Glioblastoma multiforme (GBM) is a devastating brain cancer with an extremely low probability of patient survival. In the clinic, the priority is to surgically remove as much tumor as possible while preserving critical functions, such as language production and movement. An implantable electrode grid called an electrocorticogram (ECoG) is placed on the brain surface to record electrical signatures which allow neurosurgeons to identify and avoid critical brain areas during surgery. However, existing ECoG grids are made of materials that are rigid and cannot conform to the 3D architecture of the brain. This leads to frequent repositioning of the grid, limited recording quality, and compression...

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Glioblastoma multiforme (GBM) is a devastating brain cancer with an extremely low probability of patient survival. In the clinic, the priority is to surgically remove as much tumor as possible while preserving critical functions, such as language production and movement. An implantable electrode grid called an electrocorticogram (ECoG) is placed on the brain surface to record electrical signatures which allow neurosurgeons to identify and avoid critical brain areas during surgery. However, existing ECoG grids are made of materials that are rigid and cannot conform to the 3D architecture of the brain. This leads to frequent repositioning of the grid, limited recording quality, and compression of the brain. This proposal focuses on building ECoG grids out of hydrogels, which are materials that can match all the brain's mechanical properties. By placing this ultrasoft, highly conformable grid onto and into the brain, neurosurgeons can create functional maps with higher signal-to-noise ratios while avoiding damaging the tissue. The proposal first describes methods to create a materials toolbox to replace all existing ECoG components with ultrasoft hydrogel alternatives. Further, a multifunctional ECoG which utilizes hydrogel compatibility for drug delivery is discussed and will be validated in brain slices and a rabbit GBM model. In addition to the viscoelastic ECoG, the proposal also describes using hydrogels to pattern neural networks in vitro and creating physiologically-mimicked networks of patient-derived neurons and tumors. The cells are grown above a dense electrode array which will illuminate tumor invasion mechanisms. Additionally, this platform will be used for personalized medicine to rapidly screen drugs and identify the best patient-specific treatment combination. The proposal covers methods to understand GBM progression and innervation, while introducing technologies that more comprehensively map the brain for improved removal of GBM tissue.

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