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 Albert^4,5, Constantine G. Lyketsos^2,5, Susumu Mori^1,3

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.