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Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology

机译:EEG,MRI和神经心理学颞叶癫痫和轻度认知障碍的认知下降预测

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Cognitive decline is a severe concern of patients with mild cognitive impairment. Also, in patients with temporal lobe epilepsy, memory problems are a frequently encountered problem with potential progression. On the background of a unifying hypothesis for cognitive decline, we merged knowledge from dementia and epilepsy research in order to identify biomarkers with a high predictive value for cognitive decline across and beyond these groups that can be fed into intelligent systems. We prospectively assessed patients with temporal lobe epilepsy (N?=?9), mild cognitive impairment (N?=?19), and subjective cognitive complaints (N?=?4) and healthy controls (N?=?18). All had structural cerebral MRI, EEG at rest and during declarative verbal memory performance, and a neuropsychological assessment which was repeated after 18 months. Cognitive decline was defined as significant change on neuropsychological subscales. We extracted volumetric and shape features from MRI and brain network measures from EEG and fed these features alongside a baseline testing in neuropsychology into a machine learning framework with feature subset selection and 5-fold cross validation. Out of 50 patients, 27 had a decline over time in executive functions, 23 in visual-verbal memory, 23 in divided attention, and 7 patients had an increase in depression scores. The best sensitivity/specificity for decline was 72%/82% for executive functions based on a feature combination from MRI volumetry and EEG partial coherence during recall of memories; 95%/74% for visual-verbal memory by combination of MRI-wavelet features and neuropsychology; 84%/76% for divided attention by combination of MRI-wavelet features and neuropsychology; and 81%/90% for increase of depression by combination of EEG partial directed coherence factor at rest and neuropsychology. Combining information from EEG, MRI, and neuropsychology in order to predict neuropsychological changes in a heterogeneous population could create a more general model of cognitive performance decline.
机译:认知下降是对患者的严重认知障碍患者的严重关注。此外,在颞叶癫痫患者中,记忆问题是潜在的进展常见的问题。关于认知下降的统一假设的背景下,我们将知识与痴呆症和癫痫研究合并,以识别具有高预测价值的生物标志物,以便对这些群体的认知下降和超出可以进入智能系统的群体。我们前瞻性地评估了颞叶癫痫患者(n?= 9),轻度认知障碍(n?=?19),主观认知抱怨(n?=?4)和健康的对照(n?=?18)。所有人都有结构性脑MRI,EEG在休息和陈述性言语记忆性能期间,18个月后重复的神经心理学评估。认知下降被定义为神经心理分量的显着变化。我们从脑电图中提取了来自MEG的MRI和脑网络措施的体积和形状特征,并将这些功能与神经心理学中的基线测试一起进入机器学习框架,具有特征子集选择和5倍交叉验证。在50例患者中,27例在执行职能下降时间随着时间的推移,23例在视觉言语记忆中,分裂注意力23例,7例患者增加了抑郁症分数。基于MRI体积和eEG部分连贯期间回忆回忆中的最佳敏感性/下降的最佳敏感性/特异性为高管职能为72%/ 82%;通过MRI-小波特征和神经心理学的组合,可视化语头记忆95%/ 74%;通过MRI-小波特征和神经心理学的组合除以84%/ 76%;通过休息和神经心理学的eeg部分定向的连贯因子组合增加抑郁症的增加81%/ 90%。将来自脑电图,MRI和神经心理学的信息组合以预测异质人群的神经心理变化可以创造更普通的认知性能下降模型。

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