| Epilepsy is a frequent neurological disease,of which prevalence is approximately 0.7%in the general population.Most patients with epilepsy respond well to pharmacological therapy,but about 30%of them are drug-resistant.It is thought that surgical resection of epileptogenic zone?EZ?is a more effective treatment for these patients.However,successful surgery relies heavily on the ability of localizing the EZ.Clinicians must determine the smallest resection region to both include the whole EZ and reduce the possible side effects.Before surgery,non-invasive methods such as scalp video-electroencephalogram?VEEG?,neuropsychological tests,brain magnetic resonance imaging?MRI?and electrophysiological semiology analysis are used.If the above methods cannot determine the location of EZ,invasive evaluation should be performed,including subdural EEG and stereotactic EEG?SEEG?.At present,the primary analysis method of intracranialEEG?iEEG?isvisualinspection.Experienced electroencephalographers need to look for signatures on individual channels?e.g.,rapid discharges with or without prior low-frequency high-amplitude rhythmic spikes?that might be characteristic of the seizure onset zone.With the large numbers of implanted electrodes?often more than 100 contacts?,this can be time-consuming and increase the cost and risk of infection.Moreover,the activity on individual channels is affected by functional networks that involve other channels in the surrounding regions,which is not always easily identified by visual inspection.Therefore,precise EZ localization remains a challenging problem.In recent years,with the development of neuroscience,the brain is increasingly seen as a complex network of dynamical systems.Researchers begin to analyze brain activity and network through the application of network analysis and quantified studies.In epilepsy,it has been considered that EZ is not just an isolated brain structure,but a functional network made by multiple spatially distinct brain regions based on anatomical connectivity.The brain connectivity may experience alterations both during seizures and interictal periods.Although functional properties are expressed locally,they are the result of the action of the entire network as an integrated system.Although traditional scalp VEEG and subdural EEG could limited EZ into a small cortex regions,the brain network evolution in deep structures and extensive regions could hard to be analyzed.This might lead to poor surgical outcomes,especially in patients with normal MRI.Therefore,SEEG was applied in presurgical evaluation more frequently.In this study,we quantified and analyzed the SEEG signals in interictal and ictal period by examining the eigenvector centrality?EVC?and epileptogenicity index?EI?as the characteristics of brain network,in order to observe the dynamic changes of network and features of EZ in different patients.Meanwhile,we reported the experience of our group in using SEEG in presurgical evaluation and its effectiveness in normal MRI cases,in order to provide guidelines in future evaluation and improve surgical outcomes.Part oneAnalysis of brain state evolution during seizures based onSEEG in drug-resistant focal epilepsy patientsObjective:To observe the dynamic changes of interictal and ictal brain network,by examining the changes of EVC before,during and after seizures as characteristics of network in SEEG recordings analysis and clustering the brain network into a series of brain states in 9 drug-resistant epilepsy patients with different surgical outcomes and EZ localization.Methods:Nine patients with drug-resistant epilepsy undergoing SEEG in presurgical evaluation and surgical resection were selected between May 2013and June 2014.All patients had a comprehensive evaluation including detailed history and neurologic examination,neuropsychological testing,3T brain MRI,scalp VEEG,and SEEG.After surgery,all patients have been followed up for at least 1.5 year and Engle classification was used in outcome evaluation.The first method of analysis of SEEG signals was visual inspection.The seizure onset was indicated by a variety of stereotypical electrographic features,such as rapid discharges.The recording from 60 seconds before seizure to 60 seconds after seizure in each patients was converted to EDF format for network analyzing.For each patient,each contact of electrode was considered as a node in brain network,we constructed a series of consecutive brain connectivity matrix by computing the coherence of each pair of nodes in beta frequency band as the edge.In each matrix,EVC of each node was calculated as the characteristic of matrix to cluster the different matrix over time into a set of brain states by using K-means clustering.Then we could observe the evolution of brain states in each seizure in every patient and analyze the features of brain network in different seizure type.Meanwhile,we also described the connectivity of each pair of nodes in brain network in each states.According to clinical outcomes,the patients were divided into two groups.Engle I was considered as well-controlled?SF group?,that is to say the resected areas contained the EZ in these patients.Other patients who still had seizures were in n SF group,which the resected regions determined presurgery were considered to be smaller than or outside of the EZ.We analyzed the evolution of functional connectivity in the resected regions by observing the evolution of rank vectors in these regions to find the characteristics of epileptogenic network during seizures.Results:1.For all the patients,there was only a small set of brain states?4.58±1.50?in interictal periods,while in ictal periods,the number of states was larger?8.37±1.46,P<0.05?.In SF group and nSF group respectively,the number of states in ictal periods was also larger than interictal periods?8.60±1.71 vs.4.50±1.27 in SF group,8.11±3.44 vs.4.67±2.48 in nSF group,P<0.05?.2.For all the patients,the transition of brain states in interictal periods was irregular and the intrastate distances between these states were smaller than the distances in ictal periods.Moreover,we also found the evolution of states during seizures were in more regular patterns in SF group,which was not found in nSF group.3.For patients in SF group,we found the evolution of states during seizures were similar in the same patient,especial in the seizure onset.4.For patients in SF group,we found the rank vector of nodes in resected regions dropped at the onset of seizure,which meant in the first 1 or2 states at seizure onset,brain connectivity became less connected than interictal period.And then,the connectivity enhanced with different level in different patients.For the patients in nSF group,we did not found this kind of characteristics.Part twoA quantified study of epileptogenicity in different brainstructures in drug-resistant patients with temporal lobe epilepsy based on SEEGObjective:To quantified the epileptogenicity of mesial temporal lobe structures,lateral neocortical regions,and extratemporal peri-sylvian structures in patients with drug-resistent temporal lobe epilepsy?TLE?by examining EI in these region,in order to classify the different brain networks involved in seizures in TLE and compare the etiology and outcomes in different network subtypes.Methods:Thirteen patients with drug-resistant TLE undergoing SEEG in presurgical evaluation and surgical resection were selected between 2013 and2015.All patients had a comprehensive evaluation including detailed history and neurologic examination,neuropsychological testing,3T brain MRI,scalp VEEG,and SEEG.After surgery,all patients have been followed up for at least 1.5 year and Engle classification was used in outcome evaluation.Engle I was considered as well-controlled?SF group?,while other patients who still had seizures were in nSF group.The position of SEEG electrodes include mesial temporal regions?including amygdala,entorhinal cortex,internal part of the temporal pole,the anterior part of the hippocampus,the posterior part of the hippocampus?,lateral temporal regions?including external part of the temporal pole,anterior part of the middle temporal gyrus,posterior part of the middle temporal gyrus superior temporal gyrus?,and extratemporal perisylvian regions?including the orbitofrontal cortex,the frontal operculum,the insular cortex?.The first method of analysis of SEEG signals was visual inspection.The seizure onset was indicated by a variety of stereotypical electrographic features,such as rapid discharges.The recording from 60 seconds before seizure to 60 seconds after seizure in each patients was converted to EDF format for quantified study.For each channel,the EI value was computed by detecting two important features of SEEG signals at seizure onset period:the signal energy ratio?ER?between high?theta and beta?and low?delta and theta?frequency bands of the EEG from the signal spectral density and the change-points in the ER quantity.The EI in each channel is normalized with respect to the highest value across channels ranging from 0 to 1.If there is no involvement of the brain region,then EI=0.Whereas if the brain region generates a rapid discharge and if the delay with respect to seizure onset is minimal,the EI=1.The EI between 0 and1 means secondary involvement of the considered brain region.A cutoff of EI?0.3 was used to define regions with high epileptogenicity in temporal epilepsy.According to the region where the maximum EI was,the TLE was divided into subtypes.And then,the etiology,clinical manifestation,epilepsy duration and surgical outcomes were compared in different subtypes.Results:1.According to the location of maximal EI regions,13 patients were divided into 3 subtypes,mesial temporal group?M?,lateral temporal group?L?and extratemporal perisylvian group?temporal plus,TPS?.In M group,EI value in mesial temporal structures was 0.54±0.34,while 0.19±0.26 in lateral temporal structures and 0.10±0.13 in extratemporal structures.There was significant difference in these regions?P<0.001?.In L group,the EI in lateral,mesial and extratemporal structures was 0.60±0.40,0.13±0.08 and 0.21±0.21,also with significant difference?P=0.004?.However,in TPS group,the EI in extratemporal,mesial and lateral structures was 0.63±0.35,0.42±0.23 and0.50±0.30,without significant difference?P=0.255?.2.For all the 13 patients,the median number of epileptogenic structures was 5.The duration of epilepsy was positively correlated with NEI>0.3?rs=0.811,P=0.001?.3.For the etiology in different substypes,we found that M group was predominantly associated with hippocampal sclerosis?HS?,whereas L group and TPS group were frequently associated with normal MRI or lesions other than HS.In addition,compared with those with lesions,patients with normal MRI tended to have a greater number of EI>0.3 structures?6.6 vs 4,P<0.05?.4.In M group,6/7 patients had auras such as fear,deja vu and epigastric sensation,whereas patients in other groups often had auras hard to description.In addition,the loss of consciousness and versive in M group was later than others and secondary generalized tonic-clonic seizures?sGTCs?were less?2/7vs.2/3 vs.2/3?.5.For the patients with different outcomes,the maximum EI values in mesial structures were not significantly different between SF group and nSF group?0.75±0.38 vs 0.71±0.37,P=0.40?,which were also not different in lateral structures?0.50±0.46 vs 0.80±0.26,P=0.48?.In contrast,maximum EI values in extratemporal structures were found to be significantly lower in the SF group than the nSF group?0.22±0.30 vs 0.76±0.28,P=0.02?.In addition,compared in nSF group,patients in SF group had a smaller number of EI>0.3structures?4.22 vs 6.75,P<0.05?.Part three SEEG in presurgical assessment of MRI-negative epilepsyObjective:To analyze the experience of our group in using SEEG in presurgical evaluation in patients with drug-resistent focal epilepsy and to discuss its clinical effectiveness in MRI negative cases,in order to provide guidelines in future evaluation and improve surgical outcomes.Methods:All the 27 patients with drug-resistant focal epilepsy undergoing SEEG in presurgical evaluation were selected between 2011 and2015,and were divided into 2 groups,MRI negative group and MRI lesion group.All patients had a comprehensive evaluation including detailed history and neurologic examination,neuropsychological testing,3T brain MRI,scalp VEEG,and SEEG.MRI protocol consisted of:2mm axial T1-weight,T2-weight,and fluid-attenuated inversion recovery?FLAIR?images;coronal T2-weighted and FLAIR images from AC to PC plane;without interval.MRI examinations were performed on Siemens Trio 3.0 MR scan system.The inclusion criteria of MRI negative group was?patients without any structural lesion in MRI,?the brain lesion in MRI was not related with epilepsy.Other patients were in MRI lesion group.The implanted strategies of SEEG were depended on the hypothesis of EZ location and its transmission based on non-invasive data.The method of analysis of SEEG signals was visual inspection.The seizure onset was indicated by a variety of stereotypical electrographic features,such as rapid discharges with or without prior low-frequency high-amplitude rhythmic spikes.The surgical decision was made based on the whole epileptogenic network but not only seizure onset zone.After surgery,all patients have been followed up for at least 1.5 year and Engle classification was used in outcome evaluation.Results:1.For all the patients,only 2 did not have successful localization of EZ using SEEG.They were all in the MRI negative group,but there was no significant difference between these two groups.2.The type of the EZ varied between cases.In MRI negative group,expect 2 patients without clearly EZ location,3/10 patients showed limited brain structures,2/10 patients showed more than one independent EZ,and other 5/10 patients showed several structures with closely functional connectivity.While in MRI lesion group,8/15 patients showed limited brain structures,4/15 patients showed more than one independent EZ,and other3/10 patients showed several structures with connectivity.3.In MRI negative group,expect 2 patients without clearly EZ location,all of other 10 patients accepted surgical resection.While in MRI lesion group,13/15 patients accepted surgery.The SEEG was therefore crucial in making a surgical treatment decision in the majority of cases in both groups?83%vs.87%?,with no significant difference?P>0.55?.4.The outcomes had been assessed using the Engle classification.At the point of 1.5-year follow-up,5/10 patients showed Engle I and 9/10 showed significant improvement in MRI-negative group,while 8/13 and 11/13 in MRI lesion group respectively.There was no significant difference between these two groups.5.Eight out of 10 patients accepted surgery in MRI negative group were proved to have evidence of gliosis or neuronal degeneration,while 5 of them were diagnosed as focal cortical dysplasia?FCD?.Conclusions:1.There was some characteristics in the brain network evolution during interictal and ictal periods.The evolution could be described as transition in a set of brain states.The interictal states were less than ictal states and the intrastate distances between interictal states were smaller than the distances in ictal.The transition of states during seizures were in more regular patterns than interictal periods and these patterns were similar in the same patient.2.The EI is a measure aimed at quantifying the epileptogenicity of brain structures recorded with SEEG.It reflects the two important features of SEEG signals during the seizure onset period:the redistribution of signal energy and the delay of appearance of this redistribution in a given structure with respect to the first structure.According to the location of maximal EI regions,TLE could be divided into 3 subtypes,mesial temporal group,lateral temporal group and extratemporal perisylvian group.The epileptogenic structures in the first two groups were only a few,and limited in mesial or lateral temporal.But the epileptogenicity of structures in different regions were found no significant difference in TPS group.Whatever the subtype is,the epileptogenic zone manifests a network organization but not an isolated structures.The duration of TLE was positively correlated with the range of EZ,and the surgical outcomes of TLE were related with the range of EZ and the EI values in extratemporal structures.3.Combined with thorough non-invasive assessment,SEEG can be equally effective in MRI-negative and lesional MRI cases.There was no significant difference between two groups in the effectiveness of EZ location,the rate of surgical resection and clinical outcomes.In addition,postoperative histopathology had verified there may be some histological changes even in patients with negative MRI. |
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