Analysis of anatomical variability using diffeomorphic iterative centroid in patients with Alzheimer's disease

Abstract

This article presents a new approach for template-based analysis of anatomical variability in populations, in the framework of Large Deformation Diffeomorphic Metric Mappings and mathematical currents. We propose a fast approach in which the template is computed using a diffeomorphic iterative centroid method. Statistical analysis is then performed on the initial momenta that define the deformations between the centroid and each individual subject. We applied the approach to study the variability of the hippocampus in 134 patients with Alzheimer's disease (AD) and 160 elderly control subjects. We show that this approach can describe the main modes of variability of the two populations and can predict the performance to a memory test in AD patients.

Keywords::

• shape analysis
• LDDMM
• diffeomorphic iterative centroid
• hippocampus
• Alzheimer

Notes

^1. (adni.loni.usc.edu). The Principal Investigator of this initiative is Michael W. Weiner, MD, VA Medical Center and University of California – San Francisco. The investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report A complete listing of ADNI investigators can be found at: adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. Data collection and sharing for this project were funded by the ADNI (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012).

Additional information

Funding

The research leading to these results has received funding from ANR (project HM-TC, [grant number ANR-09-EMER-006] and project KaraMetria, [grant number ANR-09-BLAN-0332]), from the CATI Project (Fondation Plan Alzheimer) and from the programme Investissements d'avenir ANR-10-IAIHU-06.