Journal of neuroscience methods · 2026
Toward intraoperative glioma localization: Exploring the relationship between tumor invasion depth and electrocorticography signals.
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Zhao Wenyu, Chang Tao, Wu Yihan, Cai Tianming, Liao Jiawei, Quan Yuxin, Li Yu, Liu Yanhui, Mao Qing, Jiang Ning, Yang Yuan, He Jiayuan
Аннотация
BACKGROUND: Glioma is a common primary malignant tumor; accurate intraoperative localization, especially of invasion depth, is critical for resection and postoperative treatment. Preoperative MRI and neuronavigation is reliable mainly before craniotomy, but brain shift begins to compromise image-to-patient registration as soon as the skull and dura are opened, before cortical resection even starts, and static MRI alone lacks functional information. Since glioma infiltration affects neural electrical activity, this study explored ECoG-based measurement of invasion depth.
NEW METHOD: ECoG electrodes were categorized into three types (Glioma Invading Subcortex [GIS], Glioma Invading Cortex [GIC], Normal-appearing cortex within patients with glioma [NC]) by underlying tumor invasion. Spectral power features across frequency bands were extracted, and linear/nonlinear methods evaluated their correlation with invasion depth.
RESULTS: GIS and GIC had significantly lower spectral power than NC. GIC showed a strong negative correlation between invasion depth and spectral power, strongest in the beta band (r = -0.642). Linear and nonlinear models had similar fitting errors, with the linear model more stable across patients.
COMPARISON WITH EXISTING METHODS: Unlike preoperative MRI (constrained by brain shift and inadequate functional data), this method uses real-time ECoG signals for dynamic intraoperative measurement with functional insights.
CONCLUSIONS: This study suggests that tumor infiltration is associated with suppression of cortical electrical activity and provides preliminary evidence of a relationship between ECoG signals and glioma invasion depth. These findings indicate a potential exploratory framework for assessing tumor infiltration intraoperatively, which may complement preoperative imaging; however, further validation in larger cohorts is required before clinical application can be established.
NEW METHOD: ECoG electrodes were categorized into three types (Glioma Invading Subcortex [GIS], Glioma Invading Cortex [GIC], Normal-appearing cortex within patients with glioma [NC]) by underlying tumor invasion. Spectral power features across frequency bands were extracted, and linear/nonlinear methods evaluated their correlation with invasion depth.
RESULTS: GIS and GIC had significantly lower spectral power than NC. GIC showed a strong negative correlation between invasion depth and spectral power, strongest in the beta band (r = -0.642). Linear and nonlinear models had similar fitting errors, with the linear model more stable across patients.
COMPARISON WITH EXISTING METHODS: Unlike preoperative MRI (constrained by brain shift and inadequate functional data), this method uses real-time ECoG signals for dynamic intraoperative measurement with functional insights.
CONCLUSIONS: This study suggests that tumor infiltration is associated with suppression of cortical electrical activity and provides preliminary evidence of a relationship between ECoG signals and glioma invasion depth. These findings indicate a potential exploratory framework for assessing tumor infiltration intraoperatively, which may complement preoperative imaging; however, further validation in larger cohorts is required before clinical application can be established.