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MRI: neurological outcomes for cardiac arrest survivors could be predicted

Anaesthesiology

According to the American Heart Association, cardiac arrest is the major cause of death in the millions in the U.S. alone. The cardiac arrest survivors were found to have severe neurological disabilities. The temporary loss of oxygenated blood flow to the brain resulted in the neuronal cell death.

Robert D. Stevens from Johns Hopkins University School of Medicine mentioned, "Current methods to predict future levels of function for these survivors have limited accuracy." To understand the magnitude of these injuries and make more accurate predictions on recovery and make more informed decision-making, better techniques are required.

In the study, more advanced MRI techniques were used by Dr. Stevens and colleagues. Diffusion tensor imaging and resting-state functional MRI (fMRI) was used to determine the brain's large-scale functional integration. This "network of networks," or connectome, represents the ensemble of different neuronal populations in the brain that work together to perform tasks.

In 46 patients who were in a coma following cardiac arrest were assessed for the brain’s functional connectivity. The MRI was performed within two weeks of cardiac arrest and the brain structure and function was studied. The default mode network (active when a person is not engaged in a specific task) and the salience network (select which stimuli are deserving of our attention) were examined through functional imaging.

The Cerebral Performance Category Scale was used to assess the cardiac arrest survivors after one year in which 11 patients had favorable outcomes. Functional connectivity was stronger in those who achieved higher levels of independence at one year compared with those who were heavily dependent. The changes in functional connectivity between networks predicted outcomes with greater accuracy than any of the MRI structural measures tested.

Dr. Stevens was amazed seeing the outcomes. The network architectures can be selectively disrupted in the setting.

The interaction between the brain's default mode and salience networks predicted the outcomes. These two networks are normally anti-correlated. As the default mode network becomes more active, activity is reduced in the salience network, and vice versa. On comparing the brain imaging results of patients who had favorable outcomes, a stark difference was noticed.

"Anti-correlation was preserved in patients who recovered and abolished in those who did not," Dr. Stevens said. "Relative preservation of this anti-correlation was the most robust signal of a favorable outcome."

The researchers said that the outcomes indicate that connectivity measures could be early markers of long-term recovery potential in patients with cardiac arrest-related brain damage.

Connectome analysis with MRI is not the only solution to predicting outcomes, while the confidence which clinicians have in communicating with patients' families in the wake of cardiac arrest could be increased. Besides, fMRI aids in the development of therapeutic interventions for neurologically disabled patients. Dr. Stevens conclude, connectome studies potentially change the outcome prediction and guide treatment.

Measuring the functional connections in the brain could aid in predicting neurological outcomes for cardiac arrest survivors