RESUMO
Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but up to 50% of patients continue to have seizures one year after the resection. In order to aid presurgical planning and predict postsurgical outcome on a patient-by-patient basis, we developed a framework of individualized computational models that combines epidemic spreading with patient-specific connectivity and epileptogeneity maps: the Epidemic Spreading Seizure and Epilepsy Surgery framework (ESSES). ESSES parameters were fitted in a retrospective study (N = 15) to reproduce invasive electroencephalography (iEEG)-recorded seizures. ESSES reproduced the iEEG-recorded seizures, and significantly better so for patients with good (seizure-free, SF) than bad (nonseizure-free, NSF) outcome. We illustrate here the clinical applicability of ESSES with a pseudo-prospective study (N = 34) with a blind setting (to the resection strategy and surgical outcome) that emulated presurgical conditions. By setting the model parameters in the retrospective study, ESSES could be applied also to patients without iEEG data. ESSES could predict the chances of good outcome after any resection by finding patient-specific model-based optimal resection strategies, which we found to be smaller for SF than NSF patients, suggesting an intrinsic difference in the network organization or presurgical evaluation results of NSF patients. The actual surgical plan overlapped more with the model-based optimal resection, and had a larger effect in decreasing modeled seizure propagation, for SF patients than for NSF patients. Overall, ESSES could correctly predict 75% of NSF and 80.8% of SF cases pseudo-prospectively. Our results show that individualised computational models may inform surgical planning by suggesting alternative resections and providing information on the likelihood of a good outcome after a proposed resection. This is the first time that such a model is validated with a fully independent cohort and without the need for iEEG recordings.
Individualized computational models of epilepsy surgery capture some of the key aspects of seizure propagation and the resective surgery. It is to be established whether this information can be integrated during the presurgical evaluation of the patient to improve surgical planning and the chances of a good surgical outcome. Here we address this question with a pseudo-prospective study that applies a computational framework of seizure propagation and epilepsy surgerythe ESSES frameworkin a pseudo-prospective study mimicking the presurgical conditions. We found that within this pseudo-prospective setting, ESSES could correctly predict 75% of NSF and 80.8% of SF cases. This finding suggests the potential of individualised computational models to inform surgical planning by suggesting alternative resections and providing information on the likelihood of a good outcome after a proposed resection.
RESUMO
OBJECTIVES: To investigate whether rhythmic/periodic EEG patterns (RPP) appearing after propofol discontinuation are more likely to be related to the elimination phase of propofol, or are an expression of severe brain damage. METHODS: In a retrospective cohort of comatose postanoxic patients, EEG was assessed one hour before (baseline) and on hour after discontinuation of propofol. Presence and duration of RPP were related to (changes in) EEG background pattern and duration of sedation. RESULTS: In eleven (of 36 eligible) patients RPP appeared after propofol discontinuation and disappeared in seven of these patients within one hour. A continuous background pattern at baseline and shorter duration of propofol infusion seemed associated with (earlier) spontaneous disappearance of RPP. In ten patients with RPP at baseline, the EEG did not change, and in one patient it changed into burst-suppression. CONCLUSION: Our findings suggest that RPP after propofol discontinuation could be propofol-related. DISCUSSION: RPP might be related to propofol discontinuation rather than an expression of severe brain damage, especially in case of, and congruent with, a continuous pattern at the time of propofol discontinuation. This opens a new insight in this phenomenon and its transient nature. In clinical practice, we suggest to consider the timing of propofol discontinuation when assessing the EEG signal in postanoxic patients.