Abstract
BackgroundAlzheimer’s disease (AD) is a major neurocognitive disorder identified by memory loss and a significant cognitive decline based on previous level of performance in one or more cognitive domains that interferes in the independence of everyday activities. The accuracy of imaging helps to identify the neuropathological features that differentiate AD from its common precursor, mild cognitive impairment (MCI). Identification of early signs will aid in risk stratification of disease and ensures proper management is instituted to reduce the morbidity and mortality associated with AD. Magnetic resonance imaging (MRI) using structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (1H-MRS) performed alone is inadequate. Thus, the combination of multiparametric MRI is proposed to increase the accuracy of diagnosing MCI and AD when compared to elderly healthy controls.MethodsThis protocol describes a non-interventional case control study. The AD and MCI patients and the healthy elderly controls will undergo multi-parametric MRI. The protocol consists of sMRI, fMRI, DTI, and single-voxel proton MRS sequences. An eco-planar imaging (EPI) will be used to perform resting-state fMRI sequence. The structural images will be analysed using Computational Anatomy Toolbox-12, functional images will be analysed using Statistical Parametric Mapping-12, DPABI (Data Processing & Analysis for Brain Imaging), and Conn software, while DTI and 1H-MRS will be analysed using the FSL (FMRIB’s Software Library) and Tarquin respectively. Correlation of the MRI results and the data acquired from the APOE genotyping, neuropsychological evaluations (i.e. Montreal Cognitive Assessment [MoCA], and Mini–Mental State Examination [MMSE] scores) will be performed. The imaging results will also be correlated with the sociodemographic factors. The diagnosis of AD and MCI will be standardized and based on the DSM-5 criteria and the neuropsychological scores.DiscussionThe combination of sMRI, fMRI, DTI, and MRS sequences can provide information on the anatomical and functional changes in the brain such as regional grey matter volume atrophy, impaired functional connectivity among brain regions, and decreased metabolite levels specifically at the posterior cingulate cortex/precuneus. The combination of multiparametric MRI sequences can be used to stratify the management of MCI and AD patients. Accurate imaging can decide on the frequency of follow-up at memory clinics and select classifiers for machine learning that may aid in the disease identification and prognostication. Reliable and consistent quantification, using standardised protocols, are crucial to establish an optimal diagnostic capability in the early detection of Alzheimer’s disease.
Highlights
Alzheimer’s disease (AD) and other dementias affects over 50 million people worldwide [1], about 30 million in Asia, and 123,000 people in Malaysia [2]
AD is a neurocognitive disorder identified by memory loss and a significant cognitive decline based on the previous level of performance in one or more cognitive domains that interfere in the independence of everyday activities
diffusion tensor imaging (DTI) parameters have been reported to provide a high cross-validated diagnostic accuracy of almost 80% for the clinical diagnosis of mild cognitive impairment (MCI) and the discrimination of Aβ positive MCI cases from Aβ negative controls [26]. 1H-MRS measures brain chemistry is sensitive to neuronal changes. 1H-MRS metabolites i.e., N-acetyl aspartate (NAA), myo-inositol, choline (Cho), creatine (Cr), NAA/Cr, NAA/ml, and mI/Cr ratios have been suggested as potential biomarkers of brain dysfunction in patients with AD [27,28,29]
Summary
Alzheimer’s disease (AD) and other dementias affects over 50 million people worldwide [1], about 30 million in Asia, and 123,000 people in Malaysia [2] The latter is projected to be 261,000 by 2030 and will continue to increase to 590,000 people in 2050 [3]. AD is a neurocognitive disorder identified by memory loss and a significant cognitive decline based on the previous level of performance in one or more cognitive domains that interfere in the independence of everyday activities. Alzheimer’s disease (AD) is a major neurocognitive disorder identified by memory loss and a significant cognitive decline based on previous level of performance in one or more cognitive domains that interferes in the independence of everyday activities. The combination of multiparametric MRI is proposed to increase the accuracy of diagnosing MCI and AD when compared to elderly healthy controls
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