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Epilepsia; 2017 Jul; Morgan et al.

Identifying a seizure propagation network in patients who have undergone surgery for unilateral temporal lobe epilepsy (TLE) may help determine which patients are most likely to remain seizure free over time, according to an analysis of patients who underwent magnetic resonance imaging (MRI) scans. Details of the investigation include the following:

  • MRI of 22 unilateral TLE patients found functional connectivity that encompassed the ipsilateral (to seizure focus) and contralateral hippocampus, thalamus, and insula. 35 healthy individuals were included in the study to act as controls.
  • Resting state functional and diffusion-weighted 3T magnetic resonance imaging was used in the study.
  • The investigators discovered a consistent connectivity pattern representing the network expected in patients who remained seizure free. This was found in 8 patients who did not have seizures one year after surgery.
  • Using this model, they were able to differentiate patients with unfavorable outcomes from those with long-term freedom from seizures.

This study provides evidence that network connectivity could be a clinical tool for epilepsy surgery outcome prediction.

 

Morgan VL, Englot DJ, Rogers BP, et al. Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy. Epilepsia. 2017;58(7):1251-1260.

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Epilepsia; 2017 Jul; Morgan et al.
Epilepsia; 2017 Jul; Morgan et al.

Identifying a seizure propagation network in patients who have undergone surgery for unilateral temporal lobe epilepsy (TLE) may help determine which patients are most likely to remain seizure free over time, according to an analysis of patients who underwent magnetic resonance imaging (MRI) scans. Details of the investigation include the following:

  • MRI of 22 unilateral TLE patients found functional connectivity that encompassed the ipsilateral (to seizure focus) and contralateral hippocampus, thalamus, and insula. 35 healthy individuals were included in the study to act as controls.
  • Resting state functional and diffusion-weighted 3T magnetic resonance imaging was used in the study.
  • The investigators discovered a consistent connectivity pattern representing the network expected in patients who remained seizure free. This was found in 8 patients who did not have seizures one year after surgery.
  • Using this model, they were able to differentiate patients with unfavorable outcomes from those with long-term freedom from seizures.

This study provides evidence that network connectivity could be a clinical tool for epilepsy surgery outcome prediction.

 

Morgan VL, Englot DJ, Rogers BP, et al. Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy. Epilepsia. 2017;58(7):1251-1260.

Identifying a seizure propagation network in patients who have undergone surgery for unilateral temporal lobe epilepsy (TLE) may help determine which patients are most likely to remain seizure free over time, according to an analysis of patients who underwent magnetic resonance imaging (MRI) scans. Details of the investigation include the following:

  • MRI of 22 unilateral TLE patients found functional connectivity that encompassed the ipsilateral (to seizure focus) and contralateral hippocampus, thalamus, and insula. 35 healthy individuals were included in the study to act as controls.
  • Resting state functional and diffusion-weighted 3T magnetic resonance imaging was used in the study.
  • The investigators discovered a consistent connectivity pattern representing the network expected in patients who remained seizure free. This was found in 8 patients who did not have seizures one year after surgery.
  • Using this model, they were able to differentiate patients with unfavorable outcomes from those with long-term freedom from seizures.

This study provides evidence that network connectivity could be a clinical tool for epilepsy surgery outcome prediction.

 

Morgan VL, Englot DJ, Rogers BP, et al. Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy. Epilepsia. 2017;58(7):1251-1260.

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