ReviewActa epileptologica2026
The use of quantitative electroencephalography in evaluating epilepsy treatment.
Review in Acta epileptologica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
Funding
Abstract
Because quantitative electroencephalography (QEEG) presents objective, data-driven measurements of brain activity with better performance than conventional EEG, it has become more popular for evaluating therapeutic response in epilepsy. Data from over 160 English-language papers on the use of QEEG in the evaluation of epilepsy treatment that were published up to March 2026 were assessed in this review. This review includes anti-seizure medications (ASMs), long-term EEG monitoring, neuromodulation methods such as vagus nerve stimulation (VNS), epilepsy surgery and epileptogenic zone identification, and new models using AI. Instead of providing a methodical or completely reproducible synthesis, this review concentrates on critically evaluating methodological trends, translational significance, and current limitations in various applications. The significant differences in patients' demographics, EEG acquisition methods, analytical approaches, and clinical goals caused difficulties in a thorough systematic review or meta-analysis. However, a qualitative review of the literature showed recurrent QEEG patterns associated with treatment response, areas of conflicting evidence, and the translational readiness of different metrics. Studies frequently find correlations between changes in spectral power, functional connectivity (FC), and epileptiform activity indices (EAI) and clinical outcomes. However, the reproducibility and robustness of these correlations greatly vary depending on treatment modality and methodological environment. Hence, the potential of QEEG in directing customized treatments is limited by the lack of standardized procedures, normative databases, and prospective validation. All things considered, it appears most promise for long-term therapy tracking and, in certain situations, for enhancing conventional clinical evaluation. This review emphasizes the necessity of thorough studies that prioritize practical application, clinical interpretability, and repeatability. Additionally, it highlights the current limitations and therapeutic potential of QEEG-based treatment evaluation.
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