title: Neurostructural predictors of Alzheimer's disease: a meta-analysis of VBM studies.
abstract: The identification of biological markers at early stages of Alzheimer's disease (AD) contributes to diagnostic accuracy and adds prognostic value. However, in spite of recent developments, results of neurostructural imaging studies on predicting conversion to AD are not uniform. We conducted a systematic review of voxel-based morphometry (VBM) studies about the neurostructural predictors of conversion to AD. Ten studies met inclusion criteria and nine reported baseline regional gray matter (GM) atrophy in mild cognitive impairment (MCI) or healthy subjects who progressed to AD. Using the method of Activation Likelihood Estimation, we meta-analyzed the coordinates from the six longitudinal VBM studies that enrolled subjects with amnestic MCI (aMCI) at baseline. These comprised a total of 429 aMCI subjects, of which 142 converted to AD. Meta-analysis yielded one significant cluster of GM volumetric reduction in aMCI patients who converted to AD, located in the left hippocampus and parahippocampal gyrus. In conclusion, left medial temporal lobe atrophy is the most consistent neurostructural biomarker to predict conversion from aMCI to AD.
authors.affiliation: Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, SP, Brazil. kobuti@yahoo.com
authors.forename: Luiz K
authors.initials: LK
authors.lastname: Ferreira
authors.forename: Breno S
authors.initials: BS
authors.lastname: Diniz
authors.forename: Orestes V
authors.initials: OV
authors.lastname: Forlenza
authors.forename: Geraldo F
authors.initials: GF
authors.lastname: Busatto
authors.forename: Marcus V
authors.initials: MV
authors.lastname: Zanetti
mesh_terms: D000544:Alzheimer Disease / Q000150:complications / Q000175:diagnosis*; D001921:Brain / Q000473:pathology*; D003072:Cognition Disorders / Q000209:etiology; D006801:Humans; D059906:Neuroimaging / Q000379:methods; D011237:Predictive Value of Tests