What if patients had the ability to know beforehand, if they had symptoms of Alzheimer's disease? What if a simple MRI scan could determine and distinguish between the different types of degenerative disease that afflict more than 4.5 million people in the U.S. each year?

Does it sound too farfetched? Well, not to a group of research at the Mayo Clinic (Rochester, Minnesota). Early results from a study completed by the team show that there is a high percentage chance that a special MRI-based framework the research center developed can differentially diagnose three of the most common neurodegenerative disorders, Alzheimer's disease, front to temporal lobar degeneration, and Lewy body disease.

Currently, examination of the brain at autopsy is the only way to confirm with certainty that a patient had a specific form of dementia.

The framework, which is called the Structural Abnormality index, or STAND-Map, shows promise in accurately diagnosing dementia patients in life. The rationale is that if each neurodegenerative disorder can be associated with a unique pattern of atrophy specific on MRI, then it may be possible to differentially diagnose new patients.

"It's just a proof of concept, it really works well," Prashanthi Vemuri, PhD, a senior research fellow at the Mayo Clinic aging and dementia imaging research lab and the lead author of the study said in an audio press conference.

Vemuri was joined by fellow researchers Clifford Jack, MD, Kejal Kantarci, MD; Matthew Senjem; Jeffrey Gunter; Jennifer Whitwell, PhD; Keith Josephs, MD; David Knopman, MD; Bradley Boeve, MD; Tanis Ferman, PhD.; Dennis Dickson, MD; and Ronald Petersen, PhD, MD.

Their work was supported in part by National Institutes of Health (NIH) grants, Robert H. Smith Family Foundation Research Fellowship, Alexander Family Alzheimer's Disease Research Professorship.

The team released results of the study and gave details about the STAND-Map last weekend at the Alzheimer's Association (Chicago) International Conference on Alzheimer's Disease (ICAD) held in Vienna, Austria.

Their study looked at 90 patients from the Mayo Clinic database that were confirmed to have only a single dementia pathology and also underwent an MRI at the time of clinical diagnosis of dementia.

Researcher's followed patients all the way from diagnosis to death. When the team received autopsies on each patient, they went back and reviewed the imaging that had been done. The team then compared those results with the patients' MRI images that had been taken throughout the years. From this method they were able to develop the STAND-Map.

"The developed system is trying to establish a direct relationship between the gold standard in dementia diagnosis which is post mortem brains and ante mortem before death MRI scans," Vemuri said.

But the million dollar question for researchers is, are the structures of the brain distinguishably different for the symptoms of degenerative disease?

Vemuri and her team seem to think so.

She added that once the group found "that specific regions of the brain were unique to each dementia disorder we could go back and, given a new incoming scan, we could say with some probability that this person might have Alzheimer's disease."

The release of the result comes at a time when the number of people with Alzheimer's and dementia – both new cases and total numbers with the disease – continues to rise among the very oldest segments of the population in contradiction of the conventional wisdom, according to research reported at the ICAD

Previous epidemiological studies have suggested that the number of people with Alzheimer's and dementia begins to level off and perhaps even go down a bit in people age 90 and above, known as the "oldest old." This is the fastest growing segment of the population in western countries.

But despite this news, Vemuri and the team said that they have a valuable resource to perhaps forewarn patients.

She said, "The early results indicate that the accuracy is 75% to 85%, but we need to test it further and test it on a large number of people to see if it really works or not. But it's really promising and we hope we can really make a difference."