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

Linda Douw, Marjolein de Groot, Edwin van Dellen, Jan J Heimans, Hanneke E Ronner, Cornelis J Stam, Jaap C Reijneveld, Linda Douw, Marjolein de Groot, Edwin van Dellen, Jan J Heimans, Hanneke E Ronner, Cornelis J Stam, Jaap C Reijneveld

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.

Conflict of interest statement

Competing Interests: L. Douw and E. van Dellen have projects sponsored by the Dutch Epilepsy Foundation, while M. de Groot is sponsored by UCB Pharma. None of these funders were involved in study design, acquisition and interpretation of data, or writing of this manuscript. Receiving these fundings does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials.

Figures

Figure 1. Flowchart of included patients.
Figure 1. Flowchart of included patients.
Figure 2. Mean SLs of epilepsy and…
Figure 2. Mean SLs of epilepsy and non-epilepsy patients in all seven frequency bands.
Note. ** significant difference between patients and controls, p<.001.>

Figure 3. ROC curve of IEDs and…

Figure 3. ROC curve of IEDs and theta band SL as predictors of diagnosis in…

Figure 3. ROC curve of IEDs and theta band SL as predictors of diagnosis in all patients (n = 114).

Figure 4. ROC curve of theta band…

Figure 4. ROC curve of theta band SL as predictor of diagnosis in epilepsy patients…

Figure 4. ROC curve of theta band SL as predictor of diagnosis in epilepsy patients without IEDs and their matched non-epilepsy patients (n = 74).
Figure 3. ROC curve of IEDs and…
Figure 3. ROC curve of IEDs and theta band SL as predictors of diagnosis in all patients (n = 114).
Figure 4. ROC curve of theta band…
Figure 4. 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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