PET Helps Predict Progression from MCI to Alzheimer’s Disease

July 21, 2014

Brain PET and age may help clinicians determine which patients with amnestic mild cognitive disorder may progress on to probable Alzheimer’s disease.

A positive [18F]flutemetamol PET scan for brain amyloid and patient age are highly significant indicators of the risk of earlier progression from amnestic mild cognitive impairment (aMCI) to probable Alzheimer’s Disease (pAD), according to study data presented at the Alzheimer’s Association International Conference 2014 (AAIC).

Researchers from Nova Southeastern University, University of Pennsylvania and the Wien Center for Alzheimer’s Disease and Memory Disorders sought to determine if they could use [18 F]flutemetamol images to identify subjects with aMCI who would be at high risk of progressing to Alzheimer’s disease.

A total of 232 participants with aMCI participated in the phase 3 study. They all received a [18F]flutemetamol injection and underwent brain scans. These images were read by five independent blinded readers who classified the images as [18F]flutemetamol negative or positive for the presence of brain amyloid. The researchers evaluated age, ApoE genotype and aMCI stage. The participants were followed on-site every six months for three years or until progression to pAD.

The results showed the odds were about 2.6 to 1 that subjects with positive [18F]flutemetamol scans would convert to pAD earlier than those with negative scans. “Patient age was highly significant in predicting conversion to pAD for each reader whereas ApoE status was not,” according to the authors. “Subjects with late-stage aMCI were more likely to progress to pAD than those with early-stage aMCI.”

“These findings demonstrate the potential role of [18F]flutemetamol in stratifying those patients at higher risk of developing Alzheimer’s disease, beyond its use as a diagnostic tool,” lead investigator David Wolk, MD, assistant director at Penn Memory Center, said in a release.

“In addition to providing patients with potentially important prognostic information about their likelihood of developing dementia, identifying high risk patients could help guide physicians’ recommendations for patient monitoring, care plans and use of diagnostic resources. These are exciting results, but we need further research to fully understand how this might be used in clinical practice.”