OBJECTIVE: To compare volumetric MRI of whole brain and medial temporal lobe structures to clinical measures for predicting progression from amnestic mild cognitive impairment (MCI) to Alzheimer disease (AD). METHODS: Baseline MRI scans from 129 subjects withamnestic MCI were obtained from participants in the Alzheimer's Disease Cooperative Study group's randomized, placebo-controlled clinical drug trial of donepezil, vitamin E, or placebo. Measures of whole brain, ventricular, hippocampal, and entorhinal cortex volumes were acquired. Participants were followed with clinical and cognitive evaluations until formal criteria for AD were met, or completion of 36 months of follow-up. Logistic regression modeling was done to assess the predictive value of all MRI measures, risk factors such as APOE genotype, age, family history of AD, education, sex, and cognitive test scores for progression to AD. Least angle regression modeling was used to determine which variables would produce an optimal predictive model, and whether adding MRI measures to a model with only clinical measures would improve predictive accuracy. RESULTS: Of the four MRI measures evaluated, only ventricular volumes and hippocampal volumes were predictive of progression to AD. Maximal predictive accuracy using only MRI measures was obtained by hippocampal volumes by themselves (60.4%). When clinical variables were added to the model, the predictive accuracy increased to 78.8%. Use of MRI measures did not improve predictive accuracy beyond that obtained by cognitive measures alone. APOE status, MRI, or demographic variables were not necessary for the optimal predictive model. This optimal model included the Delayed 10-word list recall, New York University Delayed Paragraph Recall, and the Alzheimer's Disease Assessment Scale-Cognitive Subscale total score. CONCLUSION: In moderate stages of amnestic mild cognitive impairment, common cognitive tests provide better predictive accuracy than measures of whole brain, ventricular, entorhinal cortex, or hippocampal volumes for assessing progression to Alzheimer disease.
RCT Entities:
OBJECTIVE: To compare volumetric MRI of whole brain and medial temporal lobe structures to clinical measures for predicting progression from amnestic mild cognitive impairment (MCI) to Alzheimer disease (AD). METHODS: Baseline MRI scans from 129 subjects with amnestic MCI were obtained from participants in the Alzheimer's Disease Cooperative Study group's randomized, placebo-controlled clinical drug trial of donepezil, vitamin E, or placebo. Measures of whole brain, ventricular, hippocampal, and entorhinal cortex volumes were acquired. Participants were followed with clinical and cognitive evaluations until formal criteria for AD were met, or completion of 36 months of follow-up. Logistic regression modeling was done to assess the predictive value of all MRI measures, risk factors such as APOE genotype, age, family history of AD, education, sex, and cognitive test scores for progression to AD. Least angle regression modeling was used to determine which variables would produce an optimal predictive model, and whether adding MRI measures to a model with only clinical measures would improve predictive accuracy. RESULTS: Of the four MRI measures evaluated, only ventricular volumes and hippocampal volumes were predictive of progression to AD. Maximal predictive accuracy using only MRI measures was obtained by hippocampal volumes by themselves (60.4%). When clinical variables were added to the model, the predictive accuracy increased to 78.8%. Use of MRI measures did not improve predictive accuracy beyond that obtained by cognitive measures alone. APOE status, MRI, or demographic variables were not necessary for the optimal predictive model. This optimal model included the Delayed 10-word list recall, New York University Delayed Paragraph Recall, and the Alzheimer's Disease Assessment Scale-Cognitive Subscale total score. CONCLUSION: In moderate stages of amnestic mild cognitive impairment, common cognitive tests provide better predictive accuracy than measures of whole brain, ventricular, entorhinal cortex, or hippocampal volumes for assessing progression to Alzheimer disease.
Authors: Kewei Chen; Napatkamon Ayutyanont; Jessica B S Langbaum; Adam S Fleisher; Cole Reschke; Wendy Lee; Xiaofen Liu; Dan Bandy; Gene E Alexander; Paul M Thompson; Leslie Shaw; John Q Trojanowski; Clifford R Jack; Susan M Landau; Norman L Foster; Danielle J Harvey; Michael W Weiner; Robert A Koeppe; William J Jagust; Eric M Reiman Journal: Neuroimage Date: 2011-01-27 Impact factor: 6.556
Authors: Shannon L Risacher; Li Shen; John D West; Sungeun Kim; Brenna C McDonald; Laurel A Beckett; Danielle J Harvey; Clifford R Jack; Michael W Weiner; Andrew J Saykin Journal: Neurobiol Aging Date: 2010-08 Impact factor: 4.673
Authors: David A Bennett; Robert S Wilson; Zoe Arvanitakis; Patricia A Boyle; Leyla de Toledo-Morrell; Julie A Schneider Journal: J Alzheimers Dis Date: 2013 Impact factor: 4.472
Authors: Wai Yen Loh; Alan Connelly; Jeanie L Y Cheong; Alicia J Spittle; Jian Chen; Christopher Adamson; Zohra M Ahmadzai; Lillian Gabra Fam; Sandra Rees; Katherine J Lee; Lex W Doyle; Peter J Anderson; Deanne K Thompson Journal: Neuroinformatics Date: 2016-01
Authors: Yi-Yu Chou; Natasha Leporé; Christina Avedissian; Sarah K Madsen; Neelroop Parikshak; Xue Hua; Leslie M Shaw; John Q Trojanowski; Michael W Weiner; Arthur W Toga; Paul M Thompson Journal: Neuroimage Date: 2009-02-21 Impact factor: 6.556