Mathematical
modeling of brain scans of patients with Alzheimer's disease and others at risk
for the disorder has allowed the identification of three atrophy factor
patterns, based on the loss of gray matter throughout major areas of the brain,
which may help explain the variations in symptoms occurring in individual
patients. Credit: Xiuming Zhang, National University of Singapore
Mathematical
modeling of the brain scans of patients with Alzheimer's disease and others at
risk for the devastating neurodegenerative disorder has identified specific
patterns of brain atrophy that appear to be related to the loss of particular
cognitive abilities. In their report that has been published online in the Proceedings
of the National Academy of Sciences, a team of researchers at Massachusetts
General Hospital (MGH) and the National University of Singapore describe how
different atrophy patterns may explain the different ways that Alzheimer's
disease can be manifested in individual patients.
The
symptom severity and neurodegeneration can vary widely across patients in
Alzheimer's disease," says Thomas Yeo, PhD, of the Martinos Center for
Biomedical Imaging at MGH. "Our work shows that participants in this study
exhibit at least three atrophy patterns - cortical, temporal or subcortical -
that are associated with variability in cognitive decline not only in patients
diagnosed with Alzheimer's but also in individuals with mild cognitive
impairment or those who are cognitively normal but are at risk for
Alzheimer's." In addition to his affiliation with the Martinos Center, Yeo
is an assistant professor in the Department of Electrical and Computer
Engineering, Clinical Imaging Research Centre and Singapore Institute for
Neurotechnology at the National University of Singapore.
The
study analyzed data collected as part of the Alzheimer's Disease Neuroimaging
Initiative (ADNI), a multi-institutional project to develop biomarkers -
including blood tests, cerebrospinal fluid tests, and imaging studies - that
can be used for diagnosis or in clinical trials. Yeo and his team - including
investigators at the MGH and in Singapore - analyzed MR images taken of the
brains of 378 ADNI participants when they enrolled in the study. Of these
participants, 188 had been diagnosed with Alzheimer's disease; the others - 147
with mild cognitive impairment and 43 who were cognitively normal - were at
increased risk based on levels in their brains of the beta-amyloid plaques that
are characteristic of the disease.
As a
first step, the research team analyzed data from the baseline structural MRIs
using a mathematical model that estimated the probability that particular
details of each image were associated with atrophy of a specific location
within the brain. Based on the location of atrophy factors, they determined
three atrophy factor patterns: cortical - representing atrophy in most of the
cerebral cortex; temporal - indicating atrophy in the temporal cortex (the
cortical lobe behind the ears), hippocampus and amygdala; and subcortical,
indicating atrophy in the cerebellum, striatum and thalamus, structures at the
base of the brain.
Analysis
of study participant scans taken two years later indicated that atrophy factor
patterns were persistent in individuals and did not reflect different stages of
disease. Most participants - including those in the mild cognitive
impairment and cognitively normal groups - showed levels of more
than one atrophy factor.
"Most
previous studies focused on patients already diagnosed, but we were able to
establish distinct atrophy patterns not only in diagnosed patients but also in
at-risk participants who had mild impairment or were cognitively normal at the
outset of the study," Yeo says. "That is important because the
neurodegenerative cascade that leads to Alzheimer's starts years, possibly
decades, before diagnosis. So understanding different atrophy patterns among
at-risk individuals is quite valuable.
He adds,
"Previous studies assumed that an individual can only express a single
neurodegenerative pattern, which is highly restrictive since in any aged person
there could be multiple pathological factors going on at the same time - such
as vascular impairment along with the amyloid plaques and tau tangles that are
directly associated with Alzheimer's. So individuals who are affected by
multiple, co-existing pathologies might be expected to exhibit multiple atrophy
patterns."
Future research
could further determine whether and how these atrophy patterns relate to the
distribution of amyloid and tau and the mechanisms by which they affect
specific cognitive
abilities, Yeo explains. The same analytic approach also could be
applied to other types of patient data and extended to other neurodegenerative
disorder that produce varying symptom patterns, such as Parkinson's disease and
autism.
Journal reference: Proceedings of
the National Academy of Sciences
Provided by: Massachusetts
General Hospital
http://medicalxpress.com/news/2016-10-brain-atrophy-patterns-variability-alzheimers.html
No comments:
Post a Comment