New MRI Image Technique Predicts Early Onset of Alzheimer's Disease in Patients with Mild Memory Problems

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"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 analysing 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.


(Source: Neurobiology of Aging : Penn Medicine : August 2007)