Brain Surgery Scars Distort EEG Readings, Complicating Patient Diagnosis
A new study reveals that brain tumors and surgical bone flaps significantly distort electrical brain signals measured by EEG—a test relied on by hospitals and clinics worldwide. The findings could force healthcare providers to recalibrate how they interpret EEG data for millions of post-surgical and cancer patients, potentially affecting diagnostic accuracy and treatment decisions.
Originaltitel: The Impact of Brain Tumors and Craniotomy Lesions on Scalp EEG
Electroencephalography (EEG) is widely used in both research and clinical settings, yet its accuracy can be significantly impacted by subject-specific anatomical anomalies such as brain lesions and skull defects. This study investigates the effects of glioma-related brain lesions and craniotomy-induced bone discontinuities on scalp-recorded EEG signals. To do this, single- and multi-source simulations were created using individualized forward models with and without these structural anomalies. We assessed changes in signal amplitude and topography, and identified the most affected electrodes. Furthermore, real EEG recordings were also analyzed longitudinally to evaluate how these anomalies influence the topography and source localization of early auditory evoked responses (P1 and N1 ERP components). Both single- and multi-source simulations showed that the distortions in the EEG signals depend on the location of the neural source in relation to the location of the lesion. Electrode-level analyses showed that these distortions were most pronounced at the electrodes near the bone flap, and thus near the lesions. Real ERP data supported these findings: a subject with a lesion near the auditory cortex showed notable topographic deviations longitudinally for the P1 and N1 ERP components, while a subject with a frontal lesion showed minimal changes in the scalp EEG. These results highlight the need to include detailed brain and skull anatomy in EEG models, especially in studies that track longitudinal changes in clinical populations.