Abstract Objective Interictal epileptiform spikes (IESs) are widely used biomarkers of epileptogenic tissue in presurgical epilepsy evaluation. However, their reliability for seizure onset zone (SOZ) localization in high‐density intracranial electroencephalography (iEEG) remains inconsistent. It is underexplored whether this variability reflects methodological differences across detection algorithms or a limitation of IESs as a biomarker. This study evaluates whether IES detection alone provides sufficient spatial specificity for accurate SOZ localization in iEEG. Methods We systematically benchmarked eight established IES detection algorithms using iEEG recordings from 35 patients with drug‐resistant focal epilepsy. To provide a clinically meaningful reference, algorithm performance was evaluated against the clinically defined SOZ. To refine detection outputs and move beyond only IES detection, we applied masking strategies to isolate informative IES subsets based on rate, amplitude, frequency, and co‐occurrence with high‐frequency oscillations (HFOs). Conceptually, masking acts as a spatial refinement strategy that progressively restricts diffuse IES activity to more focal, pathologically relevant event populations. Results Despite substantial variability in detection characteristics, SOZ localization performance (ratio of events originating from SOZ divided by total number of events) converged within a narrow range (.23–.51), suggesting that IESs exhibit an intrinsic ceiling in SOZ localization performance when used alone. Amplitude‐based masking yielded modest improvements, whereas frequency‐based masking reduced performance. In contrast, IES‐HFO co‐occurrence markedly improved localization, particularly when combined with rate‐based masking, achieving a median SOZ localization ratio of .89, exceeding IESs (.37) and HFOs (.63) evaluated independently. Significance These findings demonstrate that IES‐based SOZ localization may require moving beyond detection‐only approaches. The integration of informed, biomarker‐driven masking strategies provides a more robust framework for identifying the activity most relevant to the epileptogenic network and paves the way for future incorporation into the clinical decision‐making pipeline.
The Case of a 28‐Year‐Old Woman With Medically Refractory Focal Epilepsy
ABSTRACT We present the case of a 28‐year‐old right‐handed woman with medically refractory focal epilepsy. Her seizure semiology and electroencephalography (EEG) indicated a seizure onset zone in the right central‐parietal area. However, both MRI and PET scans were unremarkable, showing no focal lesions or areas of altered metabolism. Intracranial monitoring, with extensive evaluation of both hemispheres, confirmed the seizure onset zone in the right central‐parietal region. This area not only served as the site of seizure onset but also encompassed the primary sensory cortex.
Pseudo-HFOs Elimination in iEEG Recordings Using a Robust Residual-Based Dictionary Learning Framework
Summary Objective A prospective multicenter phase III trial was undertaken to evaluate the performance and tolerability in the epilepsy monitoring unit ( EMU ) of an investigational wearable surface electromyographic ( sEMG ) monitoring system for the detection of generalized tonic–clonic seizures ( GTCSs ). Methods One hundred ninety‐nine patients with a history of GTCSs who were admitted to the EMU in 11 level IV epilepsy centers for clinically indicated video‐electroencephalographic monitoring also received sEMG monitoring with a wearable device that was worn on the arm over the biceps muscle. All recorded sEMG data were processed at a central site using a previously developed detection algorithm. Detected GTCSs were compared to events verified by a majority of three expert reviewers. Results For all subjects, the detection algorithm detected 35 of 46 (76%, 95% confidence interval [CI] = 0.61–0.87) of the GTCSs, with a positive predictive value ( PPV ) of 0.03 and a mean false alarm rate ( FAR ) of 2.52 per 24 h. For data recorded while the device was placed over the midline of the biceps muscle, the system detected 29 of 29 GTCSs (100%, 95% CI = 0.88–1.00), with a detection delay averaging 7.70 s, a PPV of 6.2%, and a mean FAR of 1.44 per 24 h. Mild to moderate adverse events were reported in 28% (55 of 199) of subjects and led to study withdrawal in 9% (17 of 199). These adverse events consisted mostly of skin irritation caused by the electrode patch that resolved without treatment. No serious adverse events were reported. Significance Detection of GTCSs using an sEMG monitoring device on the biceps is feasible. Proper positioning of this device is important for accuracy, and for some patients, minimizing the number of false positives may be challenging.