Huifang E Wang, Borana Dollomaja, Jan Paul TRIEBKORN, Gian Marco Duma, Adam WILLIAMSON, Julia Makhalova, Jean-didier LEMARERECHAL, Fabrice BARTOLOMEI, Viktor Jirsa
{"title":"用于刺激癫痫的虚拟大脑双胞胎","authors":"Huifang E Wang, Borana Dollomaja, Jan Paul TRIEBKORN, Gian Marco Duma, Adam WILLIAMSON, Julia Makhalova, Jean-didier LEMARERECHAL, Fabrice BARTOLOMEI, Viktor Jirsa","doi":"10.1101/2024.07.25.24310396","DOIUrl":null,"url":null,"abstract":"Estimating the epileptogenic zone network (EZN) is an important part of the diagnosis of drug-resistant focal epilepsy and plays a pivotal role in treatment and intervention. Virtual brain twins based on personalized whole brain modeling provides a formal method for personalized diagnosis by integrating patient-specific brain topography with structural connectivity from anatomical neuroimaging such as MRI and dynamic activity from functional recordings such as EEG and stereo-EEG (SEEG). Seizures demonstrate rich spatial and temporal features in functional recordings, which can be exploited to estimate the EZN. Stimulation-induced seizures can provide important and complementary information. In our modeling process, we consider invasive SEEG stimulation as the most practical current approach, and temporal interference (TI) stimulation as a potential future approach for non-invasive diagnosis and treatment. This paper offers a virtual brain twin framework for EZN diagnosis based on stimulation-induced seizures. This framework estimates the EZN and validated the results on synthetic data with ground-truth. It provides an important methodological and conceptual basis for a series of ongoing scientific studies and clinical usage, which are specified in this paper. This framework also provides the necessary step to go from invasive to non-invasive diagnosis and treatment of drug-resistant focal epilepsy.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Virtual brain twins for stimulation in epilepsy\",\"authors\":\"Huifang E Wang, Borana Dollomaja, Jan Paul TRIEBKORN, Gian Marco Duma, Adam WILLIAMSON, Julia Makhalova, Jean-didier LEMARERECHAL, Fabrice BARTOLOMEI, Viktor Jirsa\",\"doi\":\"10.1101/2024.07.25.24310396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Estimating the epileptogenic zone network (EZN) is an important part of the diagnosis of drug-resistant focal epilepsy and plays a pivotal role in treatment and intervention. Virtual brain twins based on personalized whole brain modeling provides a formal method for personalized diagnosis by integrating patient-specific brain topography with structural connectivity from anatomical neuroimaging such as MRI and dynamic activity from functional recordings such as EEG and stereo-EEG (SEEG). Seizures demonstrate rich spatial and temporal features in functional recordings, which can be exploited to estimate the EZN. Stimulation-induced seizures can provide important and complementary information. In our modeling process, we consider invasive SEEG stimulation as the most practical current approach, and temporal interference (TI) stimulation as a potential future approach for non-invasive diagnosis and treatment. This paper offers a virtual brain twin framework for EZN diagnosis based on stimulation-induced seizures. This framework estimates the EZN and validated the results on synthetic data with ground-truth. It provides an important methodological and conceptual basis for a series of ongoing scientific studies and clinical usage, which are specified in this paper. This framework also provides the necessary step to go from invasive to non-invasive diagnosis and treatment of drug-resistant focal epilepsy.\",\"PeriodicalId\":501367,\"journal\":{\"name\":\"medRxiv - Neurology\",\"volume\":\"17 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Neurology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.07.25.24310396\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.07.25.24310396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimating the epileptogenic zone network (EZN) is an important part of the diagnosis of drug-resistant focal epilepsy and plays a pivotal role in treatment and intervention. Virtual brain twins based on personalized whole brain modeling provides a formal method for personalized diagnosis by integrating patient-specific brain topography with structural connectivity from anatomical neuroimaging such as MRI and dynamic activity from functional recordings such as EEG and stereo-EEG (SEEG). Seizures demonstrate rich spatial and temporal features in functional recordings, which can be exploited to estimate the EZN. Stimulation-induced seizures can provide important and complementary information. In our modeling process, we consider invasive SEEG stimulation as the most practical current approach, and temporal interference (TI) stimulation as a potential future approach for non-invasive diagnosis and treatment. This paper offers a virtual brain twin framework for EZN diagnosis based on stimulation-induced seizures. This framework estimates the EZN and validated the results on synthetic data with ground-truth. It provides an important methodological and conceptual basis for a series of ongoing scientific studies and clinical usage, which are specified in this paper. This framework also provides the necessary step to go from invasive to non-invasive diagnosis and treatment of drug-resistant focal epilepsy.