the
LBC1936 study. Automated and semi-automated methods were validated against
reference measurements the results of which showed that common ageing features
make automated and semi-automated methods that do not have an additional manual
editing step, ineffective at producing accurate ICV measurements. This analysis also
highlighted the need to employ additional spatial overlap assessment to volumetric
comparison of measurement methods to reduce the effect of false-positives and false-negatives
skewing apparent discrepancies between methods. Using the information
gained here ICV and TBV from the entire LBC1936 cohort were analysed in a
structural equation model, alongside cognitive ability measures at both age 11 and age
73. We found that TBV was a stronger predictor of later life cognitive ability, after
accounting for early life ability, but that a modest association remained between ICV
and late life cognition. This suggests that early life factors pay a role in how well we
age, though the relationship is complex.
The regional measures chapters look at two brain regions commonly associated with
ageing, the hippocampus and the frontal lobes. Measuring either of these brain regions
in large samples of healthy older adults is challenging for many reasons. The
hippocampus is small and as with all brain regions shows greater variation in older
age, this makes employing automated methods that have the advantage of being fast
and reproducible difficult. Following the results of our systematic review of
automated methods for measuring the hippocampus, the two most commonly used
and available automated methods were validated against reference standard
measurements. The results indicated that although automated methods present an
attractive alternative to laborious manual measurements they still require manual
editing to produce accurate measurements in older adults. The modified strategy
employed across the LBC1936 was to use an automated method and then manually
edit the output; these segmentations were used to investigate the potential of
multimodal image analysis in clarifying associations between the hippocampus and
cognitive ability in old age. The analysis focused on associations between longitudinal
relaxation time (T1), magnetization transfer ratio (MTR), fractional anisotropy (FA)
and mean diffusivity (MD) in the hippocampus and general factors of fluid
intelligence, cognitive processing speed and memory. The findings show that multi-modal
MRI assessments were more sensitive than volumetric measurements at
detecting associations with cognitive measures.
The difficulty with producing a relevant frontal lobe measure was made apparent
when the result of a large systematic review looking at the manual protocols used
revealed 19 methods and 15 different landmarks had been employed. This resulted in
an analysis that took the 5 most common boundaries reported and applied them to 10
randomly selected participants from the LBC1936. The results showed significant
differences between the resultant volumes, with the smallest measurement when using
the genu as the posterior marker representing only 35% of the measurement acquired
using the central sulcus. The results from the studies presented in this thesis strongly
highlight the need to develop age specific methods when using brain MRI to study
ageing. Furthermore the implications of using unstandardised protocols, making
assumptions about a methods performance based on validation in younger samples
and the need to account for early life factors in this area of research have been made
clearer. Studies building on these findings will be beneficial in elucidating the role of
the brain in ageing
Blood Pressure, Internal Carotid Artery Flow Parameters, and Age-Related White Matter Hyperintensities
White matter hyperintensities (WMH) are associated with hypertension. We examined interactions between blood pressure (BP), internal carotid artery (ICA) flow velocity parameters and WMH. We obtained BP measurements from 694 community-dwelling subjects at mean ages 69.6 (±0.8) and again at 72.6 (±0.7) years, plus brain MRI and ICA ultrasound at age 73±1 years. Diastolic and mean BP decreased and pulse pressure increased but systolic BP did not change between 70 and 73 years. Multiple linear regression, corrected for vascular disease and risk factors, showed that WMH at age 73 were associated with history of hypertension (β=0.13, p<0.001) and with BP at age 70 (systolic β=0.08, mean β=0.09, diastolic β=0.08, all p<0.05); similar but attenuated associations were seen for BP at age 73. Lower diastolic BP and higher pulse pressure were associated with higher ICA pulsatility index at age 73 (diastolic BP: standardized β, age 70=−0.24, p<0.001; pulse pressure age 70 β=0.19, p<0.001). WMH were associated with higher ICA pulsatility index (β=0.13, p=0.002) after adjusting for BP and correction for multiple testing. Therefore falling diastolic BP and increased pulse pressure are associated with increased ICA pulsatility index, which in turn is associated with WMH. This suggests that hypertension and WMH may either associate indirectly because hypertension increases arterial stiffness which leads to WMH over time, or co-associate through advancing age and stiffer vessels, or both. Reducing vascular stiffness may reduce WMH progression and should be tested in randomised trials, in addition to testing antihypertensive therapy
Association of allostatic load with brain structure and cognitive ability in later life
AbstractAllostatic load (AL) has been proposed as a general framework for understanding the cumulative effects of life stress on individuals. Despite growing interest in AL, limited research has been conducted on aging samples. We consider the association of AL (operationalized by a range of inflammatory, cardiovascular, and metabolic measures) with a range of brain volume measurements and cognitive ability in a large cohort sample of older adults (n = 658, mean age = 72.5 years, standard deviation = 0.7) using structural equation modeling. AL was significantly inversely associated with total brain volume (range of standardized β = −0.16 to −0.20) and white-matter volume (−0.35 to −0.36) and positively with hippocampal volume (0.10–0.15) but not gray-matter volume (0.04). AL was also significantly inversely associated with general cognitive ability (range β = −0.13 to −0.20), processing speed (−0.20 to −0.22), and knowledge (−0.18 to −0.20) but not memory or nonverbal reasoning. The associations of AL with cognitive abilities were not mediated by these brain volume measures. AL did not predict cognitive change from age 11 to approximately age 73. The findings suggest a link between AL and later life brain health and cognitive functioning
Volumetric and correlational implications of brain parcellation method selection:a 3-way comparison in the frontal lobes.
OBJECTIVE: The aims of this study were to compare distinct brain frontal lobe parcellation methods across 90 brain magnetic resonance imaging scans and examine their associations with cognition in older age. METHODS: Three parcellation methods (Manual, FreeSurfer, and Stereology) were applied to T1-weighted magnetic resonance imaging of 90 older men, aged ∼73 years. A measure of general fluid intelligence (g(f)) associated with dorsolateral frontal regions was also derived from a contemporaneous psychological test battery. RESULTS: Despite highly discordant raw volumes for the same nominal regions, Manual and FreeSurfer (but not Stereology) left dorsolateral measures were significantly correlated with g(f) (r > 0.22), whereas orbital and inferior lateral volumes were not, consistent with the hypothesized frontal localization of g(f). CONCLUSIONS: Individual differences in specific frontal lobe brain volumes—variously measured—show consistent associations with cognitive ability in older age. Importantly, differences in parcellation protocol for some regions that may impact the outcome of brain-cognition analyses are discussed
3D shape analysis of the brain's third ventricle using a midplane encoded symmetric template model
AbstractBackgroundStructural changes of the brain's third ventricle have been acknowledged as an indicative measure of the brain atrophy progression in neurodegenerative and endocrinal diseases. To investigate the ventricular enlargement in relation to the atrophy of the surrounding structures, shape analysis is a promising approach. However, there are hurdles in modeling the third ventricle shape. First, it has topological variations across individuals due to the inter-thalamic adhesion. In addition, as an interhemispheric structure, it needs to be aligned to the midsagittal plane to assess its asymmetric and regional deformation.MethodTo address these issues, we propose a model-based shape assessment. Our template model of the third ventricle consists of a midplane and a symmetric mesh of generic shape. By mapping the template's midplane to the individuals’ brain midsagittal plane, we align the symmetric mesh on the midline of the brain before quantifying the third ventricle shape. To build the vertex-wise correspondence between the individual third ventricle and the template mesh, we employ a minimal-distortion surface deformation framework. In addition, to account for topological variations, we implement geometric constraints guiding the template mesh to have zero width where the inter-thalamic adhesion passes through, preventing vertices crossing between left and right walls of the third ventricle. The individual shapes are compared using a vertex-wise deformity from the symmetric template.ResultsExperiments on imaging and demographic data from a study of aging showed that our model was sensitive in assessing morphological differences between individuals in relation to brain volume (i.e. proxy for general brain atrophy), gender and the fluid intelligence at age 72. It also revealed that the proposed method can detect the regional and asymmetrical deformation unlike the conventional measures: volume (median 1.95ml, IQR 0.96ml) and width of the third ventricle. Similarity measures between binary masks and the shape model showed that the latter reconstructed shape details with high accuracy (Dice coefficient ≥0.9, mean distance 0.5mm and Hausdorff distance 2.7mm).ConclusionsWe have demonstrated that our approach is suitable to morphometrical analyses of the third ventricle, providing high accuracy and inter-subject consistency in the shape quantification. This shape modeling method with geometric constraints based on anatomical landmarks could be extended to other brain structures which require a consistent measurement basis in the morphometry
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