Coupe, Pierrick2; Manjon, Jose3; Fonov, Vladimir4; Eskildsen, Simon Fristed5; Collins, D. Louis4
1 Department of Clinical Medicine - Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Health, Aarhus University2 Laboratoire Bordelais de Recherche en Informatique, Unité Mixte de Recherche CNRS (UMR 5800)3 Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universidad Politécnica de Valencia4 McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University5 Department of Clinical Medicine - Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Health, Aarhus University
Background: While widely used to detect morphological differences between groups, Voxel-Based Morphometry (VBM) is based on the assumption of one-to-one anatomical mapping between subjects and Gaussian distributions of focal tissue densities during statistical testing. To make data fit this model, tissue densities are blurred with large kernels at the expense of focal accuracy. To these issues, we propose a new Patch-Based Morphometry (PBM) method derived from our recently proposed innovative method to detect fine anatomical changes in MRI called Scoring by Nonlocal Image Patch Estimator . SNIPE takes advantage of non-local analysis to handle the one-to-many mapping between brain anatomies. In this study, we extend SNIPE to the whole brain before comparing populations with PBM scores. Methods: We randomly selected 50 MRI from cognitive normal (CN) subjects and 50 MRI from AD patients from the ADNI database. Step 1: the 100 images were processed as described in (inhomogeneity correction, intensity normalization and rigid registration to MNI-ICBM152-nonlinear). Through a leave-one-out procedure, SNIPE was applied on each of the MRI scans using 30 images from each population as training templates. Step 2: all grading maps were nonlinearly registered to the MNI-ICBM152-nonlinear template with ANIMAL . Step 3: a non-parametric Kruskall-Wallis test was performed at each voxel to estimate statistical differences between populations. Results: Examples of grading maps are presented in Figure 1. Figure 2 shows the p-values overlaid on the MNI-template. Maximum differences between AD and CN were found in hippocampus and para-hippocampal areas, entorhinal cortex and in the temporal lobe around the lateral sulci and insula. Moreover, diffuse differences appear within the gray matter. These results are consistent with previous VBM results . We also noted an important difference around the superior mammillary notches as previously reported in volumetric studies . Conclusion: In this proof of concept study, we showed that PBM produces results consistent with previously published VBM studies. However, contrary to VBM, these results were obtained without a blurring step since PBM can work at the voxel resolution. Further work will investigate optimal parameters for SNIPE and the possibility of using multivariate tests.
Alzheimer; patch; morphometry; early detection
Main Research Area:
Alzheimer's Association International Conference, 2012