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A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer’s Disease (REMEMBER)

BACKGROUND: Magnetic resonance imaging (MRI) acquisition/processing techniques assess brain volumes to explore neurodegeneration in Alzheimer’s disease (AD). OBJECTIVE: We examined the clinical utility of MSmetrix and investigated if automated MRI volumes could discriminate between groups covering t...

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Autores principales: Niemantsverdriet, Ellis, Ribbens, Annemie, Bastin, Christine, Benoit, Florence, Bergmans, Bruno, Bier, Jean-Christophe, Bladt, Roxanne, Claes, Lene, De Deyn, Peter Paul, Deryck, Olivier, Hanseeuw, Bernard, Ivanoiu, Adrian, Lemper, Jean-Claude, Mormont, Eric, Picard, Gaëtane, Salmon, Eric, Segers, Kurt, Sieben, Anne, Smeets, Dirk, Struyfs, Hanne, Thiery, Evert, Tournoy, Jos, Triau, Eric, Vanbinst, Anne-Marie, Versijpt, Jan, Bjerke, Maria, Engelborghs, Sebastiaan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6004934/
https://www.ncbi.nlm.nih.gov/pubmed/29782314
http://dx.doi.org/10.3233/JAD-171140
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author Niemantsverdriet, Ellis
Ribbens, Annemie
Bastin, Christine
Benoit, Florence
Bergmans, Bruno
Bier, Jean-Christophe
Bladt, Roxanne
Claes, Lene
De Deyn, Peter Paul
Deryck, Olivier
Hanseeuw, Bernard
Ivanoiu, Adrian
Lemper, Jean-Claude
Mormont, Eric
Picard, Gaëtane
Salmon, Eric
Segers, Kurt
Sieben, Anne
Smeets, Dirk
Struyfs, Hanne
Thiery, Evert
Tournoy, Jos
Triau, Eric
Vanbinst, Anne-Marie
Versijpt, Jan
Bjerke, Maria
Engelborghs, Sebastiaan
author_facet Niemantsverdriet, Ellis
Ribbens, Annemie
Bastin, Christine
Benoit, Florence
Bergmans, Bruno
Bier, Jean-Christophe
Bladt, Roxanne
Claes, Lene
De Deyn, Peter Paul
Deryck, Olivier
Hanseeuw, Bernard
Ivanoiu, Adrian
Lemper, Jean-Claude
Mormont, Eric
Picard, Gaëtane
Salmon, Eric
Segers, Kurt
Sieben, Anne
Smeets, Dirk
Struyfs, Hanne
Thiery, Evert
Tournoy, Jos
Triau, Eric
Vanbinst, Anne-Marie
Versijpt, Jan
Bjerke, Maria
Engelborghs, Sebastiaan
author_sort Niemantsverdriet, Ellis
collection PubMed
description BACKGROUND: Magnetic resonance imaging (MRI) acquisition/processing techniques assess brain volumes to explore neurodegeneration in Alzheimer’s disease (AD). OBJECTIVE: We examined the clinical utility of MSmetrix and investigated if automated MRI volumes could discriminate between groups covering the AD continuum and could be used as a predictor for clinical progression. METHODS: The Belgian Dementia Council initiated a retrospective, multi-center study and analyzed whole brain (WB), grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), cortical GM (CGM) volumes, and WM hyperintensities (WMH) using MSmetrix in the AD continuum. Baseline (n = 887) and follow-up (FU, n = 95) T1-weighted brain MRIs and time-linked neuropsychological data were available. RESULTS: The cohort consisted of cognitively healthy controls (HC, n = 93), subjective cognitive decline (n = 102), mild cognitive impairment (MCI, n = 379), and AD dementia (n = 313). Baseline WB and GM volumes could accurately discriminate between clinical diagnostic groups and were significantly decreased with increasing cognitive impairment. MCI patients had a significantly larger change in WB, GM, and CGM volumes based on two MRIs (n = 95) compared to HC (FU>24months, p = 0.020). Linear regression models showed that baseline atrophy of WB, GM, CGM, and increased CSF volumes predicted cognitive impairment. CONCLUSION: WB and GM volumes extracted by MSmetrix could be used to define the clinical spectrum of AD accurately and along with CGM, they are able to predict cognitive impairment based on (decline in) MMSE scores. Therefore, MSmetrix can support clinicians in their diagnostic decisions, is able to detect clinical disease progression, and is of help to stratify populations for clinical trials.
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spelling pubmed-60049342018-06-25 A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer’s Disease (REMEMBER) Niemantsverdriet, Ellis Ribbens, Annemie Bastin, Christine Benoit, Florence Bergmans, Bruno Bier, Jean-Christophe Bladt, Roxanne Claes, Lene De Deyn, Peter Paul Deryck, Olivier Hanseeuw, Bernard Ivanoiu, Adrian Lemper, Jean-Claude Mormont, Eric Picard, Gaëtane Salmon, Eric Segers, Kurt Sieben, Anne Smeets, Dirk Struyfs, Hanne Thiery, Evert Tournoy, Jos Triau, Eric Vanbinst, Anne-Marie Versijpt, Jan Bjerke, Maria Engelborghs, Sebastiaan J Alzheimers Dis Research Article BACKGROUND: Magnetic resonance imaging (MRI) acquisition/processing techniques assess brain volumes to explore neurodegeneration in Alzheimer’s disease (AD). OBJECTIVE: We examined the clinical utility of MSmetrix and investigated if automated MRI volumes could discriminate between groups covering the AD continuum and could be used as a predictor for clinical progression. METHODS: The Belgian Dementia Council initiated a retrospective, multi-center study and analyzed whole brain (WB), grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), cortical GM (CGM) volumes, and WM hyperintensities (WMH) using MSmetrix in the AD continuum. Baseline (n = 887) and follow-up (FU, n = 95) T1-weighted brain MRIs and time-linked neuropsychological data were available. RESULTS: The cohort consisted of cognitively healthy controls (HC, n = 93), subjective cognitive decline (n = 102), mild cognitive impairment (MCI, n = 379), and AD dementia (n = 313). Baseline WB and GM volumes could accurately discriminate between clinical diagnostic groups and were significantly decreased with increasing cognitive impairment. MCI patients had a significantly larger change in WB, GM, and CGM volumes based on two MRIs (n = 95) compared to HC (FU>24months, p = 0.020). Linear regression models showed that baseline atrophy of WB, GM, CGM, and increased CSF volumes predicted cognitive impairment. CONCLUSION: WB and GM volumes extracted by MSmetrix could be used to define the clinical spectrum of AD accurately and along with CGM, they are able to predict cognitive impairment based on (decline in) MMSE scores. Therefore, MSmetrix can support clinicians in their diagnostic decisions, is able to detect clinical disease progression, and is of help to stratify populations for clinical trials. IOS Press 2018-05-30 /pmc/articles/PMC6004934/ /pubmed/29782314 http://dx.doi.org/10.3233/JAD-171140 Text en © 2018 – IOS Press and the authors. All rights reserved https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Niemantsverdriet, Ellis
Ribbens, Annemie
Bastin, Christine
Benoit, Florence
Bergmans, Bruno
Bier, Jean-Christophe
Bladt, Roxanne
Claes, Lene
De Deyn, Peter Paul
Deryck, Olivier
Hanseeuw, Bernard
Ivanoiu, Adrian
Lemper, Jean-Claude
Mormont, Eric
Picard, Gaëtane
Salmon, Eric
Segers, Kurt
Sieben, Anne
Smeets, Dirk
Struyfs, Hanne
Thiery, Evert
Tournoy, Jos
Triau, Eric
Vanbinst, Anne-Marie
Versijpt, Jan
Bjerke, Maria
Engelborghs, Sebastiaan
A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer’s Disease (REMEMBER)
title A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer’s Disease (REMEMBER)
title_full A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer’s Disease (REMEMBER)
title_fullStr A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer’s Disease (REMEMBER)
title_full_unstemmed A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer’s Disease (REMEMBER)
title_short A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer’s Disease (REMEMBER)
title_sort retrospective belgian multi-center mri biomarker study in alzheimer’s disease (remember)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6004934/
https://www.ncbi.nlm.nih.gov/pubmed/29782314
http://dx.doi.org/10.3233/JAD-171140
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