Follow-up MRI predicts neurological outcomes of cardiac arrest patients

Clinicians could predict the long-term neurological outcomes of cardiac arrest survivors with something as simple as a follow-up MRI, a study published this week in Radiology states.

An analysis of 46 patients across three hospitals in France and Belgium showed MR imaging within a month following cardiac arrest more accurately forecasted both favorable and unfavorable outcomes in patients who’d slipped into a coma following their heart failure, according to the paper.

Cardiac arrest (CA) survivors often suffer from brain damage, Robert D. Stevens, MD, and colleagues wrote in the study, since oxygenated blood flow to the brain is often cut off during such events, leading to widespread neuronal cell death.

“Survivors suffer from varying degrees of anoxic brain injury with long-term functional disability and cognitive impairment,” the authors wrote. “A challenge in the care of patients after CA is that individuals with similarly manifesting characteristics may have markedly different outcomes, ranging from death or states of chronically depressed consciousness to complete recovery.”

To evaluate the varying outcomes of CA on patients’ neurological health, Stevens and co-authors conducted multiparametric structural and functional MRIs in cardiac arrest patients an average of two weeks after they were admitted to the hospital. The researchers measured within- and between-network brain connectivity in four cranial regions—the dorsal attention network (DAN), default-mode network (DMN), salience network (SN) and executive control network (ECN)—through seed-based analysis on resting-state functional MRI data.

After 12 months, Stevens and colleagues wrote, 11 of the initial 46 patients had seen favorable outcomes. The researchers measured individuals’ progress with the Cerebral Performance Category Scale, which is commonly used to measure neurological function after cardiac arrest. Subjects who experienced the most favorable results had higher within-DMN connectivity, the scientists found, and greater anticorrelation between SN and DMN and SN and ECN when compared with patients who had less favorable outcomes.

But the most accurate predictor of a favorable outcome, the authors found, was anticorrelation of SN-DMN.

“Anti-correlation was preserved in patients who recovered and abolished in those who did not,” Stevens said in a release from the Radiological Society of North America. “Relative preservation of this anti-correlation was the most robust signal of a favorable outcome.”

These results suggest imaging information obtained in the acute phase of CA could be a novel biomarker for predicting the long-term recovery odds in affected patients.

“Current methods to predict future levels of function for these survivors have limited accuracy,” Stevens said. “This is game-changing information about what happens in the brains of people who suffer cardiac arrest."