Multi-modal MRI analysis with disease-specific spatial filtering: Initial testing to predict mild cognitive impairment patients who convert to Alzheimer's disease

Kenichi Oishi, Kazi Akhter, Michelle Mielke, Can Ceritoglu, Jiangyang Zhang, Hangyi Jiang, Xin Li, Laurent Younes, Michael I. Miller, Peter C.M. van Zijl, Marilyn Albert, Constantine G. Lyketsos, Susumu Mori

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Background: Alterations of the gray and white matter have been identified in Alzheimer's disease (AD) by structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). However, whether the combination of these modalities could increase the diagnostic performance is unknown. Methods: Participants included 19 AD patients, 22 amnestic mild cognitive impairment (aMCI) patients, and 22 cognitively normal elderly (NC). The aMCI group was further divided into an "aMCI-converter" group (converted to AD dementia within 3 years), and an "aMCI-stable" group who did not convert in this time period. A T1-weighted image, aT2 map, and a DTI of each participant were normalized, and voxel-based comparisons between AD and NC groups were performed. Regions-of-interest, which defined the areas with significant differences between AD and NC, were created for each modality and named "disease-specific spatial filters" (DSF). Linear discriminant analysis was used to optimize the combination of multiple MRI measurements extracted by DSF to effectively differentiate AD from NC.The resultant DSF and the discriminant function were applied to the aMCI group to investigate the power to differentiate the aMCI-converters from the aMCI-stable patients. Results:The multi-modal approach with AD-specific filters led to a predictive model with an area under the receiver operating characteristic curve (AUC) of 0.93, in differentiating aMCI-converters from aMCI-stable patients.This AUC was better than that of a single-contrast-based approach, such as T1-based morphometry or diffusion anisotropy analysis. Conclusion: The multi-modal approach has the potential to increase the value of MRI in predicting conversion from aMCI to AD.

Original languageEnglish (US)
Article numberArticle 54
JournalFrontiers in Neurology
VolumeAUG
DOIs
StatePublished - 2011

Keywords

  • Alzheimer's disease
  • Diffusion tensor imaging
  • Magnetic resonance imaging
  • Mild cognitive impairment
  • Multi-modal disease-specific spatial filtering
  • Pre-dementia phase
  • White matter

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology

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