Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Höller, Yvonne, Butz, Kevin H. G., Thomschewski, Aljoscha C., Schmid, Elisabeth V., Hofer, Christoph D., Uhl, Andreas, Bathke, Arne C., Staffen, Wolfgang, Nardone, Raffaele, Schwimmbeck, Fabian, Leitinger, Markus, Kuchukhidze, Giorgi, Derner, Marlene, Fell, Jürgen, Trinka, Eugen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256687/
https://www.ncbi.nlm.nih.gov/pubmed/32549888
http://dx.doi.org/10.1155/2020/8915961
_version_ 1783539966175870976
author Höller, Yvonne
Butz, Kevin H. G.
Thomschewski, Aljoscha C.
Schmid, Elisabeth V.
Hofer, Christoph D.
Uhl, Andreas
Bathke, Arne C.
Staffen, Wolfgang
Nardone, Raffaele
Schwimmbeck, Fabian
Leitinger, Markus
Kuchukhidze, Giorgi
Derner, Marlene
Fell, Jürgen
Trinka, Eugen
author_facet Höller, Yvonne
Butz, Kevin H. G.
Thomschewski, Aljoscha C.
Schmid, Elisabeth V.
Hofer, Christoph D.
Uhl, Andreas
Bathke, Arne C.
Staffen, Wolfgang
Nardone, Raffaele
Schwimmbeck, Fabian
Leitinger, Markus
Kuchukhidze, Giorgi
Derner, Marlene
Fell, Jürgen
Trinka, Eugen
author_sort Höller, Yvonne
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7256687
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-72566872020-06-16 Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology Höller, Yvonne Butz, Kevin H. G. Thomschewski, Aljoscha C. Schmid, Elisabeth V. Hofer, Christoph D. Uhl, Andreas Bathke, Arne C. Staffen, Wolfgang Nardone, Raffaele Schwimmbeck, Fabian Leitinger, Markus Kuchukhidze, Giorgi Derner, Marlene Fell, Jürgen Trinka, Eugen Comput Intell Neurosci Research Article 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. Hindawi 2020-05-20 /pmc/articles/PMC7256687/ /pubmed/32549888 http://dx.doi.org/10.1155/2020/8915961 Text en Copyright © 2020 Yvonne Höller et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Höller, Yvonne
Butz, Kevin H. G.
Thomschewski, Aljoscha C.
Schmid, Elisabeth V.
Hofer, Christoph D.
Uhl, Andreas
Bathke, Arne C.
Staffen, Wolfgang
Nardone, Raffaele
Schwimmbeck, Fabian
Leitinger, Markus
Kuchukhidze, Giorgi
Derner, Marlene
Fell, Jürgen
Trinka, Eugen
Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology
title Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology
title_full Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology
title_fullStr Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology
title_full_unstemmed Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology
title_short Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology
title_sort prediction of cognitive decline in temporal lobe epilepsy and mild cognitive impairment by eeg, mri, and neuropsychology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256687/
https://www.ncbi.nlm.nih.gov/pubmed/32549888
http://dx.doi.org/10.1155/2020/8915961
work_keys_str_mv AT holleryvonne predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT butzkevinhg predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT thomschewskialjoschac predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT schmidelisabethv predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT hoferchristophd predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT uhlandreas predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT bathkearnec predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT staffenwolfgang predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT nardoneraffaele predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT schwimmbeckfabian predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT leitingermarkus predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT kuchukhidzegiorgi predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT dernermarlene predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT felljurgen predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology
AT trinkaeugen predictionofcognitivedeclineintemporallobeepilepsyandmildcognitiveimpairmentbyeegmriandneuropsychology