Cargando…
Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review
BACKGROUND: Alzheimer’s disease (AD) is a neurodegenerative disorder commonly associated with deficits of cognition and changes in behavior. Mild cognitive impairment (MCI) is the prodromal stage of AD that is defined by slight cognitive decline. Not all with MCI progress to AD dementia. Thus, the a...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118884/ https://www.ncbi.nlm.nih.gov/pubmed/32241302 http://dx.doi.org/10.1186/s13643-020-01332-7 |
_version_ | 1783514656248168448 |
---|---|
author | Ahmadzadeh, Maryam Christie, Gregory J. Cosco, Theodore D. Moreno, Sylvain |
author_facet | Ahmadzadeh, Maryam Christie, Gregory J. Cosco, Theodore D. Moreno, Sylvain |
author_sort | Ahmadzadeh, Maryam |
collection | PubMed |
description | BACKGROUND: Alzheimer’s disease (AD) is a neurodegenerative disorder commonly associated with deficits of cognition and changes in behavior. Mild cognitive impairment (MCI) is the prodromal stage of AD that is defined by slight cognitive decline. Not all with MCI progress to AD dementia. Thus, the accurate prediction of progression to Alzheimer’s, particularly in the stage of MCI could potentially offer developing treatments to delay or prevent the transition process. The objective of the present study is to investigate the most recent neuroimaging procedures in the domain of prediction of transition from MCI to AD dementia for clinical applications and to systematically discuss the machine learning techniques used for the prediction of MCI conversion. METHODS: Electronic databases including PubMed, SCOPUS, and Web of Science will be searched from January 1, 2017, to the date of search commencement to provide a rapid review of the most recent studies that have investigated the prediction of conversion from MCI to Alzheimer’s using neuroimaging modalities in randomized trial or observational studies. Two reviewers will screen full texts of included papers using predefined eligibility criteria. Studies will be included if addressed research on AD dementia and MCI, explained the results in a way that would be able to report the performance measures such as the accuracy, sensitivity, and specificity. Only studies addressed Alzheimer’s type of dementia and its early-stage MCI using neuroimaging modalities will be included. We will exclude other forms of dementia such as vascular dementia, frontotemporal dementia, and Parkinson’s disease. The risk of bias in individual studies will be appraised using an appropriate tool. If feasible, we will conduct a random effects meta-analysis. Sensitivity analyses will be conducted to explore the potential sources of heterogeneity. DISCUSSION: The information gathered in our study will establish the extent of the evidence underlying the prediction of conversion to AD dementia from its early stage and will provide a rigorous and updated synthesis of neuroimaging modalities allied with the data analysis techniques used to measure the brain changes during the conversion process. SYSTEMATIC REVIEW REGISTRATION: PROSPERO,CRD42019133402 |
format | Online Article Text |
id | pubmed-7118884 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71188842020-04-07 Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review Ahmadzadeh, Maryam Christie, Gregory J. Cosco, Theodore D. Moreno, Sylvain Syst Rev Protocol BACKGROUND: Alzheimer’s disease (AD) is a neurodegenerative disorder commonly associated with deficits of cognition and changes in behavior. Mild cognitive impairment (MCI) is the prodromal stage of AD that is defined by slight cognitive decline. Not all with MCI progress to AD dementia. Thus, the accurate prediction of progression to Alzheimer’s, particularly in the stage of MCI could potentially offer developing treatments to delay or prevent the transition process. The objective of the present study is to investigate the most recent neuroimaging procedures in the domain of prediction of transition from MCI to AD dementia for clinical applications and to systematically discuss the machine learning techniques used for the prediction of MCI conversion. METHODS: Electronic databases including PubMed, SCOPUS, and Web of Science will be searched from January 1, 2017, to the date of search commencement to provide a rapid review of the most recent studies that have investigated the prediction of conversion from MCI to Alzheimer’s using neuroimaging modalities in randomized trial or observational studies. Two reviewers will screen full texts of included papers using predefined eligibility criteria. Studies will be included if addressed research on AD dementia and MCI, explained the results in a way that would be able to report the performance measures such as the accuracy, sensitivity, and specificity. Only studies addressed Alzheimer’s type of dementia and its early-stage MCI using neuroimaging modalities will be included. We will exclude other forms of dementia such as vascular dementia, frontotemporal dementia, and Parkinson’s disease. The risk of bias in individual studies will be appraised using an appropriate tool. If feasible, we will conduct a random effects meta-analysis. Sensitivity analyses will be conducted to explore the potential sources of heterogeneity. DISCUSSION: The information gathered in our study will establish the extent of the evidence underlying the prediction of conversion to AD dementia from its early stage and will provide a rigorous and updated synthesis of neuroimaging modalities allied with the data analysis techniques used to measure the brain changes during the conversion process. SYSTEMATIC REVIEW REGISTRATION: PROSPERO,CRD42019133402 BioMed Central 2020-04-02 /pmc/articles/PMC7118884/ /pubmed/32241302 http://dx.doi.org/10.1186/s13643-020-01332-7 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Protocol Ahmadzadeh, Maryam Christie, Gregory J. Cosco, Theodore D. Moreno, Sylvain Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review |
title | Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review |
title_full | Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review |
title_fullStr | Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review |
title_full_unstemmed | Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review |
title_short | Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer’s disease: protocol for a rapid systematic review |
title_sort | neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to alzheimer’s disease: protocol for a rapid systematic review |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118884/ https://www.ncbi.nlm.nih.gov/pubmed/32241302 http://dx.doi.org/10.1186/s13643-020-01332-7 |
work_keys_str_mv | AT ahmadzadehmaryam neuroimagingandanalyticalmethodsforstudyingthepathwaysfrommildcognitiveimpairmenttoalzheimersdiseaseprotocolforarapidsystematicreview AT christiegregoryj neuroimagingandanalyticalmethodsforstudyingthepathwaysfrommildcognitiveimpairmenttoalzheimersdiseaseprotocolforarapidsystematicreview AT coscotheodored neuroimagingandanalyticalmethodsforstudyingthepathwaysfrommildcognitiveimpairmenttoalzheimersdiseaseprotocolforarapidsystematicreview AT morenosylvain neuroimagingandanalyticalmethodsforstudyingthepathwaysfrommildcognitiveimpairmenttoalzheimersdiseaseprotocolforarapidsystematicreview |