Speakers: Bartosz Grobelny, MD

Bartosz Grobelny, MD


Saint Luke’s Health System


Bartosz Grobelny is a neurosurgeon at St. Luke’s Hospital in Kansas City specializing in epilepsy surgery. Originally from Poland, he immigrated to the United States as a child. He did his undergraduate studies at Columbia University in New York where he majored in both Physics and Neuroscience before undertaking his medical studies at Thomas Jefferson University in Philadelphia. He completed his neurosurgical residency at New York University Hospital and his Functional and Epilepsy Neurosurgery fellowship at Emory University Hospital. He has employed both conventional as well as minimally invasive approaches to diagnosis and treatment of focal epilepsy while employing both resective/ablative strategies in addition to neuromodulation. He was mentored in his clinical and research work during his residency by Drs. Howard Weiner and Werner Doyle at NYU and Drs. Bob Gross and Jon Willie at Emory. He has been interested by the applications of mathematical modelling to interpreting and visualizing brain activity and connectivity..

Imaging the Electrical Connections of the Brain in Surgical Epilepsy Patients as it Relates to Seizure Outcome

Objective: We sought to determine whether the presence or surgical removal of certain nodes in a connectivity network constructed from intracranial electroencephalography recordings determines postoperative seizure freedom in surgical epilepsy patients.
Methods: We analyzed connectivity networks constructed from peri-ictal intracranial electroencephalography of surgical epilepsy patients before a tailored resection. Thirty-six patients and 123 seizures were analyzed. Their Engel class postsurgical seizure outcome was determined at least one year after surgery. Betweenness centrality, a measure of a node’s importance as a hub in the network, was used to compare nodes.
Results: The presence of larger quantities of high-betweenness nodes in interictal and postictal networks was associated with failure to achieve seizure freedom from the surgery(p<0.001), as was resection of high-betweenness nodes in three successive frequency groups in mid-seizure networks(p<0.001).
Conclusions: Betweenness centrality is a biomarker for postsurgical seizure outcomes. The presence of high-betweeeness nodes in interictal and postictal networks can predict patient outcome independent of resection. Additionally, since their resection is associated with worse seizure outcomes, the mid-seizure network high-betweenness centrality nodes may represent hubs in self-regulatory networks that inhibit or help terminate seizures.