Reduced FDG-PET brain metabolism and executive function predict clinical progression in elderly healthy subjects☆☆☆

[1]  Jean-François Dartigues,et al.  Short- versus long-term prediction of dementia among subjects with low and high educational levels , 2013, Alzheimer's & Dementia.

[2]  H. Amièva,et al.  Prevalence of Word Retrieval Complaint and Prediction of Dementia in a Population-Based Study of Elderly Subjects , 2013, Dementia and Geriatric Cognitive Disorders.

[3]  Stephen F. Carter,et al.  Prediction of dementia in MCI patients based on core diagnostic markers for Alzheimer disease , 2013, Neurology.

[4]  Michael Wagner,et al.  Glucose metabolism, gray matter structure, and memory decline in subjective memory impairment , 2012, Neurology.

[5]  Paul Edison,et al.  A European multicentre PET study of fibrillar amyloid in Alzheimer’s disease , 2012, European Journal of Nuclear Medicine and Molecular Imaging.

[6]  C. Jack,et al.  Prediction of conversion from mild cognitive impairment to Alzheimer's disease dementia based upon biomarkers and neuropsychological test performance , 2012, Neurobiology of Aging.

[7]  F. Jessen,et al.  Glucose metabolism, gray matter structure and memory decline in subjective memory impairment , 2012, Alzheimer's & Dementia.

[8]  A. Dale,et al.  Amyloid-β--associated clinical decline occurs only in the presence of elevated P-tau. , 2012, Archives of neurology.

[9]  Mark Jenkinson,et al.  Structural MRI changes detectable up to ten years before clinical Alzheimer's disease , 2012, Neurobiology of Aging.

[10]  B. Dickerson,et al.  MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults , 2012, Neurology.

[11]  Norbert Schuff,et al.  Identifying cognitively healthy elderly individuals with subsequent memory decline by using automated MR temporoparietal volumes. , 2011, Radiology.

[12]  Nick C Fox,et al.  The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[13]  Denise C. Park,et al.  Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[14]  J. Morris,et al.  The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[15]  R. Killiany,et al.  Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults , 2011, Neurology.

[16]  Anderson M. Winkler,et al.  Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies , 2010, NeuroImage.

[17]  D. Wedding.  Halstead‐Reitan Neuropsychological Test Battery , 2010 .

[18]  Nikolaus Weiskopf,et al.  A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging , 2009, NeuroImage.

[19]  M. Sarazin,et al.  Faculty Opinions recommendation of Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. , 2009 .

[20]  Jeffrey A. Fessler,et al.  Reducing between scanner differences in multi-center PET studies , 2009, NeuroImage.

[21]  R. Petersen,et al.  Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects , 2009, Annals of neurology.

[22]  S. Santi,et al.  Hippocampal hypometabolism predicts cognitive decline from normal aging , 2008, Neurobiology of Aging.

[23]  Nick C Fox,et al.  The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods , 2008, Journal of magnetic resonance imaging : JMRI.

[24]  John Ashburner,et al.  A fast diffeomorphic image registration algorithm , 2007, NeuroImage.

[25]  P. Scheltens,et al.  Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria , 2007, The Lancet Neurology.

[26]  F. Schmitt,et al.  Brain structural alterations before mild cognitive impairment , 2007, Neurology.

[27]  Felice Sun,et al.  Brain imaging evidence of preclinical Alzheimer's disease in normal aging , 2006, Annals of neurology.

[28]  S. Graham,et al.  An fMRI study of the Trail Making Test , 2005, Neuropsychologia.

[29]  Karl J. Friston,et al.  Unified segmentation , 2005, NeuroImage.

[30]  L. Mosconi,et al.  Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease , 2005, European Journal of Nuclear Medicine and Molecular Imaging.

[31]  Henry Rusinek,et al.  Regional brain atrophy rate predicts future cognitive decline: 6-year longitudinal MR imaging study of normal aging. , 2003, Radiology.

[32]  M. Bobinski,et al.  Prediction of cognitive decline in normal elderly subjects with 2-[18F]fluoro-2-deoxy-d-glucose/positron-emission tomography (FDG/PET) , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[33]  A. Evans,et al.  Correction for partial volume effects in PET: principle and validation. , 1998, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[34]  P. Rubé,et al.  L’examen Clinique en Psychologie , 1959 .

[35]  T. Robbins,et al.  Differential cognitive deterioration in dementia: a two year longitudinal study. , 2011, Journal of Alzheimer's disease : JAD.

[36]  A. Hofman,et al.  Use of hippocampal and amygdalar volumes on magnetic resonance imaging to predict dementia in cognitively intact elderly people. , 2006, Archives of general psychiatry.

[37]  J. Barth,et al.  The Halstead-Reitan Neuropsychological Test Battery. , 2000 .

[38]  Jacob Cohen.  QUANTITATIVE METHODS IN PSYCHOLOGY A Power Primer , 1992 .

[39]  Alan C. Evans,et al.  NeuroImage: Clinical , 2022 .