Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

Agatha D. Lee; Natasha Leporé; Caroline Brun; Yi Yu Chou; Marina Barysheva; Ming Chang Chiang; Sarah K. Madsen; Greig I. De Zubicaray; Katie L. McMahon; Margaret J. Wright; Arthur W. Toga; Paul M. Thompson

doi:10.1007/978-3-642-04268-3_119

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

Agatha D. Lee
, Natasha Leporé
, Caroline Brun
, Yi Yu Chou
, Marina Barysheva
, Ming Chang Chiang
, Sarah K. Madsen
, Greig I. De Zubicaray
, Katie L. McMahon
, Margaret J. Wright
, Arthur W. Toga
, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

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 [1]. 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.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 12th International Conference, Proceedings
Pages	967-974
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-04268-3_119
State	Published - 2009
Externally published	Yes
Event	12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom Duration: 20 Sep 2009 → 24 Sep 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	5761 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
Country/Territory	United Kingdom
City	London
Period	20/09/09 → 24/09/09

Access to Document

10.1007/978-3-642-04268-3_119

Cite this

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 Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 12th International Conference, Proceedings (PART 1 ed., pp. 967-974). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5761 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-04268-3_119

Lee, Agatha D. ; Leporé, Natasha ; Brun, Caroline et al. / Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 12th International Conference, Proceedings. PART 1. ed. 2009. pp. 967-974 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{1279dab9d53b40369b475cb5444fd327,

title = "Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins",

abstract = "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 [1]. 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.",

author = "Lee, \{Agatha D.\} and Natasha Lepor{\'e} and Caroline Brun and Chou, \{Yi Yu\} and Marina Barysheva and Chiang, \{Ming Chang\} and Madsen, \{Sarah K.\} and \{De Zubicaray\}, \{Greig I.\} and McMahon, \{Katie L.\} and Wright, \{Margaret J.\} and Toga, \{Arthur W.\} and Thompson, \{Paul M.\}",

year = "2009",

doi = "10.1007/978-3-642-04268-3\_119",

language = "English",

isbn = "3642042678",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 1",

pages = "967--974",

booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 12th International Conference, Proceedings",

edition = "PART 1",

note = "12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 ; Conference date: 20-09-2009 Through 24-09-2009",

}

Lee, AD, Leporé, N, Brun, C, Chou, YY, Barysheva, M, Chiang, MC, Madsen, SK, De Zubicaray, GI, McMahon, KL, Wright, MJ, Toga, AW & Thompson, PM 2009, Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins. in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 12th International Conference, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5761 LNCS, pp. 967-974, 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, London, United Kingdom, 20/09/09. https://doi.org/10.1007/978-3-642-04268-3_119

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins. / Lee, Agatha D.; Leporé, Natasha; Brun, Caroline et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 12th International Conference, Proceedings. PART 1. ed. 2009. p. 967-974 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5761 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Brun, Caroline

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AU - Barysheva, Marina

AU - Chiang, Ming Chang

AU - Madsen, Sarah K.

AU - De Zubicaray, Greig I.

AU - McMahon, Katie L.

AU - Wright, Margaret J.

AU - Toga, Arthur W.

AU - Thompson, Paul M.

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AB - 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 [1]. 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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AN - SCOPUS:79955662527

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SN - 9783642042676

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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T2 - 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009

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ER -

Lee AD, Leporé N, Brun C, Chou YY, Barysheva M, Chiang MC et al. Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2009 - 12th International Conference, Proceedings. PART 1 ed. 2009. p. 967-974. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-04268-3_119

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

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