Study shows
hope for early diagnosis of Alzheimer’s
Newswise — Research by faculty and staff at
Rowan University, Glassboro, N.J.; the
University of Pennsylvania School of Medicine;
and Drexel University may lead to better
diagnosis of early-stage Alzheimer’s disease.
In a $1.1-million National Institutes of
Health’s National Institute on Aging study that
team members conducted during the last three
years, they determined early Alzheimer’s could
be diagnosed with a high rate of accuracy
evaluating electroencephalogram (EEG) signals.
The study may lead to an earlier diagnosis, and
therefore earlier treatment and improved quality
of life, for people at the earliest stages of
the disease.
According to the Alzheimer’s Association, the
condition affects more than 5 million Americans,
approximately 1.5 percent of the population.
That number is only expected to grow. (For
information on Alzheimer’s disease, visit
http://www.alz.org/documents/FSADFacts.pdf.)
Rowan University electrical and computer
engineering associate professor Dr. Robi
Polikar conducted the research with Dr.
Christopher Clark, associate professor of
neurology, associate director of the NIH-sponsored
Alzheimer's Disease Center at Penn and
director of the Penn Memory Center, and with
Dr. John Kounios, a Drexel psychology
professor.
“Individuals in the earliest stage of
Alzheimer’s disease are often not aware of their
progressing memory loss, and family members
often believe the changes are simply due to
aging,” Clark said.
“Even the patient’s personal physician may be
reluctant to initiate an evaluation until a
considerable degree of brain failure has
occurred. The advantage of using a modified EEG
to detect these early changes is that can it is
non-invasive, simple to do, can be repeated when
necessary and can be done in a physician’s
office. This makes it an ideal method to screen
elderly individuals for the earliest indication
of this common scourge of late life.”
The researchers employed signal processing and
automated neural network analysis of event
related potentials (ERPs) of the EEG signals,
monitoring how the patients’ brains reacted to a
series of auditory stimuli.
Clark’s team conducted neuropsychological tests,
including memory tests, of research subjects and
evaluated their scores to decide whether they
were suited for the study.
Kounios and his team acquired the EEG data from
the participants. They used a specific protocol,
called the “oddball paradigm with novel sounds,”
to collect the EEG signals, during which
patients hear a series of low- and
high-frequency tones as well as some novel
sounds. Patients were asked to respond by
pressing a button every time they heard the high
frequency tone, also known as the “oddball”
tone, which generates ERPs in the EEG.
Generally, in the ERP of a person without
Alzheimer’s, that response registers a peak, the
P300, about 300 milliseconds after the “oddball”
tone. People with dementia, particularly
Alzheimer’s, may exhibit that peak much later
than 300 milliseconds, show a much weaker peak
or have no peak at all, according to Polikar.
Kounios said the P300 signal is generated by
areas of the brain that seem to be attacked at
an early phase of Alzheimer’s disease, but the
results are not always conclusive.
Polikar and his students analyzed the data using
sophisticated signal processing, pattern
recognition and artificial intelligence
techniques to explore the hypothesis that the
entire ERP signal, not just the P300 indicator,
reveals markers that previously have not been
associated with Alzheimer’s disease.
The teams conducted several experiments,
ultimately evaluating the parietal and occipital
regions of the brains of 71 patients, some
already diagnosed with Alzheimer’s and some
without Alzheimer’s. Their diagnostic accuracy
rate was 82 to 85 percent using the EEGs (e.g.,
it matched evaluations conducted at Penn 82 to
85 percent of the time). Alzheimer’s disease
cannot be confirmed until a patient has died and
his or her brain has been examined. Gold
standard tests administered at world-class
research facilities, such as Penn, have a
90-percent accuracy rate. However, most people
are evaluated at community hospitals and
clinics, where the diagnostic accuracy is
estimated to be around 75 percent.
Though the study’s accuracy rate is under that
90-percent figure, it still means the test
potentially could have great value to physicians
and patients and their families, and the results
are particularly significant for patients who
have limited access to teaching hospitals, where
they may undergo six to 12 months of evaluation
for a diagnosis.
“Currently, the state-of-the-art evaluation for
Alzheimer’s disease is only available to those
who have geographic proximity and/or financial
ability to access research hospitals, where
expert neuropsychologists continuously interview
patients and caregivers over six to 12 months to
make a diagnosis,” said Polikar, principal
investigator on the project at Rowan. “But most
people don’t have access to such facilities and
instead go to community clinics and hospitals.
Our methodology involves just one ‘snapshot’
that in itself is highly accurate and will be
especially beneficial in these locations.”
"Modern engineering methods are enabling us to
take EEG, an 80-year-old technique for measuring
brain activity, and turn it into a cutting-edge
tool for diagnosing Alzheimer's disease,"
Kounios added.
The team members hope that eventually they or
other researchers will develop a hand-held
device that can be used to conduct similar
evaluations as those done by the
Rowan/Penn//Drexel group.
“We don’t envision this replacing a
neurologist,” Polikar said. “We hope it can
serve as a first test for those folks who don’t
have access to research facilities.” If the
initial test indicates a possible problem,
physicians could refer the patient to a research
hospital for further evaluation.
“Our ultimate goal is to increase the number of
patients who are diagnosed earlier so they can
start treatment sooner and slow the progress of
Alzheimer’s and improve their quality of life,”
Polikar said.
