Utility of quantitative EEG in early Lewy body disease

Massa, Federico; Meli, Riccardo; Grazzini, Matteo; Famà, Francesco; Carli, Fabrizio De; Filippi, Laura; Arnaldi, Dario; Pardini, Matteo; Morbelli, Silvia; Nobili, Flavio

doi:10.1016/j.parkreldis.2020.05.007

Cited by 30 publications

(26 citation statements)

References 30 publications

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“…Quantitative EEG findings of MCI-LB have been reported to be similar to those reported in DLB vs. AD, where MCI-LB have lower dominant frequency compared to MCI-AD [65][66][67]. This also translates into higher pre-alpha power and lower alpha and beta power and a higher theta/alpha ratio [65][66][67].…”

Section: Prodromal Dlb and Progression To Dementiasupporting

confidence: 61%

“…AD, where MCI-LB have lower dominant frequency compared to MCI-AD [ 65 , 66 , 67 ]. This also translates into higher pre-alpha power and lower alpha and beta power and a higher theta/alpha ratio [ 65 , 66 , 67 ]. Schumacher 2020b reported that spectral power analyses had sensitivities of 23–51%, specificity of 81–97% and area under receiver operating characteristics curve (AUROC) of 0.54–0.71 in diagnosing MCI-LB ( Table 4 ) [ 67 ].…”

Section: Resultsmentioning

confidence: 99%

“…Several studies explored whether EEG features can predict progression to dementia in patients with MCI. One study reported a reduction in mean frequency and alpha/theta ratio in MCI who progressed to DLB (MCI-LB) compared to those who progressed to AD(MCI-AD) [65]. Another study used CSA to predict progression in patients with MCI to DLB, AD or no progression at 3 years with an overall accuracy of 76%.…”

Section: Prodromal Dlb and Progression To Dementiamentioning

confidence: 99%

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The Role of EEG in the Diagnosis, Prognosis and Clinical Correlations of Dementia with Lewy Bodies—A Systematic Review

et al. 2020

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Despite improvements in diagnostic criteria for dementia with Lewy bodies (DLB), the ability to discriminate DLB from Alzheimer’s disease (AD) and other dementias remains suboptimal. Electroencephalography (EEG) is currently a supportive biomarker in the diagnosis of DLB. We performed a systematic review to better clarify the diagnostic and prognostic role of EEG in DLB and define the clinical correlates of various EEG features described in DLB. MEDLINE, EMBASE, and PsycINFO were searched using search strategies for relevant articles up to 6 August 2020. We included 43 studies comparing EEG in DLB with other diagnoses, 42 of them included a comparison of DLB with AD, 10 studies compared DLB with Parkinson’s disease dementia, and 6 studies compared DLB with other dementias. The studies were visual EEG assessment (6), quantitative EEG (35) and event-related potential studies (2). The most consistent observation was the slowing of the dominant EEG rhythm (<8 Hz) assessed visually or through quantitative EEG, which was observed in ~90% of patients with DLB and only ~10% of patients with AD. Other findings based on qualitative rating, spectral power analyses, connectivity, microstate and machine learning algorithms were largely heterogenous due to differences in study design, EEG acquisition, preprocessing and analysis. EEG protocols should be standardized to allow replication and validation of promising EEG features as potential biomarkers in DLB.

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Section: Prodromal Dlb and Progression To Dementiasupporting

confidence: 61%

Section: Resultsmentioning

confidence: 99%

Section: Prodromal Dlb and Progression To Dementiamentioning

confidence: 99%

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The Role of EEG in the Diagnosis, Prognosis and Clinical Correlations of Dementia with Lewy Bodies—A Systematic Review

et al. 2020

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“…There is emerging evidence supporting the role of quantitative electroencephalography (EEG) as a diag nostic marker for DLB, with slower wave activity and variation in dominant frequency in patients with this disorder 11,12 . Similar changes, such as quantitative EEG background slowingdown and spectral power analy sis performed with machine learning techniques, are associated with cognitive impairment in Lewy body disease 165,166 and preliminary studies have suggested EEG as a predictive biomarker of cognitive decline in PD 167 . In a subsequent study, an increased risk of dementia in patients with PD with low background rhythm frequency and increased theta median power was found 168 .…”

Section: Biomarkers Of Cognitive Declinementioning

confidence: 90%

Parkinson disease-associated cognitive impairment

Aarsland

Batzu

Halliday

et al. 2021

Nat Rev Dis Primers

597

417

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Parkinson disease (PD) is the second most common neurodegenerative disorder, affecting >1% of the population ≥65 years of age and with a prevalence set to double by 2030. In addition to the defining motor symptoms of PD, multiple non-motor symptoms occur; among them, cognitive impairment is common and can potentially occur at any disease stage. Cognitive decline is usually slow and insidious, but rapid in some cases. Recently, the focus has been on the early cognitive changes, where executive and visuospatial impairments are typical and can be accompanied by memory impairment, increasing the risk for early progression to dementia. Other risk factors for early progression to dementia include visual hallucinations, older age and biomarker changes such as cortical atrophy, as well as Alzheimer-type changes on functional imaging and in cerebrospinal fluid, and slowing and frequency variation on EEG. However, the mechanisms underlying cognitive decline in PD remain largely unclear. Cortical involvement of Lewy body and Alzheimer-type pathologies are key features, but multiple mechanisms are likely involved. Cholinesterase inhibition is the only high-level evidence-based treatment available, but other pharmacological and non-pharmacological strategies are being tested. Challenges include the identification of disease-modifying therapies as well as finding biomarkers to better predict cognitive decline and identify patients at high risk for early and rapid cognitive impairment.

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“…It can be inferred that patients with white matter demyelinating have insignificant changes in dominant frequency distribution and delta wave power, a decrease in α wave power and a / θ value, and an increase in θ wave and δ + θ / α + β value. Therefore, the power of α wave, the value of α / θ , the value of θ wave, and δ + θ / α + β were QEEG indicators with auxiliary diagnostic value [ 13 ]. The scores of the SPMSQ scale showed that the difference in learning, language, and execution of the two groups was not obvious ( P > 0.05).…”

Section: Discussionmentioning

confidence: 99%

Value of Magnetic Resonance Diffusion Tensor Imaging Combined with Quantitative Electroencephalogram in Diagnosis of Neurocognitive Impairment in Patients with White Matter Demyelination

Li¹,

Li²,

Ma³

et al. 2021

Contrast Media & Molecular Imaging

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This paper aimed to explore the clinical value of combined adoption of magnetic resonance diffusion tensor imaging (DTI) and quantitative electroencephalogram (QEEG) in assessing microstructure changes and mild neurocognitive dysfunction in patients with white matter demyelination. 128 cases of white matter demyelination admitted to the hospital from October 2018 to October 2019 were rolled into the research group, and 100 healthy patients physically examined during the same period were rolled into the control (ctrl) group. QEEG and magnetic resonance DTI examinations were performed for all patients. The wave power of δ, θ, α, and β and the ratio of α/θ and (δ + θ)/(α + β) were recorded. The FA values of white matter fibers in different brain areas were measured, and the Montreal Cognitive Assessment (MoCA) and Addenbrooke Cognitive Evaluation rating (ACE-R) were adopted to assess the neurocognitive function of patients. It was found that the dominant frequency of each brain area in the research group was 8-9 Hz slow α wave. In contrast with the ctrl, the α wave and α/θ values in the research group were lower, while θ wave and δ + θ/α + β values were higher ( P < 0.05 ); the scores of ACE-R and MoCA were lower ( P < 0.01 ); the fractional anisotropy (FA) values of the right frontal lobe white matter (0.335 ± 0.068), the left temporal lobe white matter (0.391 ± 0.032), and the corpus callosum knee white matter (0.658 ± 0.053) were lower ( P < 0.05 ). The FA values of these three areas were positively correlated with attention and calculation, memory, and memory of MoCA scale, respectively ( P < 0.05 ). The FA value of the right frontal white matter was positively correlated with the attention and calculation score of the ACE-R scale ( P < 0.05 ). In conclusion, magnetic resonance DTI combined with QEEG could reflect the microstructural changes of white matter, which may be associated with mild neurocognitive impairment. The primary objective of the study was to explore the clinical value of combined adoption of magnetic resonance DTI and QEEG in assessing microstructure changes and mild neurocognitive dysfunction in patients with white matter demyelination, expected to provide a theoretical basis for the treatment of white matter demyelination.

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Utility of quantitative EEG in early Lewy body disease

Cited by 30 publications

References 30 publications

The Role of EEG in the Diagnosis, Prognosis and Clinical Correlations of Dementia with Lewy Bodies—A Systematic Review

The Role of EEG in the Diagnosis, Prognosis and Clinical Correlations of Dementia with Lewy Bodies—A Systematic Review

Parkinson disease-associated cognitive impairment

Value of Magnetic Resonance Diffusion Tensor Imaging Combined with Quantitative Electroencephalogram in Diagnosis of Neurocognitive Impairment in Patients with White Matter Demyelination

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