Wednesday, May 5, 2010

Using MRI to Predict Alzheimer’s

A new method of brain imaging identifies a pattern of regional brain atrophy in patients with mild cognitive impairment (MCI). The finding indicates a greater likelihood of progression to Alzheimer’s disease.

“Previously, this pattern has been observed only after a diagnosis of probable Alzheimer’s disease,” said the study’s lead author, Linda K. McEvoy, Ph.D, assistant project scientist in the Department of Radiology at the University of California San Diego School of Medicine in La Jolla.

“Our results show that some individuals with MCI have the atrophy pattern characteristic of mild Alzheimer’s disease, and these people are at higher risk of experiencing a faster rate of brain degeneration and a faster decline to dementia than individuals with MCI who do not show that atrophy pattern.”

According to the Alzheimer’s Association, more than five million Americans currently have Alzheimer’s disease. One of the goals of modern neuro-imaging is to help in early and accurate diagnosis, which can be challenging. There is no cure for Alzheimer’s disease, but when it is diagnosed early, drug treatment may help improve or stabilize patient symptoms.

In Alzheimer’s disease, nerve cell death and tissue loss cause areas of the brain to atrophy. Structural MRI allows radiologists to visualize subtle anatomic changes in the brain that signal atrophy. MCI is associated with an increased risk of progression to Alzheimer’s disease.

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Rates of progression vary. Some patients progress rapidly, while others remain stable for relatively long periods of time.

For the study, Dr. McEvoy and colleagues set out to determine if they could identify a pattern of regional atrophy characteristic of mild Alzheimer’s disease in order to aid in the prediction of cognitive decline in patients with MCI.

In the study, the researchers analyzed brain MR images from 84 patients with mild Alzheimer’s disease, 175 patients with MCI and 139 healthy controls, using with semi-automated, individually specific quantitative MRI methods. The results showed widespread cortical atrophy in some patients with MCI, involving all cortical areas except those involved with processing of primary motor and sensory information.

However, most indicative of future cognitive decline were atrophy in parts of the medial and lateral temporal lobes and in the frontal lobes. This pattern was also present in the patients with mild Alzheimer’s disease.

“Although these individuals are reporting problems mainly with memory, the atrophy involves more than just memory areas, extending into brain regions involved in planning, organization, problem solving and language,” Dr. McEvoy said.

Followup data were available for 160 patients with MCI. The patients exhibiting atrophy in the brain regions described above showed significant one-year clinical decline and structural brain loss and were more likely to progress to a probable diagnosis of Alzheimer’s disease. MCI patients without that pattern of atrophy remained stable after a year.

Dr. McEvoy hopes that these findings will have an impact on the design of clinical trials to test medications that may slow or halt the progression of Alzheimer’s disease.

“Currently there are no treatments that will prevent or cure Alzheimer’s disease, but information about risk of rapid decline may help patients with MCI and their families plan for the future,” Dr. McEvoy said.

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The latest 2009 study confirmed the findings several previous researches, producing similar outcomes. For example, the study of 2003 documents signatures of the early brain changes, occurring several years before the memory problems of early Alzheimer's actually show up.  These changes are caused by loss of brain cells, writes lead researcher Henry Rusinek, PhD, a professor of radiology at New York University School of Medicine in New York City. The researchers say that other studies have pointed to the medial temporal lobe, a small section of the brain, as being very vulnerable to the aging process. These studies show that these changes are also seen in the early stages of Alzheimer's disease. That means mean looking for these brain changes could help pinpoint who is likely to go on to develop Alzheimer's disease in the nearest future.

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MRI scans that detect shrinkage in specific regions of the mid-brain attacked by Alzheimer’s disease accurately diagnose the neurodegenerative disease, even before dementia symptoms interfere with daily function, a 2008 study by the Florida Alzheimer’s Disease Research Center (ADRC) in Miami and Tampa found.

“We advocate, based on these findings, that the criteria for the diagnosis of Alzheimer’s disease should include MRI scans,” said the study’s lead author Ranjan Duara, MD, medical director of the Wien Center for Alzheimer’s Disease and Memory Disorders at Mount Sinai Medical Centerhttp://kona.kontera.com/javascript/lib/imgs/grey_loader.gif. “By incorporating MRIs into the assessment of patients with memory problems, early diagnosis can be standardized and done far more accurately.”

“This study demonstrates that MRI brain scans are accurate enough to be clinically useful, both in diagnosing Alzheimer’s disease itself at an early stage and in identifying people at risk of developing Alzheimer’s,” said Florida ADRC Director Huntington Potter, PhD, a neuroscientist at the Byrd Alzheimer’s Center and Research Institute, University of South Florida.

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While locating the area of the AD marker place in the brain remains a most significant direction of research, the following analysis can be automated by using the special software.  Massachusetts General Hospital researchers are using automated MRI software to detect individuals in the preclinical phase of Alzheimer's disease with 95% accuracy.

Dr. Rahul Desikan, a researcher at MGH, and colleagues identified which regions of the brain are affected by AD and mild cognitive impairment in two patient groups of 97 and 216, respectively. Based on earlier pathological and imaging studies, the investigators confirmed that those with AD or MCI demonstrate a significant difference in thickness and volume in their entorhinal cortex, hippocampus, and supramarginal gyrus. The researchers then processed MRI scans of individuals with AD and MCI using FreeSurfer, open source software developed at MGH and the University of California, San Diego

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