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Exactly 21 years have passed since John Besson’s chapter ‘Imaging’ in the previous edition of these seminars. There has been an amazing proliferation of imaging methods, but very little change in the clinical imaging protocols available to the average UK clinician. X-ray computed tomography (CT) still seems to be the mainstay of assessment in the standard psychiatric memory clinic. Magnetic resonance imaging (MRI) tends to be available, but only as a ‘special treat’, often mediated by neurologists, and emission tomography, such as single photon emission computerised tomography (SPECT) and positron emission tomography (PET), is only used in highly specialised cases outside a few academic centres. Apart from generic NHS austerity, ‘health without mental health’, and institutional ageism, what could be the reasons for this?
The contribution of education and intelligence to resilience against
age-related cognitive decline is not clear, particularly in the presence
of ‘normal for age’ minor brain abnormalities.
Method
Participants (n = 208, mean age 69.2 years, s.d. = 5.4)
in the Whitehall II imaging substudy attended for neuropsychological
testing and multisequence 3T brain magnetic resonance imaging. Images
were independently rated by three trained clinicians for global and
hippocampal atrophy, periventricular and deep white matter changes.
Results
Although none of the participants qualified for a clinical diagnosis of
dementia, a screen for cognitive impairment (Montreal Cognitive
Assessment (MoCA) <26) was abnormal in 22%. Hippocampal atrophy, in
contrast to other brain measures, was associated with a reduced MoCA
score even after controlling for age, gender, socioeconomic status, years
of education and premorbid IQ. Premorbid IQ and socioeconomic status were
associated with resilience in the presence of hippocampal atrophy.
Conclusions
Independent contributions from a priori risk (age,
hippocampal atrophy) and resilience (premorbid function, socioeconomic
status) combine to predict measured cognitive impairment.
Hypertension is associated with an increased risk of dementia and
depression with uncertain longitudinal associations with brain
structure.
Aims
To examine lifetime blood pressure as a predictor of brain structure in
old age.
Method
A total of 190 participants (mean age 69.3 years) from the Whitehall II
study were screened for hypertension six times (1985–2013). In 2012–2013,
participants had a 3T-magnetic resonance imaging (MRI) brain scan. Data
from the MRI were analysed using automated and visual measures of global
atrophy, hippocampal atrophy and white matter hyperintensities.
Results
Longitudinally, higher mean arterial pressure predicted increased
automated white matter hyperintensities (P<0.002).
Cross-sectionally, hypertensive participants had increased automated
white matter hyperintensities and visually rated deep white matter
hyperintensities. There was no significant association with global or
hippocampal atrophy.
Conclusions
Long-term exposure to high blood pressure predicts hyperintensities,
particularly in deep white matter. The greatest changes are seen in those
with severe forms of hypertension, suggesting a dose–response
pattern.
An increasing number of studies have examined the effects of training of cognitive and other tasks on brain structure, using magnetic resonance imaging.
Methods:
Studies combining cognitive and other tasks training with longitudinal imaging designs were reviewed, with a view to identify paradigms potentially applicable to treatment of cognitive impairment.
Results:
We identified 36 studies, employing training as variable as juggling, working memory, meditation, learning abstract information, and aerobic exercise. There were training-related structural changes, increases in gray matter volume, decreases, increases and decreases in different regions, or no change at all. There was increased integrity in white matter following training, but other patterns of results were also reported.
Conclusions:
Questions still to be answered are: Are changes due to use-dependent effects or are they specific to learning? What are the underlying neural correlates of learning, the temporal dynamics of changes, the relations between structure and function, and the upper limits of improvement? How can gains be maintained? The question whether neuroplasticity will contribute to the treatment of dementia will need to be posed again at that stage.
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