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The medical director of the Arkansas Children’s Comprehensive Epilepsy Program detailed advancements and strategies in using neuromodulation for LGS, as well as the future research needed to expand these approaches. [WATCH TIME: 4 minutes]
WATCH TIME: 4 minutes
"Artificial intelligence could help identify which patients are likely to be super responders, paving the way for personalized neuromodulation strategies."
Despite the array of available high efficacy antiseizure medications, many patients with Lennox-Gastaut syndrome (LGS) struggle to control their seizures. Alternate invasive neuromodulatory options include vagus nerve stimulation (VNS), deep brain stimulation (DBS), and responsive neurostimulation (RNS). VNS has been in use the longest, receiving FDA approval in 1997 for focal, drug-resistant epilepsy and extended approval in 2017 for children over 4 years old.
Earlier this year, members of the Pediatric Epilepsy Research Consortium (PERC) convened to publish a new guidance paper on the use of neuromodulation in LGS. One of the specific focuses was on initiation and titration strategies, as well as emerging data on combining multiple neuromodulation modalities. For initiation, devices are usually activated at low electrical stimulation levels to minimize side effects such as discomfort, nausea, or local irritation. Parameters like frequency, pulse width, and intensity are carefully chosen based on patient tolerance and seizure response.
Recently, lead author Depobam Samanta, MD, MS, FAAP, FAES, sat down to discuss more about initiation and titration protocols for devices like VNS and DBS. Samanta, medical director of the Arkansas Children’s Comprehensive Epilepsy Program, highlighted practical insights on optimizing stimulation settings, utilizing new features like automated scheduling, and the potential of novel approaches like low-frequency, long-duration stimulation for non-responders. Additionally, the conversation delved into challenges in advancing neuromodulation research and the promising role of artificial intelligence in improving patient and device selection.