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'Functional connectivity' is a sensitive predictor of epilepsy diagnosis after the first seizure.

Douw L, de Groot M, van Dellen E, Heimans JJ, Ronner HE, Stam CJ, Reijneveld JC - PLoS ONE (2010)

Bottom Line: The synchronization likelihood (SL) was used as an index of functional connectivity of the EEG, and average SL per patient was calculated in seven frequency bands.In total, 114 patients were selected.Our results indicate that epilepsy diagnosis could be improved by using functional connectivity.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands. l.douw@vumc.nl

ABSTRACT

Background: Although epilepsy affects almost 1% of the world population, diagnosis of this debilitating disease is still difficult. The EEG is an important tool for epilepsy diagnosis and classification, but the sensitivity of interictal epileptiform discharges (IEDs) on the first EEG is only 30-50%. Here we investigate whether using 'functional connectivity' can improve the diagnostic sensitivity of the first interictal EEG in the diagnosis of epilepsy.

Methodology/principal findings: Patients were selected from a database with 390 standard EEGs of patients after a first suspected seizure. Patients who were later diagnosed with epilepsy (i.e. > or = two seizures) were compared to matched non-epilepsy patients (with a minimum follow-up of one year). The synchronization likelihood (SL) was used as an index of functional connectivity of the EEG, and average SL per patient was calculated in seven frequency bands. In total, 114 patients were selected. Fifty-seven patients were diagnosed with epilepsy (20 had IEDs on their EEG) and 57 matched patients had other diagnoses. Epilepsy patients had significantly higher SL in the theta band than non-epilepsy patients. Furthermore, theta band SL proved to be a significant predictor of a diagnosis of epilepsy. When only those epilepsy patients without IEDs were considered (n = 74), theta band SL could predict diagnosis with specificity of 76% and sensitivity of 62%.

Conclusion/significance: Theta band functional connectivity may be a useful diagnostic tool in diagnosing epilepsy, especially in those patients who do not show IEDs on their first EEG. Our results indicate that epilepsy diagnosis could be improved by using functional connectivity.

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ROC curve of theta band SL as predictor of diagnosis in epilepsy patients without IEDs and their matched non-epilepsy patients (n = 74).
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pone-0010839-g004: ROC curve of theta band SL as predictor of diagnosis in epilepsy patients without IEDs and their matched non-epilepsy patients (n = 74).

Mentions: Predictive significance of connectivity would be even more interesting in those patients without IEDs, as no information from the EEG can be used in this population up till now. Therefore, we performed logistic regression analysis on epilepsy patients without IEDs on their EEGs and their matched non-epilepsy patients only (n = 74, see table 3 for patient characteristics). This model was significant (chi-square = 8.0, p = .005), as was theta band SL as a predictor (Exp(B) = 1.86, p = .015). Theta band SL accurately classified 69% of cases; specificity was 76%, while sensitivity was 62% (see figure 4 for ROC curve). When adding radiological abnormalities and medication use to the regression analysis, these two variables were again removed from the model, while theta band SL remained a significant predictor.


'Functional connectivity' is a sensitive predictor of epilepsy diagnosis after the first seizure.

Douw L, de Groot M, van Dellen E, Heimans JJ, Ronner HE, Stam CJ, Reijneveld JC - PLoS ONE (2010)

ROC curve of theta band SL as predictor of diagnosis in epilepsy patients without IEDs and their matched non-epilepsy patients (n = 74).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2877105&req=5

pone-0010839-g004: ROC curve of theta band SL as predictor of diagnosis in epilepsy patients without IEDs and their matched non-epilepsy patients (n = 74).
Mentions: Predictive significance of connectivity would be even more interesting in those patients without IEDs, as no information from the EEG can be used in this population up till now. Therefore, we performed logistic regression analysis on epilepsy patients without IEDs on their EEGs and their matched non-epilepsy patients only (n = 74, see table 3 for patient characteristics). This model was significant (chi-square = 8.0, p = .005), as was theta band SL as a predictor (Exp(B) = 1.86, p = .015). Theta band SL accurately classified 69% of cases; specificity was 76%, while sensitivity was 62% (see figure 4 for ROC curve). When adding radiological abnormalities and medication use to the regression analysis, these two variables were again removed from the model, while theta band SL remained a significant predictor.

Bottom Line: The synchronization likelihood (SL) was used as an index of functional connectivity of the EEG, and average SL per patient was calculated in seven frequency bands.In total, 114 patients were selected.Our results indicate that epilepsy diagnosis could be improved by using functional connectivity.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands. l.douw@vumc.nl

ABSTRACT

Background: Although epilepsy affects almost 1% of the world population, diagnosis of this debilitating disease is still difficult. The EEG is an important tool for epilepsy diagnosis and classification, but the sensitivity of interictal epileptiform discharges (IEDs) on the first EEG is only 30-50%. Here we investigate whether using 'functional connectivity' can improve the diagnostic sensitivity of the first interictal EEG in the diagnosis of epilepsy.

Methodology/principal findings: Patients were selected from a database with 390 standard EEGs of patients after a first suspected seizure. Patients who were later diagnosed with epilepsy (i.e. > or = two seizures) were compared to matched non-epilepsy patients (with a minimum follow-up of one year). The synchronization likelihood (SL) was used as an index of functional connectivity of the EEG, and average SL per patient was calculated in seven frequency bands. In total, 114 patients were selected. Fifty-seven patients were diagnosed with epilepsy (20 had IEDs on their EEG) and 57 matched patients had other diagnoses. Epilepsy patients had significantly higher SL in the theta band than non-epilepsy patients. Furthermore, theta band SL proved to be a significant predictor of a diagnosis of epilepsy. When only those epilepsy patients without IEDs were considered (n = 74), theta band SL could predict diagnosis with specificity of 76% and sensitivity of 62%.

Conclusion/significance: Theta band functional connectivity may be a useful diagnostic tool in diagnosing epilepsy, especially in those patients who do not show IEDs on their first EEG. Our results indicate that epilepsy diagnosis could be improved by using functional connectivity.

Show MeSH
Related in: MedlinePlus