INTRODUCTION AND RATIONALE Aggressive brain tumors like glioma have the ability to infiltrate the surrounding healthy brain tissue, disrupting normal neuronal activities and leading to impaired motor and cognitive functions, as well as causing epilepsy. This malignant brain tumor is considered one of the most challenging cancers to treat, with a median survival of 12 to 15 months. Recent findings on direct neuron-tumor interactions indicate that abnormal brain activity in the regions surrounding brain tumors may contribute to develop epilepsy and accelerating tumor growth. Tumors tend to 'fuel' themselves with neurotransmitters released during its 'daily' neuronal firing. Hyperactive neurons in the peritumoral cortex can form excitatory electrochemical synapses with surrounding tumor cells, creating direct communication pathways within the peritumoral microenvironment, which aids in the progression and proliferation of tumor cells via direct and paracrine signalling pathways. However, the specific features of this abnormal brain activity in the peritumoral cortex have not been fully clarified and information on the pathological changes of neuronal activity in glioma patients is largely lacking. To advance more effective treatment strategies, it is crucial to better understand the complex interactions between the tumor and the brain. This is especially important for the group of patients of which many perceive diminished quality of life because of epilepsy, cognitive functioning and language problems after tumor surgery. Furthermore, a thorough understanding is lacking of what tumor resection does to the original hyperactive peritumoral cortex and if resecting this is beneficial for improving postoperative outcome both for epilepsy as well as regarding survival. Therefore, identifying the hyperactive peritumoral cortex and directly addressing its impacts on the brain function and long-term surgical outcome could be a promising novel therapeutic strategy for treating glioma patients. STUDY AIM The measurement focuses on capturing neuronal activity at single-neuron resolution in the peritumoral cortex of glioma patients using cortical depth electrodes. It is well-established that gliomas can remodel the surrounding brain tissue, leading to abnormal neuronal hyperactivity, which contributes to tumor progression and epilepsy. However, the specific neuronal patterns and underlying mechanisms of these changes are not yet fully understood. This study will aim to collect detailed single-neuron recordings in this context, enabling us to map the precise neurophysiological disruptions caused by gliomas. On the long term, this research could lay the groundwork in identifying novel therapeutic approaches by providing critical in-sights into how gliomas alter brain function.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DEVICE_FEASIBILITY
Masking
NONE
Enrollment
10
Neuropixel recordings captures neuronal activity at the single-neuron level across the layers of the cortex.
Number of Successful Neuropixels Probe Recordings During Glioma Surgeries
Description: The primary outcome measure is the number of successful Neuropixels depth electrode recordings achieved during glioma surgeries. Success is defined as: Sterility: No postoperative infections, assessed by clinical follow-up and microbiological testing. Signal Quality: Signal-to-noise ratio (SNR) above 30 dB, as measured during and after surgery through electrophysiological software. Device Integrity: No fractures or damage to the Neuropixels probe, verified by post-procedure inspection. Training Efficiency: Setup time and error reduction during the recording process, recorded across surgeries to assess team proficiency.
Time frame: From the beginning to end of tumor surgery
Prognostic Biomarker Identification (Unit: Number of Isolated Single Neurons with Tumor-Modulated Activity):
The secondary outcome will focus on identifying prognostic biomarkers through intra-operative recordings using Neuropixels. This includes measuring the number of single neurons isolated with distinct spiking or waveform characteristics that correlate with tumor pathology. The outcome will be quantified as the number of neurons showing unique tumor-related activity patterns (e.g., altered firing rates, waveform morphology) across patients undergoing surgery.
Time frame: From the beginning to end of surgery
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