Differentiation of Subjective Cognitive Decline, Mild Cognitive Impairment, and Dementia Using qEEG/ERP-Based Cognitive Testing and Volumetric MRI in an Outpatient Specialty Memory Clinic
| Autor: | Aarthi S. Ganapathi, Ryan M. Glatt, Tess H. Bookheimer, Emily S. Popa, Morgan L. Ingemanson, Casey J. Richards, John F. Hodes, Kyron P. Pierce, Colby B. Slyapich, Fatima Iqbal, Jenna Mattinson, Melanie G. Lampa, Jaya M. Gill, Ynez M. Tongson, Claudia L. Wong, Mihae Kim, Verna R. Porter, Santosh Kesari, Somayeh Meysami, Karen J. Miller, Jennifer E. Bramen, David A. Merrill, Prabha Siddarth |
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| Rok vydání: | 2022 |
| Předmět: |
Aging
Clinical Sciences Neuropsychological Tests Neurodegenerative Alzheimer's Disease mild cognitive impairment Clinical Research Behavioral and Social Science Acquired Cognitive Impairment Humans Cognitive Dysfunction Evoked Potentials Neurology & Neurosurgery General Neuroscience Neurosciences Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) General Medicine Magnetic Resonance Imaging Brain Disorders Psychiatry and Mental health Clinical Psychology Mental Health Neurological Biomedical Imaging Dementia Cognitive Sciences Geriatrics and Gerontology electroencephalography |
| Zdroj: | Journal of Alzheimer's disease : JAD, vol 90, iss 4 |
| Popis: | Background: 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. Objective: 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). Methods: 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. Results: 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). Conclusion: 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. |
| Databáze: | OpenAIRE |
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