Systematic Review of Advanced Algorithms for Brain Mapping in Stereotactic Neurosurgery: Integration of fMRI and EEG Data
Loading...
Date
Publisher
MDPI
Abstract
Background: Advances in stereotactic neurosurgery rely on precise brain mapping, which
allows the identification of functional regions for safer and more effective surgical interventions.
The aim of this systematic review was to assess the effectiveness, challenges, and
clinical applicability of algorithms used for multimodal data integration. Methodology:
Databases were searched for studies published in the last 13 years. Studies that integrate
fMRI and EEG data for brain mapping, quantitatively assess the performance of algorithms,
and have potential applications in stereotactic neurosurgery were included. Heterogeneity
among studies was assessed using the I2 statistic, and the results were analyzed by thematic
synthesis and meta-analysis. Results: The average accuracy of the algorithms was 90.2%
(±5.0%). Key challenges include computational requirements, susceptibility to artifacts,
and limited clinical applicability. Heterogeneity analysis showed significant methodological
variability (I2 = 71.90%), with greater heterogeneity among highly relevant algorithms
(I2 = 79.64%). Conclusions: Advanced algorithms offer significant potential to improve
precision, safety, and applicability in stereotactic neurosurgery. Key recommendations
include standardization of protocols, expansion of clinical validation, and optimization of
algorithms for real-time application.
Metadata
License
Except where otherwise noted, this item's license is described as Attribution 4.0 International