Source localization of epileptic spikes using Multiple Sparse Priors.
Clin Neurophysiol
; 132(2): 586-597, 2021 02.
Article
em En
| MEDLINE
| ID: mdl-33477100
ABSTRACT
OBJECTIVE:
To evaluate epileptic source estimation using multiple sparse priors (MSP) inverse method and high-resolution, individual electrical head models.METHODS:
Accurate source localization is dependent on accurate electrical head models and appropriate inverse solvers. Using high-resolution, individual electrical head models in fifteen epilepsy patients, with surgical resection and clinical outcome as criteria for accuracy, performance of MSP method was compared against standardized low-resolution brain electromagnetic tomography (sLORETA) and coherent maximum entropy on the mean (cMEM) methods.RESULTS:
The MSP method performed similarly to the sLORETA method and slightly better than the cMEM method in terms of success rate. The MSP and cMEM methods were more focal than sLORETA with the advantage of not requiring an arbitrary selection of a hyperparameter or thresholding of reconstructed current density values to determine focus. MSP and cMEM methods were better than sLORETA in terms of spatial dispersion.CONCLUSIONS:
Results suggest that the three methods are complementary and could be used together. In practice, the MSP method will be easier to use and interpret compared to sLORETA, and slightly more accurate and faster than the cMEM method.SIGNIFICANCE:
Source localization of interictal spikes from dense-array electroencephalography data has been shown to be a reliable marker of epileptic foci and useful for pre-surgical planning. The advantages of MSP make it a useful complement to other inverse solvers in clinical practice.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Mapeamento Encefálico
/
Eletroencefalografia
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Epilepsia
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Modelagem Computacional Específica para o Paciente
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
Limite:
Adolescent
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Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Clin Neurophysiol
Assunto da revista:
NEUROLOGIA
/
PSICOFISIOLOGIA
Ano de publicação:
2021
Tipo de documento:
Article