||Researchers from the University
of Pennsylvania School of Medicine and the National
Institute on Aging successfully detected mild cognitive disorder
(MCI) using new MRI techniques
to analyze tissue composition and structure in the brain.
||Mild cognitive disorder
causes mild memory
problems and is often an early symptom of Alzheimer’s
||In the first-of-its-kind study, researchers
created a unique picture of patients’ brains by combining
and analyzing MRI images measuring the density and volume of
various different tissues and their spatial distribution within
the brain. From these images patterns associated with MCI were
||Using this technique, researchers were able
to not only to detect, with 100 % accuracy, those patients in
the study with cognitive impairment from those with normal cognitive
function, but also those predicted, with 90 percent accuracy,
those patients with increasing onset of MCI.
||Results of the research were published in
a recent issue of Neurobiology
(PHILADELPHIA) — Using new MRI techniques
to analyze tissue composition and structure in the brain, researchers
from the Perelman School of Medicine and
the National Institute on Aging successfully detected mild cognitive disorder (MCI), a condition in which patients suffer mild memory
problems and is often an early symptom of Alzheimer’s disease
(AD). Results of the research were published in a recent issue
“This is important because detecting this kind of brain
abnormality in its early stages with these techniques could have
pivotal importance for the early detection and management of AD,” said
lead author of the study Christos
Davatzikos, MD, Chief
of the Biomedical Image
Analysis Section in Penn’s Department
of Radiology. “The diagnostic power of this technique
could work hand-in-hand with the new drugs currently under development
that target the early stages of AD before irreversible brain tissue
damage sets in.”
In the first-of-its-kind study, researchers created a unique picture
of patients’ brains by combining and analyzing MRI images
measuring the density and volume of various different tissues and
their spatial distribution within the brain. From these images
patterns associated with MCI were detected. Using this technique,
researchers were able to not only to detect, with 100 % accuracy,
those patients in the study with cognitive impairment from those
with normal cognitive function, but also those predicted, with
90 percent accuracy, those patients with increasing onset of MCI,
thereby demonstrating the diagnostic power of the new tool.
Up to now, the predictive power of MRI images relative to MCI
and AD have been limited because they compared region-by-region
evaluations over time and were not able to be applied on an individual
patient basis. The technique designed by the researchers provides,
for the first time, the sensitivity and specificity for individual
patient diagnosis of MCI leading to AD. Not only are the abnormalities
in the MCI brain detected earlier than other imaging techniques,
but can be identified and measured even before the patient’s
mental processes deteriorate to the point of clinical symptoms.
The ability to accurately classify even mildly impaired individuals
from a single cross-sectional MRI is significant because it contrasts
with prevailing thinking that effective prediction of early stages
of AD will require measurement of longitudinal brain changes. Frequent
follow-up is often difficult and expensive in a clinical setting.
This study demonstrated that an accurate diagnosis can be made
from a single MRI image.
“Our study is the first to show that by using MRI techniques
to classify tissue patterns in the brain provides very high diagnostic
accuracy on an individual basis,” added Davatzikos.
Prevalence of AD doubles every 5 years of life after the age of
60, with more than four million Americans affected. Definitive
diagnosis requires postmortem identification of amyloid plaques and neurofibrillary
tangles linked to the disease. Patients with
MCI, which include memory problems that do not meet criteria for
dementia, convert to AD with rates of 6 – 15 % annually.
This new method of analysis using MRI imaging to detect tissue
patterns, promises to aid in the early diagnosis and monitoring
of MCI and AD.
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Penn Medicine is one of the world’s leading academic medical centers, dedicated to the related missions of medical education, biomedical research, and excellence in patient care. Penn Medicine consists of the Raymond and Ruth Perelman School of Medicine at the University of Pennsylvania (founded in 1765 as the nation's first medical school) and the University of Pennsylvania Health System, which together form a $7.8 billion enterprise.
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