An algorithmic approach to preoperative studies and patient selection for hemispheric disconnection surgery: a literature review

Autor: Dario J. Englot, Andrew T. Hale, Luke Tomycz, Hael F. Abdulrazeq, Robert P. Naftel, Eric Segal
Rok vydání: 2020
Předmět:
Zdroj: Epileptic Disorders. 22:592-609
ISSN: 1950-6945
1294-9361
Popis: Hemispheric disconnection surgery (HDS) is one of the most effective surgical options for appropriate candidates with medically-refractory epilepsy (MRE) in whom most or all seizures arise from diffuse areas within a single hemisphere. While there are several well-accepted indications for HDS, there are additional patients who may benefit from HDS. However, there are no standardized recommendations for how preoperative studies should be used to identify appropriate candidates for HDS. We aimed to propose an algorithmic approach for presurgical evaluation in order to guide appropriate implementation of HDS for either cure or palliation of severe MRE in infants, children, and adults. We performed a qualitative review of the literature using PubMed, the Cochrane Library, and Google Scholar to select primary articles addressing imaging modalities used for the presurgical evaluation of patients with MRE being considered for HDS. In total, we identified 126 articles that met our inclusion criteria. We propose a framework to guide candidate selection for HDS that incorporates various elements of the clinical presentation, electroencephalographic analysis, and neuroimaging. While this approach still requires prospective validation, the authors feel it is grounded in a synthesis of the best available evidence in the literature and informed by expert opinion. HDS is a powerful tool in the armamentarium of experienced multi-disciplinary epilepsy centers to treat patients with severe MRE arising from diffuse areas constrained to a single hemisphere. The under-utilization of epilepsy surgery may be, in part, remedied by establishing evidence-based pathways for presurgical analyses to determine surgical candidacy.
Databáze: OpenAIRE