Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins
Lee, A. D., Leporé, N., Brun, C., Chou, Y. Y., Barysheva, M., Chiang, M. C., Madsen, S. K., de Zubicaray, G. I., McMahon, K. L., Wright, M. J., Toga, A. W., & Thompson, P. M. (2009) Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins. In Yang, Guang-Zhong, Hawkes, David, Rueckert, Daniel, Noble, Alison, & Taylor, Chris (Eds.) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009: 12th International Conference, London, UK, September 20-24, 2009, Proceedings, Part I, Springer Berlin Heidelberg, London, UK, pp. 967-974.
Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.
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|Item Type:||Conference Paper|
|Divisions:||Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
|Copyright Owner:||Copyright 2009 Springer Berlin Heidelberg|
|Deposited On:||09 Oct 2015 02:53|
|Last Modified:||21 Oct 2015 02:00|
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