The inability to turn off certain brain regions, rather than decline in the ability to turn them on, could be the clue to diagnosing Alzheimer’s disease, according to Duke University researchers. Findings from a 4T functional MR imaging trial suggest this brain marker, not structural ones such as atrophy, could help diagnosis and management of AD patients.
The inability to turn off certain brain regions, rather than decline in the ability to turn them on, could be the clue to diagnosing Alzheimer's disease, according to Duke University researchers. Findings from a 4T functional MR imaging trial suggest this brain marker, not structural ones such as atrophy, could help diagnosis and management of AD patients.
Functional MRI consistently shows reduced activation of the hippocampi in AD patients. The test, however, has shown either increased or decreased activation of the hippocampi and other brain regions involved in cognitive function in patients with mild cognitive impairment, which often precedes AD.
Functional MRI is useful to understand how memory networks in the brain deteriorate as AD progresses, but to reach diagnostic potential it should identify brain regions whose activation or deactivation magnitude correlate with cognitive function in healthy subjects and patients with MCI and AD, according to lead investigator Dr. Jeffrey R. Petrella, an associate professor of radiology at Duke.
Petrella and colleagues prospectively enrolled 75 subjects with a mean age of 72.9 years. The group comprised 13 patients with AD, 34 patients with MCI, and 28 healthy controls. All subjects completed a neuropsychological test and later underwent 4T fMRI scanning while performing an associative memory task.
Researchers found that activation in the medial temporal lobe became increasingly impaired as patients progress from MCI to AD. The most striking finding, however, was an increasingly impaired deactivation in the posteromedial cortices, an area that suppresses its activity in healthy individuals during a memory task. The investigators published their findings in the October issue of Radiology.
"In other words, the brain not only loses its ability to turn on in certain regions but also loses its ability to turn off in others, and the latter may be a more sensitive marker. These findings give us insight into how the brain's memory networks break down, remodel, and finally fail as memory impairment ensues," Petrella said.
Functional MRI showed that activation in the medial temporal lobe, including the hippocampus and parahippocampal and fusiform gyri, decreased along the spectrum from control subjects to MCI patients to AD patients. Conversely, fMRI showed increasing activation in the posteromedial cortices of MCI and AD patients, respectively, primarily in the precuneus and posterior cingulate gyrus. The correlation between activation magnitude and the neuropsychological test score was statistically significant (p<0.001).
As new therapies for Alzheimer's disease enter the pipeline over the next five years, early diagnosis will become critical for patient selection. Functional MRI may play a key role in early diagnosis, Petrella said.
The next step is to conduct a large multicenter study to see if fMRI can be combined with other imaging modalities and clinical and genetic tests to scan for future disease, said coauthor Dr. P. Murali Doraiswamy, chief of Duke's biological psychiatry division.
"Much like a negative colonoscopy gives you reassurance, a normal fMRI may in the future also offer predictive value," Doraiswamy said.
For more information from the Diagnostic Imaging archives:
fMRI tests assumptions about behavior and thought
Early results from Alzheimer's neuroimaging studies could speed research
PIB-PET opens diagnostic front in Alzheimer's disease
Can MRI-Based AI Enhance Pre-Op Prediction of Tumor Deposits in Patients with Rectal Cancer?
October 31st 2024For patients with rectal cancer, an emerging nomogram that combines deep learning and clinical factors had greater than 16 percent and 23 percent increases in accuracy and specificity, respectively, for pre-op prediction of tumor deposits in comparison to clinical factors alone.
Can Diffusion MRI Predict Patient Response to Neoadjuvant Chemotherapy for Breast Cancer?
October 23rd 2024A model emphasizing time-dependent diffusion MRI was 15 percent more effective than apparent diffusion coefficient (ADC) measurements at predicting pathologic complete response to neoadjuvant chemotherapy for women with breast cancer, according to new research.