Abstract
The classical way for surgical selection and planning in cerebral glioma mainly focused on tumor topography. The emerging science of connectomics, which aims of mapping brain connectivity, resulted in a paradigmatic shift from a modular account of cerebral organization to a meta-network perspective. Adaptive behavior is actually mediated by constant changes in interactions within and across large-scale delocalized neural systems underlying conation, cognition, and emotion. Here, to optimize the onco-functional balance of glioma surgery, the purpose is to switch toward a connectome-based resection taking account of both relationships between the tumor and critical distributed circuits (especially subcortical pathways) as well as the perpetual instability of the meta-network. Such dynamic in the neural spatiotemporal integration permits functional reallocation leading to neurological recovery after massive resection in structures traditionally thought as “inoperable.” This better understanding of connectome increases benefit/risk ratio of surgery (i) by selecting resection in areas deemed “eloquent” according to a localizationist dogma; (ii), conversely, by refining intraoperative awake cognitive mapping and monitoring in so-called non-eloquent areas; (iii) by improving preoperative information, enabling an optimal selection of intrasurgical tasks tailored to the patient’s wishes; (iv) by developing an “oncological disconnection surgery”; (v) by defining a personalized multistep surgical strategy adapted to individual brain reshaping potential; and (vi) ultimately by preserving environmentally and socially appropriate behavior, including return to work, while increasing the extent of (possibly repeated) resection(s). Such a holistic vision of neural processing can enhance reliability of connectomal surgery in oncological neuroscience and may also be applied to restorative neurosurgery.
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Duffau, H. Brain connectomics applied to oncological neuroscience: from a traditional surgical strategy focusing on glioma topography to a meta-network approach. Acta Neurochir 163, 905–917 (2021). https://doi.org/10.1007/s00701-021-04752-z
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DOI: https://doi.org/10.1007/s00701-021-04752-z