Model based prediction of post epilepsy surgery
In about 30% of epileptic patients, epilepsy is not controlled by medication. For some of these patients surgery is an option. However, the surgery requires accurate determination of the seizure onset zone. So the prediction of reliable epileptic brain area is of crucial importance. Here...
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| 格式: | Theses and Dissertations |
| 語言: | English |
| 出版: |
2014
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| 主題: | |
| 在線閱讀: | http://hdl.handle.net/10356/55322 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | In about 30% of epileptic patients, epilepsy is not controlled by medication. For some
of these patients surgery is an option. However, the surgery requires accurate
determination of the seizure onset zone. So the prediction of reliable epileptic brain
area is of crucial importance.
Here, a dynamic model is developed to predict the seizure onset zone and outcome of
surgery in patients. The model uses the inter-ictal ECoG data as a connectivity to
predict the seizure onset zone in the brain.
The examination of betweenness centrality of the node gives the strong correlation
with the seizure onset zone. Betweenness centralization of the network depends on the
seizure onset zone, if seizure onset is removed the betweenness centralization of the
network decreases. Increase in betweenness centralization of the network is also
associated with the seizure onset zone.
It is shown that the probability of seizure occurrence is less with decrease in
betweenness centralization ofthe network. Hence, the model can be used to predict
the seizure onset zone and outcome of surgery. |
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