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Volume-Based vs. Voxel-Based Brain Morphometry in Alzheimer's Disease Prediction

A. Roche, D. Schmitter, B. Maréchal, D. Ribes, A. Abdulkadir, M. Bach Cuadra, A. Daducci, C. Granziera, S. Klöppel, P. Maeder, R. Meuli, G. Krueger

Joint Annual Meeting of the of the International Society for Magnetic Resonance in Medicine and the European Society for Magnetic Resonance in Medicine and Biology (ISMRM/ESMRMB '14), Milano, Italian Republic, May 10-16, 2014, pp. 4733.



Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable accurate automated classification of AD patients, mild cognitive impaired (MCI) patients and elderly controls [1, 2]. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles…) as opposed to about a million voxel-wise gray matter (GM) concentrations. This work aims to experimentally compare voxel-based and volume-based brain morphometry for automated disease classification.

References

  1. S. Klöppel, C.M. Stonnington, C. Chu, B. Draganski, R.I. Scahill, J.D. Rohrer, N.C. Fox, C.R. Jack, J. Ashburner, R.S.J. Frackowiak, "Automatic Classification of MR Scans in Alzheimer's Disease," Brain—A Journal of Neurology, vol. 131, no. 3, pp. 681-689, March 2008.

  2. R. Cuingnet, E. Gerardin, J. Tessieras, G. Auzias, S. Lehéricy, M.-O. Habert, M. Chupin, H. Benali, O. Colliot, "Automatic Classification of Patients with Alzheimer's Disease from Structural MRI: A Comparison of Ten Methods Using the ADNI Database," NeuroImage, vol. 56, no. 2, pp. 766-781, May 15, 2011.


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