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Abstract #0688

Multi-Modal MRI Analysis with Disease Specific Spatial Filtering: Initial Testing to Predict Mild Cognitive Impairment Patients Who Convert to Alzheimers Disease

Kenichi Oishi1, Michelle M. Mielke2, Andreia V. Faria1, Michael I. Miller, Perer C. M. van Zijl3, Marilyn Albert4,5, Constantine G. Lyketsos2,5, Susumu Mori1,3

1Radiology, Johns Hopkins University, Baltimore, MD, USA; 2Psychiatry & Behavioral Sciences, Johns Hopkins University; 3Kennedy Krieger Institute; 4Neurology, Johns Hopkins University; 5The Johns Hopkins Alzheimers Disease Research Center

We have developed an image analysis tool in which information extracted from multiple MRI modalities, using disease-specific spatial filters, is combined to generate a disease score. This tool was tested as an automated method to predict the conversion from amnestic mild cognitive impairment (aMCI) to Alzheimers disease (AD). We created disease-specific filters for each modality and optimized the combination to separate AD from control participants, using a training dataset, and applied the tool to calculate disease scores of 22 aMCI patients. The disease score predicted the conversion better than a single-modality approach, indicating the potential value for clinical application.