Pomiar niessymetryczności napadów międzynapadowych w EEG czaszki do ustalenia strony pochodzenia napadów w epilepsji skroniowej
Quantifying Interictal Spike Asymmetry on Scalp EEG to Lateralize the Seizure-Onset Zone in Temporal Lobe Epilepsy
W skrócie
Badacze opracowali sztuczną inteligencję do analizy zapisu EEG, która automatycznie liczy anomalie elektryczne w mózgu i sprawdza, czy występują częściej po jednej stronie czaszki. Ta metoda może dokładnie wskazać, z której strony mózgu pochodzą napady u pacjentów z epilepsją skroniową i pomóc lekarzom w zaplanowaniu operacji. Wykazano, że kiedy wynik analizy zgadza się z innymi badaniami diagnostycznymi, pacjenci po operacji mają lepsze szanse na pozbycie się napadów.
Oryginalny abstract (angielski)
BACKGROUND AND OBJECTIVES: Accurate lateralization of the seizure focus in temporal lobe epilepsy (TLE) is critical for surgical planning. Our current approach of capturing multiple seizures often misses bilateral disease because of seizure-onset variability. Interictal spike rate asymmetry is a promising marker of TLE laterality. However, visual analysis has low interrater reliability and cannot estimate long-term spike rates. This study evaluated whether asymmetry of automatically detected interictal spikes on scalp EEG can lateralize the clinician-annotated seizure focus in TLE. METHODS: We performed a retrospective cohort study of patients with drug-resistant TLE who underwent scalp EEG recording at the Hospital of the University of Pennsylvania. Spike rates were quantified using a validated deep learning model, with a novel leave-one-hemisphere-out approach developed to lateralize the side of the spikes. We developed a logistic regression model to predict the clinician-determined laterality. Model performance was assessed using the area under the ROC curve (AUC), accuracy, and area under the precision-recall curve (AUPRC). RESULTS: Of 365 included patients (205 women [56.2%]; median age 38, range 18-86 years), the training cohort comprised 261 patients and the independent, time-shifted validation cohort comprised 104. In the test cohort, classification of left TLE vs right/bilateral achieved an AUC of 0.78 (95% CI 0.69-0.87), an accuracy of 70%, and an AUPRC of 0.80 (95% CI 0.69-0.91), and classification of right TLE vs left/bilateral achieved an AUC of 0.80 (95% CI 0.70-0.88), an accuracy of 75%, and an AUPRC of 0.71 (95% CI 0.56-0.85). Model-surgery concordance was positively associated with favorable surgical outcomes. Engel I outcomes were associated with higher concordance probabilities (median difference = 0.20; 95% CI -0.02 to 0.39; = 0.35; = 0.037), and no significant association was observed for ILAE 1-2 (median difference = 0.20; 95% CI -0.06 to 0.38; = 0.29; = 0.084). DISCUSSION: Interictal spike asymmetry on scalp EEG shows promise as a noninvasive lateralizing marker in TLE. Applying this model could confirm TLE laterality when it agrees with other noninvasive data or identify patients with a high likelihood of bilateral TLE, potentially avoiding un-necessary invasive studies and reducing the number of seizures needed for evaluation.