| MAREČEK, Radek, Pavel ŘÍHA, Michaela BARTOŇOVÁ, Martin KOJAN, Martin LAMOŠ, Martin GAJDOŠ, Lubomír VOJTÍŠEK, Michal MIKL, Marek BARTOŇ, Irena DOLEŽALOVÁ, Martin PAIL, Ondřej STRÝČEK, Marta PAŽOURKOVÁ, Milan BRÁZDIL a Ivan REKTOR. Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging. Human Brain mapping. Hoboken: WILEY-BLACKWELL, 2021, roč. 42, č. 9, s. 2921-2930. ISSN 1065-9471. Dostupné z: https://dx.doi.org/10.1002/hbm.25413. |
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@article{1781359,
author = {Mareček, Radek and Říha, Pavel and Bartoňová, Michaela and Kojan, Martin and Lamoš, Martin and Gajdoš, Martin and Vojtíšek, Lubomír and Mikl, Michal and Bartoň, Marek and Doležalová, Irena and Pail, Martin and Strýček, Ondřej and Pažourková, Marta and Brázdil, Milan and Rektor, Ivan},
article_location = {Hoboken},
article_number = {9},
doi = {http://dx.doi.org/10.1002/hbm.25413},
keywords = {data fusion; neuroimaging; nonlesional epilepsy; seizure onset zone},
language = {eng},
issn = {1065-9471},
journal = {Human Brain mapping},
title = {Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging},
url = {https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hbm.25413},
volume = {42},
year = {2021}
}
TY - JOUR
ID - 1781359
AU - Mareček, Radek - Říha, Pavel - Bartoňová, Michaela - Kojan, Martin - Lamoš, Martin - Gajdoš, Martin - Vojtíšek, Lubomír - Mikl, Michal - Bartoň, Marek - Doležalová, Irena - Pail, Martin - Strýček, Ondřej - Pažourková, Marta - Brázdil, Milan - Rektor, Ivan
PY - 2021
TI - Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging
JF - Human Brain mapping
VL - 42
IS - 9
SP - 2921-2930
EP - 2921-2930
PB - WILEY-BLACKWELL
SN - 10659471
KW - data fusion
KW - neuroimaging
KW - nonlesional epilepsy
KW - seizure onset zone
UR - https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hbm.25413
N2 - Many methods applied to data acquired by various imaging modalities have been evaluated for their benefit in localizing lesions in magnetic resonance (MR) negative epilepsy patients. No approach has proven to be a stand-alone method with sufficiently high sensitivity and specificity. The presented study addresses the potential benefit of the automated fusion of results of individual methods in presurgical evaluation. We collected electrophysiological, MR, and nuclear imaging data from 137 patients with pharmacoresistant MR-negative/inconclusive focal epilepsy. A subgroup of 32 patients underwent surgical treatment with known postsurgical outcomes and histopathology. We employed a Gaussian mixture model to reveal several classes of gray matter tissue. Classes specific to epileptogenic tissue were identified and validated using the surgery subgroup divided into two disjoint sets. We evaluated the classification accuracy of the proposed method at a voxel-wise level and assessed the effect of individual methods. The training of the classifier resulted in six classes of gray matter tissue. We found a subset of two classes specific to tissue located in resected areas. The average classification accuracy (i.e., the probability of correct classification) was significantly higher than the level of chance in the training group (0.73) and even better in the validation surgery subgroup (0.82). Nuclear imaging, diffusion-weighted imaging, and source localization of interictal epileptic discharges were the strongest methods for classification accuracy. We showed that the automatic fusion of results can identify brain areas that show epileptogenic gray matter tissue features. The method might enhance the presurgical evaluations of MR-negative epilepsy patients.
ER -
MAREČEK, Radek, Pavel ŘÍHA, Michaela BARTOŇOVÁ, Martin KOJAN, Martin LAMOŠ, Martin GAJDOŠ, Lubomír VOJTÍŠEK, Michal MIKL, Marek BARTOŇ, Irena DOLEŽALOVÁ, Martin PAIL, Ondřej STRÝČEK, Marta PAŽOURKOVÁ, Milan BRÁZDIL a Ivan REKTOR. Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging. \textit{Human Brain mapping}. Hoboken: WILEY-BLACKWELL, 2021, roč.~42, č.~9, s.~2921-2930. ISSN~1065-9471. Dostupné z: https://dx.doi.org/10.1002/hbm.25413.
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