MR helps predict cerebrovascular disease

Twitter icon
Facebook icon
LinkedIn icon
e-mail icon
Google icon
 - brain sketch

Phase wave velocity (PWV) from the aortic arch obtained with phase-contrast MR imaging may prove a useful tool for determining the risk of cerebrovascular disease. In a study published in the June issue of Radiology, PWV was an independent predictor of subsequent white matter hyperintensity volume.

White matter hyperintensities are thought to result from cerebral microvascular disease and contribute to cognitive decline, stroke and mortality. Kevin S. King, MD, of the radiology department at the University of Texas Southwestern Medical Center in Dallas, and colleagues reasoned that phase-contrast MR imaging might provide insights in disease development by measuring PWV from the aortic arch, where cerebral circulation arises.

They speculated that PWV may predict white matter hyperintensity volume, independent of other cardiovascular risk factors such as hypertension, at a later point in time. To test their theory, they used the two-stage Dallas Heart Study. In the first stage, 2,596 participants received aorta and cardiac imaging plus clinical evaluation. In the second stage, conducted seven years later, a subset of 1,320 people underwent brain imaging.

King et al’s study included 1,270 participants from the second-stage study. Their outcome measure was white matter hyperintensity volume.

They found that, outside of age, aortic arch PWV was a primary independent predictor of subsequent white matter hyperintensity volume. “The results provide evidence of a link between large-vessel disease in the aortic arch and small-vessel disease in the brain,” they wrote.

Every 1 percent increase in aortic arch PWV was associated with a 0.29 percent increase in subsequent volume. The results also add to evidence that shows aortic stiffness as predictive of cardiovascular disease.

“Aortic PWV is a forceful marker that improves determination of risk for cardiovascular events both in indicating higher risk among those with otherwise low risk as well as further stratification among those already identified as at risk,” King et al wrote.

The study did not include baseline brain MR imaging from the first stage and used “relatively low” temporal imaging. The researchers recommended more research to confirm their findings, which then might provide a useful tool for stratifying risk and designing treatment plans.