Automated Analysis Of Brain Scans May Identify Early Alzheimer’s Disease

May 22, 2009

Adapted from Massachusetts General Hospital

Analyzing MRI studies of the brain with software developed at the Martinos Center for Biomedical Imaging at Massachusetts General Hospital (MGH) may allow diagnosis of Alzheimer's disease and of mild cognitive impairment, a lesser form of dementia that precedes the development of Alzheimer's by several years.

In their report that appears in the journal Brain and has been released online, the research team shows how their software program can accurately differentiate patients with mild cognitive impairment or Alzheimer's disease from normal elderly individuals based on anatomic differences in brain structures known to be affected by the disease.

"Traditionally Alzheimer's has been diagnosed based on a combination of factors—such as a neurologic exam, detailed medical history and written tests of cognitive functioning—with neuroimaging used primarily to rule out other diseases such as stroke or a brain tumor," says Rahul Desikan M.D., Ph.D., of the Martinos Center and Boston University School of Medicine, lead author of the Brain paper. "Our findings show the feasibility and importance of using automated, MRI-based neuroanatomic measures as a diagnostic marker for Alzheimer's disease."

The researchers note that mild cognitive impairment occurs in about 20 percent of elderly individuals—as many as 40 percent of those over 85 – 80 percent of whom develop Alzheimer's within five or six years. Since drugs that may slow the progression of Alzheimer's are in development, the ability to treat patients in the earliest stages of the disease may significantly delay progression to dementia. To investigate whether MR imaging can produce diagnostic markers for mild cognitive impairment and Alzheimer's disease, the research team used FreeSurfer—an openly available imaging software package developed at the Martinos Center and the University of California at San Diego—to examine a number of neuroanatomic regions across a range of normal individuals and patients with mild cognitive impairment and Alzheimer's disease.

"Our results indicate that these automated MRI measures are one effective way of identifying individuals in the earliest stages of Alzheimer's disease, but before this technology can be used clinically, several follow-up studies need to be done," says Desikan. "Those include determining whether these automated MRI measures can accurately predict which individuals with mild cognitive impairment will progress to Alzheimer's; seeing if they can differentiate Alzheimer's from other neurodegenerative diseases; assessing how these measures do at early diagnosis, compared to other measures such as cellular biomarkers; and then validating all of these findings against the gold standard for diagnosis, postmortem examination of brain tissue."

View all news updates for Alzheimer's disease