Faculty, Staff and Student Publications
Publication Date
9-15-2022
Journal
Neuro-Oncology Advances
Abstract
BACKGROUND: For patients with brain tumors, maximizing the extent of resection while minimizing postoperative neurological morbidity requires accurate preoperative identification of eloquent structures. Recent studies have provided evidence that anatomy may not always predict eloquence. In this study, we directly compare transcranial magnetic stimulation (TMS) data combined with tractography to traditional anatomic grading criteria for predicting permanent deficits in patients with motor eloquent gliomas.
METHODS: We selected a cohort of 42 glioma patients with perirolandic tumors who underwent preoperative TMS mapping with subsequent resection and intraoperative mapping. We collected clinical outcome data from their chart with the primary outcome being new or worsened motor deficit present at 3 month follow up, termed "permanent deficit". We overlayed the postoperative resection cavity onto the preoperative MRI containing preoperative imaging features.
RESULTS: Almost half of the patients showed TMS positive points significantly displaced from the precentral gyrus, indicating tumor induced neuroplasticity. In multivariate regression, resection of TMS points was significantly predictive of permanent deficits while the resection of the precentral gyrus was not. TMS tractography showed significantly greater predictive value for permanent deficits compared to anatomic tractography, regardless of the fractional anisotropic (FA) threshold. For the best performing FA threshold of each modality, TMS tractography provided both higher positive and negative predictive value for identifying true nonresectable, eloquent cortical and subcortical structures.
CONCLUSION: TMS has emerged as a preoperative mapping modality capable of capturing tumor induced plastic reorganization, challenging traditional presurgical imaging modalities.
Keywords
anatomy, glioma, neurological deficit, tractography, transcranial magnetic stimulation
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Neurology Commons, Neurosciences Commons, Oncology Commons
Comments
PMID: 36128584