Pacific Brain Health Center, Pacific Neuroscience Institute and Foundation, Santa Monica, CA, USA.
Providence Saint John's Health Center, Santa Monica, CA, USA.
J Alzheimers Dis. 2022;90(4):1761-1769. doi: 10.3233/JAD-220616.
Distinguishing between subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia in a scalable, accessible way is important to promote earlier detection and intervention.
We investigated diagnostic categorization using an FDA-cleared quantitative electroencephalographic/event-related potential (qEEG/ERP)-based cognitive testing system (eVox® by Evoke Neuroscience) combined with an automated volumetric magnetic resonance imaging (vMRI) tool (Neuroreader® by Brainreader).
Patients who self-presented with memory complaints were assigned to a diagnostic category by dementia specialists based on clinical history, neurologic exam, neuropsychological testing, and laboratory results. In addition, qEEG/ERP (n = 161) and quantitative vMRI (n = 111) data were obtained. A multinomial logistic regression model was used to determine significant predictors of cognitive diagnostic category (SCD, MCI, or dementia) using all available qEEG/ERP features and MRI volumes as the independent variables and controlling for demographic variables. Area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the diagnostic accuracy of the prediction models.
The qEEG/ERP measures of Reaction Time, Commission Errors, and P300b Amplitude were significant predictors (AUC = 0.79) of cognitive category. Diagnostic accuracy increased when volumetric MRI measures, specifically left temporal lobe volume, were added to the model (AUC = 0.87).
This study demonstrates the potential of a primarily physiological diagnostic model for differentiating SCD, MCI, and dementia using qEEG/ERP-based cognitive testing, especially when combined with volumetric brain MRI. The accessibility of qEEG/ERP and vMRI means that these tools can be used as adjuncts to clinical assessments to help increase the diagnostic certainty of SCD, MCI, and dementia.
以可扩展且易于使用的方式区分主观认知下降（SCD）、轻度认知障碍（MCI）和痴呆症对于促进早期发现和干预非常重要。
我们使用经 FDA 批准的定量脑电图/事件相关电位（qEEG/ERP）为基础的认知测试系统（Evoke Neuroscience 的 eVox®）结合自动容积磁共振成像（vMRI）工具（Brainreader 的 Neuroreader®）来研究诊断分类。
根据临床病史、神经系统检查、神经心理学测试和实验室结果，记忆主诉的患者由痴呆症专家分配到诊断类别。此外，还获得了 qEEG/ERP（n=161）和定量 vMRI（n=111）数据。使用多元逻辑回归模型，使用所有可用的 qEEG/ERP 特征和 MRI 体积作为自变量，并控制人口统计学变量，确定认知诊断类别（SCD、MCI 或痴呆症）的显著预测因子。接收者操作特征曲线下的面积（AUC）用于评估预测模型的诊断准确性。
反应时间、错误数和 P300b 波幅的 qEEG/ERP 测量值是认知类别的显著预测因子（AUC=0.79）。当将体积 MRI 测量值（特别是左侧颞叶体积）添加到模型中时，诊断准确性提高（AUC=0.87）。
这项研究表明，使用基于 qEEG/ERP 的认知测试区分 SCD、MCI 和痴呆症的主要生理诊断模型具有潜力，特别是与容积脑 MRI 结合使用时。qEEG/ERP 和 vMRI 的可及性意味着这些工具可作为临床评估的辅助手段，有助于提高 SCD、MCI 和痴呆症的诊断确定性。
