Intractable Epilepsy Advances Brain Aging

brain mri
brain mri
Structural MRI revealed differences in white matter in people with intractable epilepsy compared to healthy controls.

PHILADELPHIA —Epilepsy appears to advance brain aging by nearly 9 years in people with intractable focal seizures, data presented at the 2015 American Epilepsy Society Annual Meeting suggest.

However, the effect was not observed in people with new onset focal epilepsy, suggesting that ongoing seizures contribute to the biological phenomenon.

The study, led by Heath R. Pardoe, PhD, of NYU Langone Medical Center, and colleagues utilized multivariate analysis of structural MRI and a machine learning algorithm to predict brain age of participants with intractable epilepsy, new onset epilepsy, and healthy controls.

Participants were comprised of individuals with new onset focal epilepsy (n=20) from the Human Epilepsy Project, those with intractable focal epilepsy (n=18) being assessed for surgical resection, and healthy controls (n=20). Whole brain T1 weighted MRI was obtained for all participants, with two age estimates generated per subject based on white matter and gray matter segmentation. The PRONTO multivariate machine learning matlab toolbox predicted age based on data from healthy controls from large, public imaging databases.

Those with intractable epilepsy had a difference between predicted brain age and chronological age on average 8.8 years older than healthy controls (P= 0.003) based on white matter segments. No difference in predicted brain age was observed for patients with new onset epilepsy (-1.5 years, P= 0.55. No differences in predicted age were observed when using gray matter segments for both intractable epilepsy (0.84 years; P= 0.72) and new onset (-1.06 years; P= 0.64).

“This technique could potentially be used to identify individuals with intractable epilepsy early in the course of their disease,” Dr. Pardoe said, “and may also be useful for other applications like measuring the protective effect of antiepileptic medication.”

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Pardoe HR, Cole JH, Thesen T, Blackmon K, Kuzniecky R. Abstract 1.146. Do seizures age the brain? Machine learning analysis of structural MRI. Presented at: American Epilepsy Society Annual Meeting; Dec. 4-8, 2015; Philadelphia.