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UltraHigh Field MR Imaging in Epilepsy.超高场磁共振成像在癫痫中的应用。
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2
Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study.常见癫痫中基于网络的萎缩建模:一项全球范围的ENIGMA研究。
Sci Adv. 2020 Nov 18;6(47). doi: 10.1126/sciadv.abc6457. Print 2020 Nov.
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Unsupervised machine learning reveals lesional variability in focal cortical dysplasia at mesoscopic scale.无监督机器学习揭示了微观尺度下局灶性皮质发育不良的病变变异性。
Neuroimage Clin. 2020;28:102438. doi: 10.1016/j.nicl.2020.102438. Epub 2020 Sep 18.
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Value of 7T MRI and post-processing in patients with nonlesional 3T MRI undergoing epilepsy presurgical evaluation.3T MRI 无病变且行癫痫术前评估的患者中 7T MRI 及后处理的价值。
Epilepsia. 2020 Nov;61(11):2509-2520. doi: 10.1111/epi.16682. Epub 2020 Sep 19.
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Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy.癫痫中的大数据:临床和研究方面的考虑。国际抗癫痫联盟癫痫大数据工作组的报告。
Epilepsia. 2020 Sep;61(9):1869-1883. doi: 10.1111/epi.16633. Epub 2020 Aug 7.
6
The ENIGMA-Epilepsy working group: Mapping disease from large data sets.ENIGMA-癫痫工作组:从大型数据集中绘制疾病图谱。
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Functional connectome contractions in temporal lobe epilepsy: Microstructural underpinnings and predictors of surgical outcome.颞叶癫痫的功能连接收缩:手术结果的微观结构基础和预测因素。
Epilepsia. 2020 Jun;61(6):1221-1233. doi: 10.1111/epi.16540. Epub 2020 May 26.
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Clinical utility of structural connectomics in predicting memory in temporal lobe epilepsy.结构连接组学在预测颞叶癫痫患者记忆中的临床应用。
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Multidimensional associations between cognition and connectome organization in temporal lobe epilepsy.颞叶癫痫患者认知功能与连接组组织的多维关联。
Neuroimage. 2020 Jun;213:116706. doi: 10.1016/j.neuroimage.2020.116706. Epub 2020 Mar 6.
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Microstructural imaging in temporal lobe epilepsy: Diffusion imaging changes relate to reduced neurite density.颞叶癫痫的微观结构成像:弥散成像的变化与神经丝密度降低有关。
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癫痫神经影像学的新趋势

Emerging Trends in Neuroimaging of Epilepsy.

作者信息

Bernasconi Neda, Wang Irene

机构信息

Neuroimaging of Epilepsy Laboratory, 55981Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.

Epilepsy Center, Neurological Institute, 2569Cleveland Clinic, Cleveland, OH, USA.

出版信息

Epilepsy Curr. 2021 Mar;21(2):79-82. doi: 10.1177/1535759721991161. Epub 2021 Feb 9.

DOI:10.1177/1535759721991161
PMID:33557612
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8010873/
Abstract

Neuroimaging techniques, particularly magnetic resonance imaging, yield increasingly sophisticated markers of brain structure and function. Combined with ongoing developments in machine learning, these methods refine our abilities to detect subtle epileptogenic lesions and develop reliable prognostics.

摘要

神经成像技术,尤其是磁共振成像,产生了越来越复杂的脑结构和功能标记物。结合机器学习的不断发展,这些方法提高了我们检测细微致痫性病变和制定可靠预后指标的能力。