The multivariate A/C/E model and the genetics of fiber architecture
Lee, A. D., Leporé, N., Chou, Y. Y., Brun, C., Barysheva, M., Chang, M. C., Madsen, S. K., Toga, A. W., Thompson, P. M., McMahon, K. L., de Zubicaray, G. I., & Wright, M. J. (2009) The multivariate A/C/E model and the genetics of fiber architecture. In 2009 6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Proceedings, IEEE, Boston, USA, pp. 125-128.
We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework , and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.
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|Item Type:||Conference Paper|
|Keywords:||DTI, Genetics, Multivariate statistics, Twin studies|
|Divisions:||Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
|Copyright Owner:||Copyright 2009 IEEE|
|Deposited On:||09 Oct 2015 05:14|
|Last Modified:||21 Oct 2015 03:07|
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