Brain Atrophy Measures Predict Risk of Alzheimer's
Magnetic resonance imaging predicts progression of cognitive impairment to Alzheimer's disease
THURSDAY, April 7 (HealthDay News) -- Single-time-point or longitudinal magnetic resonance (MR) imaging measures can be used to predict which adults with mild cognitive impairment (MCI) are more likely to progress to Alzheimer's disease (AD), according to a study published online April 6 in Radiology.
Linda K. McEvoy, Ph.D., from the University of California in San Diego, and colleagues evaluated whether single-time-point and longitudinal MR imaging measures could predict progression from amnestic MCI to AD. They compared 164 patients with late-onset AD with 203 healthy controls by separate analyses of MR images obtained at one time point or combined single-time-point measures with change at one year to identify discriminatory functions. These were applied to 317 MCI cases to identify patient risk scores. The odds of conversion to AD from highest to lowest risk score quartiles were evaluated.
The investigators found that individualized risk estimates for one-year risk of conversion to AD at baseline ranged from 3 to 40 percent (average group risk, 17 percent; odds ratio [OR], 7.2 for highest compared to lowest score quartile). Risk estimates were significantly improved by including measures of one-year change in global and regional volumes. In the subsequent year, the risk of conversion to AD ranged from 3 to 69 percent (average group risk, 27 percent; OR, 12.0 for highest compared to lowest score quartiles).
"Patient-specific estimates of the risk of conversion from MCI to AD can be derived from quantitative measures of brain atrophy obtained from both single-time-point and serial MR imaging examinations," the authors write.
Several authors disclosed financial relationships with CorTech Labs, and one of the study authors disclosed financial relationships with the health care industry. Data from this study were obtained from the Alzheimer's Disease Neuroimaging Initiative database, which is funded by the pharmaceutical industry.