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Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: Research protocol of a case-control study design

BACKGROUND: 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 accuracy of imaging helps to i...

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Autores principales: Piersson, Albert Dayor, Ibrahim, Buhari, Suppiah, Subapriya, Mohamad, Mazlyfarina, Hassan, Hasyma Abu, Omar, Nur Farhayu, Ibrahim, Mohd Izuan, Yusoff, Ahmad Nazlim, Ibrahim, Normala, Saripan, M. Iqbal, Razali, Rizah Mazzuin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454976/
https://www.ncbi.nlm.nih.gov/pubmed/34547018
http://dx.doi.org/10.1371/journal.pone.0252883
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author Piersson, Albert Dayor
Ibrahim, Buhari
Suppiah, Subapriya
Mohamad, Mazlyfarina
Hassan, Hasyma Abu
Omar, Nur Farhayu
Ibrahim, Mohd Izuan
Yusoff, Ahmad Nazlim
Ibrahim, Normala
Saripan, M. Iqbal
Razali, Rizah Mazzuin
author_facet Piersson, Albert Dayor
Ibrahim, Buhari
Suppiah, Subapriya
Mohamad, Mazlyfarina
Hassan, Hasyma Abu
Omar, Nur Farhayu
Ibrahim, Mohd Izuan
Yusoff, Ahmad Nazlim
Ibrahim, Normala
Saripan, M. Iqbal
Razali, Rizah Mazzuin
author_sort Piersson, Albert Dayor
collection PubMed
description BACKGROUND: 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 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 ((1)H-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. METHODS: This 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 (1)H-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. DISCUSSION: The 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.
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spelling pubmed-84549762021-09-22 Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: Research protocol of a case-control study design Piersson, Albert Dayor Ibrahim, Buhari Suppiah, Subapriya Mohamad, Mazlyfarina Hassan, Hasyma Abu Omar, Nur Farhayu Ibrahim, Mohd Izuan Yusoff, Ahmad Nazlim Ibrahim, Normala Saripan, M. Iqbal Razali, Rizah Mazzuin PLoS One Registered Report Protocol BACKGROUND: 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 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 ((1)H-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. METHODS: This 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 (1)H-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. DISCUSSION: The 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. Public Library of Science 2021-09-21 /pmc/articles/PMC8454976/ /pubmed/34547018 http://dx.doi.org/10.1371/journal.pone.0252883 Text en © 2021 Piersson et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Registered Report Protocol
Piersson, Albert Dayor
Ibrahim, Buhari
Suppiah, Subapriya
Mohamad, Mazlyfarina
Hassan, Hasyma Abu
Omar, Nur Farhayu
Ibrahim, Mohd Izuan
Yusoff, Ahmad Nazlim
Ibrahim, Normala
Saripan, M. Iqbal
Razali, Rizah Mazzuin
Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: Research protocol of a case-control study design
title Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: Research protocol of a case-control study design
title_full Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: Research protocol of a case-control study design
title_fullStr Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: Research protocol of a case-control study design
title_full_unstemmed Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: Research protocol of a case-control study design
title_short Multiparametric MRI for the improved diagnostic accuracy of Alzheimer’s disease and mild cognitive impairment: Research protocol of a case-control study design
title_sort multiparametric mri for the improved diagnostic accuracy of alzheimer’s disease and mild cognitive impairment: research protocol of a case-control study design
topic Registered Report Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454976/
https://www.ncbi.nlm.nih.gov/pubmed/34547018
http://dx.doi.org/10.1371/journal.pone.0252883
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