BOLD mapping of human epileptic spikes recorded during simultaneous intracranial EEG-fMRI: The impact of automated spike classification

被引:10
作者
Sharma, Niraj K. [1 ,2 ]
Pedreira, Carlos [3 ,4 ]
Chaudhary, Umair J. [1 ,2 ,5 ]
Centeno, Maria [1 ,2 ,6 ,7 ]
Carmichael, David W. [8 ,9 ]
Yadee, Tinonkorn [1 ,10 ]
Murta, Teresa [1 ,11 ]
Diehl, Beate [1 ,2 ,6 ]
Lemieux, Louis [1 ,2 ]
机构
[1] UCL Inst Neurol, Dept Clin & Expt Epilepsy, Queen Sq, London, England
[2] Epilepsy Soc, MRI Unit, Gerrards Cross, Bucks, England
[3] Univ Oxford, Dept Expt Psychol, Oxford, England
[4] Sensium Healthcare, Milton Pk, Abingdon, Oxon, England
[5] Univ Hosp Birmingham, Queen Elizabeth Hosp, NHS Fdn Trust, Neurol Dept, Birmingham, W Midlands, England
[6] UCLH NHS Fdn Trust, Natl Hosp Neurol & Neurosurg, Queen Sq, London, England
[7] Clin Univ Pamplona, Neurol Dept, Epilepsy Unit, Navarra, Spain
[8] UCL, Inst Child Hlth, Dev Imaging & Biophys, London, England
[9] Kings Coll London, St Thomas Hosp, Wellcome EPSRC Ctr Med Engn, London, England
[10] Prasat Neurol Inst, Bangkok, Thailand
[11] Natl Phys Lab, Teddington, Middx, England
基金
英国惠康基金; 英国医学研究理事会;
关键词
EEG-fMRI; IED; Intracranial EEG; Automated IED classification; BOLD response; FOCAL CORTICAL DYSPLASIA; INTERICTAL SPIKES; DISCHARGES; ELECTROENCEPHALOGRAPHY; NETWORKS; VALIDATION; SEIZURES; PROTOCOL;
D O I
10.1016/j.neuroimage.2018.09.065
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Objectives: Simultaneous intracranial EEG and functional MRI (icEEG-fMRI) can be used to map the haemodynamic (BOLD) changes associated with the generation of IEDs. Unlike scalp EEG-fMRI, in most patients who undergo icEEG-fMRI, IEDs recorded intracranially are numerous and show variability in terms of field amplitude and morphology. Therefore, visual marking can be highly subjective and time consuming. In this study, we applied an automated spike classification algorithm, Wave_clus (WC), to IEDs marked visually on icEEG data acquired during simultaneous fMRI acquisition. The motivation of this work is to determine whether using a potentially more consistent and unbiased automated approach can produce more biologically meaningful BOLD patterns compared to the BOLD patterns obtained based on the conventional, visual classification. Methods: We analysed simultaneous icEEG-fMRI data from eight patients with severe drug resistant epilepsy, and who subsequently underwent resective surgery that resulted in a good outcome: confirmed epileptogenic zone (EZ). For each patient two fMRI analyses were performed: one based on the conventional visual IED classification and the other based on the automated classification. We used the concordance of the IED-related BOLD maps with the confirmed EZ as an indication of their biological meaning, which we compared for the automated and visual classifications for all IED originating in the EZ. Results: Across the group, the visual and automated classifications resulted in 32 and 24 EZ IED classes respectively, for which 75% vs 83% of the corresponding BOLD maps were concordant. At the single-subject level, the BOLD maps for the automated approach had greater concordance in four patients, and less concordance in one patient, compared to those obtained using the conventional visual classification, and equal concordance for three remaining patients. These differences did not reach statistical significance. Conclusion: We found automated IED classification on icEEG data recorded during fMRI to be feasible and to result in IED-related BOLD maps that may contain similar or greater biological meaning compared to the conventional approach in the majority of the cases studied. We anticipate that this approach will help to gain significant new insights into the brain networks associated with IEDs and in relation to postsurgical outcome.
引用
收藏
页码:981 / 992
页数:12
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