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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Cerebral Hemodynamics in Mild Cognitive Impairment: A Systematic Review
Lucy Beishon1, Victoria J Haunton1,2, Ronney B Panerai1,2
1Department of Cardiovascular Sciences, University of Leicester, Leicester, UK.
Background:
The incidence of dementia is projected to rise over the coming decades, but with no sensitive diagnostic tests available. Vascular pathology precedes the deposition of amyloid and is an attractive early target.
Objective:
The aim of this review was to investigate the use of cerebral hemodynamics and oxygenation as a novel biomarker for mild cognitive impairment (MCI), focusing on transcranial Doppler ultrasonography (TCD) and near-infrared spectroscopy (NIRS).
Methods:
2,698 articles were identified from Medline, Embase, PsychINFO, and Web of Science databases. 306 articles were screened and quality assessed independently by two reviewers; 26 met the inclusion criteria. Meta-analyses were performed for each marker with two or more studies and limited heterogeneity.
Results:
Eleven studies were TCD, 8 NIRS, 5 magnetic resonance imaging, and 2 positron/single photon emission tomography. Meta-analyses showed reduced tissue oxygenation index, cerebral blood flow and velocity, with higher pulsatility index, phase and cerebrovascular resistance in MCI compared to controls. The majority of studies found reduced CO2 reactivity in MCI, with mixed findings in neuroactivation studies.
Conclusion:
Despite small sample sizes and heterogeneity, meta-analyses demonstrate clear abnormalities in cerebral hemodynamic and oxygenation parameters, even at an early stage of cognitive decline. Further work is required to investigate the use of cerebral hemodynamic and oxygenation parameters as a sensitive biomarker for dementia.
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