MRI continues to play a pivotal role in the early detection of Alzheimer’s disease, and new research suggests that using distance measures from MRI data may outperform traditional volumetric assessments in predicting cognitive decline. A recent study explored how these novel MRI distance metrics could more effectively forecast future clinical status in individuals during the preclinical phase of Alzheimer’s disease.
Brain atrophy, a hallmark of Alzheimer’s, often begins years before noticeable cognitive symptoms emerge. Historically, researchers have relied on changes in brain volume or cortical thickness to quantify atrophy over time. However, the brain’s complex spatial and hierarchical organization means that degeneration doesn’t occur uniformly across regions. This complexity necessitates more nuanced methods of measurement.
In this study, researchers analyzed MRI data from cognitively normal individuals enrolled in the Preclinical Alzheimer’s Disease Consortium (PAC). Participants were followed over time, with some remaining cognitively normal and others progressing to mild cognitive impairment (MCI). The team employed various distance measures, mathematical metrics that quantify differences between brain structures over time, to model these trajectories. They adjusted for age, sex, education, and APOE genotype, ensuring a robust analysis.
The study used a two-step approach. First, individual models were created for different combinations of distance measures and brain regions, using future diagnostic status (normal vs. MCI) as the outcome. Second, these models were aggregated to generate an overall predictive estimate. Results demonstrated that distance measures consistently outperformed traditional volumetric assessments, both at the individual brain region level and in the combined models.
These findings highlight the potential of MRI distance metrics to capture the multidimensional aspects of brain atrophy more accurately, offering a promising new avenue for identifying individuals at risk for Alzheimer’s disease and related disorders before clinical symptoms manifest. This could lead to earlier interventions and more personalized approaches to care.
Reference: Chang J et al. MRI distance measures as a predictor of subsequent clinical status during the preclinical phase of Alzheimer’s disease and related disorders. Hum Brain Mapp. 2025;46(6):e70205.
