Brain MRI hippocampal volume and prediction of clinical status in a mild cognitive impairment trial

Michael Grundman, Drahomira Sencakova, Clifford R. Jack, Ronald C. Petersen, Hyun T. Kim, Arlan Schultz, Myron F. Weiner, Charles DeCarli, Steven T. DeKosky, Christopher Van Dyck, Ronald G. Thomas, Leon J. Thal

Research output: Contribution to journalArticlepeer-review

114 Scopus citations


Mild Cognitive Impairment (MCI) is considered a transitional stage in the pathogenesis of Alzheimer's disease; however, not all MCI patients progress to clinically defined AD or decline at identical rates. Hippocampal atrophy, as measured by Magnetic Resonance Imaging (MRI), may be a marker for hippocampal pathology in patients with MCI and predict a more rapid deterioration to clinical AD. In this study, we used MRI data from an ongoing MCI clinical trial to determine whether MRI hippocampal volume at baseline was associated with cognitive and functional performance in MCI subjects and whether it predicted those individuals who were more likely to develop AD. We performed correlational analyses between the MRI hippocampal volumes at study entry and the subjects' concurrent performance on neuropsychological measures and clinical ratings. Larger hippocampal volume was associated with better performance on tests of memory, general cognition, and overall clinical ratings. Further analyses suggested that a smaller baseline hippocampal volume may be associated with a higher risk of developing clinical AD. As the trial is still ongoing, these results require confirmation once the trial is completed. In summary, these data suggest that MRI hippocampal volume may be a useful correlate of disease severity in MCI subjects and a prognostic indicator of subsequent AD.

Original languageEnglish (US)
Pages (from-to)23-27
Number of pages5
JournalJournal of Molecular Neuroscience
Issue number1-2
StatePublished - 2002


  • Alzheimer's disease
  • Clinical trial
  • Hippocampal volume
  • MRI
  • Mild Cognitive Impairment

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience


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