Year: 2020
Type: dissertation
Abstract: BACKGROUND: \n \n \n \nSurgical treatment of Insular gliomas is technically challenging and may lead to high postoperative morbidity. However, previous research has proven that maximal safe resection is critical for maintaining quality of life as well as enhancing overall and progression-free survival. Insular gliomas are currently resected through either a transsylvian or transcortical approach. However, there is no objective evidence to aid surgical management to maximize safe resection rates. \n \n \nOBJECTIVES: \n \n \n \nTo define an optimal treatment strategy for the neurosurgical management of insular gliomas using a sequential research protocol. Phase A1- Design a custom embalming formula for preserving native brain features in cadavers to optimize the validity and clinical applicability of laboratory-based operative research. A2- Design a laboratory method to obtain objective data to assess -and compare- neurosurgical techniques in cadavers. Phase B- Define an optimal surgical technique for the management of each insular glioma of the Berger-Sanai classification system using our surgical simulation method in cadavers. Phase C- Validate the existing anatomical classification of insular gliomas to predict extent of resection (extent of resection) and anticipate neurological morbidity. \n \n \nMETHODS: \n \n \n \nWe aimed to provide sound objective evidence to the surgical management of insular gliomas through a multidisciplinary, sequential method including basic laboratory research, neurosurgical simulation using cadavers and a prospective clinical study. We first developed a customized embalming formula to create a neurosurgical simulation method that best resembles life surgery (a). We then used this optimized surgical simulation method to objectively determine and quantify the best surgical approach (transsylvian vs transcortical) for each type of insular tumor according to the Berger-Sanai insular glioma classification (b). Finally, we carried out a prospective clinical study to assess the predictability of the Berger-Sanai insular glioma classification regarding extent of resection and patient outcomes (c). \n \nRESULTS: \n \n \n \nWe designed an embalming solution that dramatically improved validity and applicability of research using neurosurgical simulation in cadavers. Our formula optimizes resemblance to life surgery (lower retraction pressure and greater retraction area) compared to the gold standard (formaldehyde). Our embalming method preserved specimens for significantly longer use than un-embalmed cadavers, which allows for complex research designs (such as Phase B of this work). We described cutting-edge surgical simulation techniques to objectivize surgical techniques in the laboratory. Our surgical simulation experiments show that the transcortical approach performs better than the transsylvian approach on all parameters for zones I and IV. On Zones II and III, cortical mapping and specific anatomical features may make the transsylvian approach more favorable. Our prospective clinical study showed that the Berger-Sanai insular glioma classification is a reliable tool to predict extent of resection (highest on zone I, IV) and postoperative complications (lowest on zone II and IV) following surgical treatment. \n \n \nCLINICAL AND SCIENTIFIC IMPACT: \n \n \n \nOverall, this work improved the field of neurosurgical simulation research by providing a detailed description of cadaver preparation (including public disclosure of the embalming chemical formula) and methodology to carry objective measurements to compare surgical techniques. For the first time, we provided objective data to aid the neurosurgeon in choosing the best surgical approach to maximize resection rates of insular gliomas tailored to the Berger-Sanai insular glioma classification. Finally, we validated the Berger-Sanai insular glioma classification as a tool to anticipate resection rates and postoperative neurological complications. As a whole, this work will substantially impact management of insular gliomas and patient informed decisions.
Author: Arnau Benet Cabero
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W3111692044