Cargando…
Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis
OBJECTIVE: The aim of this study was to explore the prognostic values of biomarkers of neurodegeneration as measured by magnetic resonance imaging (MRI) and amyloid burden as measured by amyloid positron emission tomography (PET) in predicting conversion to Alzheimer's disease (AD) in patients...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Neuropsychiatric Association
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355020/ https://www.ncbi.nlm.nih.gov/pubmed/28326120 http://dx.doi.org/10.4306/pi.2017.14.2.205 |
_version_ | 1782515442049351680 |
---|---|
author | Seo, Eun Hyun Park, Woon Yeong Choo, IL Han |
author_facet | Seo, Eun Hyun Park, Woon Yeong Choo, IL Han |
author_sort | Seo, Eun Hyun |
collection | PubMed |
description | OBJECTIVE: The aim of this study was to explore the prognostic values of biomarkers of neurodegeneration as measured by magnetic resonance imaging (MRI) and amyloid burden as measured by amyloid positron emission tomography (PET) in predicting conversion to Alzheimer's disease (AD) in patients with mild cognitive impairment (MCI). METHODS: PubMed and EMBASE databases were searched for structural MRI or amyloid PET imaging studies published between January 2000 and July 2014 that reported conversion to AD in patients with MCI. Means and standard deviations or individual numbers of biomarkers with positive or negative status at baseline and corresponding numbers of patients who had progressed to AD at follow-up were retrieved from each study. The effect size of each biomarker was expressed as Hedges's g. RESULTS: Twenty-four MRI studies and 8 amyloid PET imaging studies were retrieved. 674 of the 1741 participants (39%) developed AD. The effect size for predicting conversion to AD was 0.770 [95% confidence interval (CI) 0.607–0.934] for across MRI and 1.316 (95% CI 0.920–1.412) for amyloid PET imaging (p<0.001). The effect size was 1.256 (95% CI 0.902–1.609) for entorhinal cortex volume from MRI. CONCLUSION: Our study suggests that volumetric MRI measurement may be useful for the early detection of AD. |
format | Online Article Text |
id | pubmed-5355020 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Korean Neuropsychiatric Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-53550202017-03-21 Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis Seo, Eun Hyun Park, Woon Yeong Choo, IL Han Psychiatry Investig Original Article OBJECTIVE: The aim of this study was to explore the prognostic values of biomarkers of neurodegeneration as measured by magnetic resonance imaging (MRI) and amyloid burden as measured by amyloid positron emission tomography (PET) in predicting conversion to Alzheimer's disease (AD) in patients with mild cognitive impairment (MCI). METHODS: PubMed and EMBASE databases were searched for structural MRI or amyloid PET imaging studies published between January 2000 and July 2014 that reported conversion to AD in patients with MCI. Means and standard deviations or individual numbers of biomarkers with positive or negative status at baseline and corresponding numbers of patients who had progressed to AD at follow-up were retrieved from each study. The effect size of each biomarker was expressed as Hedges's g. RESULTS: Twenty-four MRI studies and 8 amyloid PET imaging studies were retrieved. 674 of the 1741 participants (39%) developed AD. The effect size for predicting conversion to AD was 0.770 [95% confidence interval (CI) 0.607–0.934] for across MRI and 1.316 (95% CI 0.920–1.412) for amyloid PET imaging (p<0.001). The effect size was 1.256 (95% CI 0.902–1.609) for entorhinal cortex volume from MRI. CONCLUSION: Our study suggests that volumetric MRI measurement may be useful for the early detection of AD. Korean Neuropsychiatric Association 2017-03 2017-03-06 /pmc/articles/PMC5355020/ /pubmed/28326120 http://dx.doi.org/10.4306/pi.2017.14.2.205 Text en Copyright © 2017 Korean Neuropsychiatric Association http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://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 | Original Article Seo, Eun Hyun Park, Woon Yeong Choo, IL Han Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis |
title | Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis |
title_full | Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis |
title_fullStr | Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis |
title_full_unstemmed | Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis |
title_short | Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis |
title_sort | structural mri and amyloid pet imaging for prediction of conversion to alzheimer's disease in patients with mild cognitive impairment: a meta-analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355020/ https://www.ncbi.nlm.nih.gov/pubmed/28326120 http://dx.doi.org/10.4306/pi.2017.14.2.205 |
work_keys_str_mv | AT seoeunhyun structuralmriandamyloidpetimagingforpredictionofconversiontoalzheimersdiseaseinpatientswithmildcognitiveimpairmentametaanalysis AT parkwoonyeong structuralmriandamyloidpetimagingforpredictionofconversiontoalzheimersdiseaseinpatientswithmildcognitiveimpairmentametaanalysis AT chooilhan structuralmriandamyloidpetimagingforpredictionofconversiontoalzheimersdiseaseinpatientswithmildcognitiveimpairmentametaanalysis |