{"title":"反应性神经刺激和深部脑刺激治疗癫痫的个体化规划。","authors":"Lara Wadi, Sandipan Pati, Shruti Agashe","doi":"10.1097/WNP.0000000000001195","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>Responsive neurostimulation and deep brain stimulation have emerged as effective intracranial neuromodulation therapies for drug-resistant epilepsy when surgical resection is not an option. However, programming these devices presents unique challenges in epilepsy. Without immediate feedback and a vast programming space, clinicians are often tasked with fine-tuning device settings without clear, mechanistic guidance and limited clinical time. Recent efforts toward individualized programming have shown promise, including the use of nonstandard parameter sets, target-specific stimulation strategies, and patient-tailored adaptations while avoiding unintended interference with critical functions such as emotional regulation. Emerging research in programming is shifting beyond the one-size-fits-all protocols, incorporating closed-loop biomarkers, integrating multimodal data and predictive modeling that hold promise for improving seizure control and reducing adverse effects. This review synthesizes current evidence on standard and individualized programming approaches for deep brain stimulation and responsive neurostimulation in epilepsy, highlighting practical strategies, clinical outcomes, and insights from recent studies. Although emerging tools such as biomarker-guided programming and predictive modeling are gaining interest, the focus of this review is on existing clinical literature shaping programming today.</p>","PeriodicalId":15516,"journal":{"name":"Journal of Clinical Neurophysiology","volume":"42 6","pages":"513-520"},"PeriodicalIF":1.7000,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Individualizing Programming of Responsive Neurostimulation and Deep Brain Stimulation Therapies in Epilepsy.\",\"authors\":\"Lara Wadi, Sandipan Pati, Shruti Agashe\",\"doi\":\"10.1097/WNP.0000000000001195\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Summary: </strong>Responsive neurostimulation and deep brain stimulation have emerged as effective intracranial neuromodulation therapies for drug-resistant epilepsy when surgical resection is not an option. However, programming these devices presents unique challenges in epilepsy. Without immediate feedback and a vast programming space, clinicians are often tasked with fine-tuning device settings without clear, mechanistic guidance and limited clinical time. Recent efforts toward individualized programming have shown promise, including the use of nonstandard parameter sets, target-specific stimulation strategies, and patient-tailored adaptations while avoiding unintended interference with critical functions such as emotional regulation. Emerging research in programming is shifting beyond the one-size-fits-all protocols, incorporating closed-loop biomarkers, integrating multimodal data and predictive modeling that hold promise for improving seizure control and reducing adverse effects. This review synthesizes current evidence on standard and individualized programming approaches for deep brain stimulation and responsive neurostimulation in epilepsy, highlighting practical strategies, clinical outcomes, and insights from recent studies. Although emerging tools such as biomarker-guided programming and predictive modeling are gaining interest, the focus of this review is on existing clinical literature shaping programming today.</p>\",\"PeriodicalId\":15516,\"journal\":{\"name\":\"Journal of Clinical Neurophysiology\",\"volume\":\"42 6\",\"pages\":\"513-520\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2025-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Clinical Neurophysiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/WNP.0000000000001195\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical Neurophysiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/WNP.0000000000001195","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Individualizing Programming of Responsive Neurostimulation and Deep Brain Stimulation Therapies in Epilepsy.
Summary: Responsive neurostimulation and deep brain stimulation have emerged as effective intracranial neuromodulation therapies for drug-resistant epilepsy when surgical resection is not an option. However, programming these devices presents unique challenges in epilepsy. Without immediate feedback and a vast programming space, clinicians are often tasked with fine-tuning device settings without clear, mechanistic guidance and limited clinical time. Recent efforts toward individualized programming have shown promise, including the use of nonstandard parameter sets, target-specific stimulation strategies, and patient-tailored adaptations while avoiding unintended interference with critical functions such as emotional regulation. Emerging research in programming is shifting beyond the one-size-fits-all protocols, incorporating closed-loop biomarkers, integrating multimodal data and predictive modeling that hold promise for improving seizure control and reducing adverse effects. This review synthesizes current evidence on standard and individualized programming approaches for deep brain stimulation and responsive neurostimulation in epilepsy, highlighting practical strategies, clinical outcomes, and insights from recent studies. Although emerging tools such as biomarker-guided programming and predictive modeling are gaining interest, the focus of this review is on existing clinical literature shaping programming today.
期刊介绍:
The Journal of Clinical Neurophysiology features both topical reviews and original research in both central and peripheral neurophysiology, as related to patient evaluation and treatment.
Official Journal of the American Clinical Neurophysiology Society.