Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis
Psychiatry Investigation
;
: 205-215, 2017.
Artículo
en Inglés
| WPRIM
| ID: wpr-166079
ABSTRACT
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.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Imagen por Resonancia Magnética
/
Biomarcadores
/
Estudios de Seguimiento
/
Corteza Entorrinal
/
Tomografía de Emisión de Positrones
/
Enfermedad de Alzheimer
/
Disfunción Cognitiva
/
Amiloide
Tipo de estudio:
Estudio observacional
/
Estudio pronóstico
/
Factores de riesgo
/
Estudio de tamizaje
/
Revisiones Sistemáticas Evaluadas
Límite:
Humanos
Idioma:
Inglés
Revista:
Psychiatry Investigation
Año:
2017
Tipo del documento:
Artículo
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