A Unified Statistical Approach to Deformation-Based Morphometry

Chung, Moo K.; Worsley, Keith J.; Paus, Tomáš; Cherif, C.; Collins, D. Louis; Giedd, Jay N.; Rapoport, Judith L.; Evans, Alan C.

doi:10.1006/nimg.2001.0862

Cited by 385 publications

(318 citation statements)

References 31 publications

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“…Jacobian determinant values derived from these tensor fields indicate the fractional volume expansion and contraction at each voxel (e.g., Chung et al, 2001;Davatzikos et al, 1996). In other words, the resulting Jacobian map quantifies the magnitude of regional volume alterations required to match the template.…”

Section: Image Analysismentioning

confidence: 99%

“…Compared to prior VBM studies, the following methodological improvements have been made in the current study. First, tensor-based morphometry (TBM; Ashburner et al, 1998;Chung et al, 2001;Davatzikos, Genc, Xu, & Resnick, 2001;Gaser, Volz, Kiebel, Riehemann, & Sauer, 1999;Studholme et al, 2004;Thompson et al, 2000) was used. TBM methods utilize information from high resolution deformation tensor fields obtained from the non-linear transformations of individual images to the template.…”

Section: Introductionmentioning

confidence: 99%

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Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study

et al. 2008

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Traumatic brain injury (TBI) is one of the most common causes of long-term disability. Despite the importance of identifying neuropathology in individuals with chronic TBI, methodological challenges posed at the stage of inter-subject image registration have hampered previous voxel-based MRI studies from providing a clear pattern of structural atrophy after TBI. We used a novel symmetric diffeomorphic image normalization method to conduct a tensor-based morphometry (TBM) study of TBI. The key advantage of this method is that it simultaneously estimates an optimal template brain and topology preserving deformations between this template and individual subject brains. Detailed patterns of atrophies are then revealed by statistically contrasting control and subject deformations to the template space. Participants were 29 survivors of TBI and 20 control subjects who were matched in terms of age, gender, education, and ethnicity. Localized volume losses were found most prominently in white matter regions and the subcortical nuclei including the thalamus, the midbrain, the corpus callosum, the mid-and posterior cingulate cortices, and the caudate. Significant voxel-wise volume loss clusters were also detected in the cerebellum and the frontal/ temporal neocortices. Volume enlargements were identified largely in ventricular regions. A similar pattern of results was observed in a subgroup analysis where we restricted our analysis to the 17 TBI participants who had no macroscopic focal lesions (total lesion volume> 1.5 cm 3 ). The current study confirms, extends, and partly challenges previous structural MRI studies in chronic TBI. By demonstrating that a large deformation image registration technique can be successfully combined with TBM to identify TBI-induced diffuse structural changes with greater precision, our approach is expected to increase the sensitivity of future studies examining brain-behavior relationships in the TBI population.

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Section: Image Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study

et al. 2008

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“…On the other hand, deformation-based morphometry and tensor-based morphometry in the normal developmental studies in children show that there is relative brain tissue growth in the corpus callosum over time (Chung et al, 2001;Thompson et al, 2000). In particular, Chung et al (2001) showed white matter local volume increase in the midbody, isthmus, and splenium of the corpus callosum in 28 normal subjects from 12 to 16 years. In our study, the age for the control group is 17.1 F 2.8, and for the autism group, it is 16.1 F 4.5 years ( Table 1).…”

Section: General Linear Modelsmentioning

confidence: 99%

Less white matter concentration in autism: 2D voxel-based morphometry

Chung¹,

Dalton²,

Alexander³

et al. 2004

NeuroImage

143

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Autism is a neurodevelopmental disorder affecting behavioral and social cognition, but there is little understanding about the link between the functional deficit and its underlying neuroanatomy. We applied a 2D version of voxel-based morphometry (VBM) in differentiating the white matter concentration of the corpus callosum for the group of 16 high functioning autistic and 12 normal subjects. Using the white matter density as an index for neural connectivity, autism is shown to exhibit less white matter concentration in the region of the genu, rostrum, and splenium removing the effect of age based on the general linear model (GLM) framework. Further, it is shown that the less white matter concentration in the corpus callosum in autism is due to hypoplasia rather than atrophy. D

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“…While this overall goal may be impractical to accomplish at the moment, various prospective longitudinal efforts are underway. Within the methodological analysis of specific research groups, an initial glimpse of the form of the normal developmental trajectory for some anatomic structures can begin to be formed [Chung et al, 2001;Giedd et al, 1996;Giedd et al, 1999;Paus et al, 1999;Thompson et al, 2000]. Such valuable studies of their own right can easily be anticipated to be highly magnified in their significance when performed as a comprehensive, multi-site, longitudinal study utilizing a homogeneous analysis method.…”

Section: Discussionmentioning

confidence: 99%

MRI‐based morphometric analysis of typical and atypical brain development

Kennedy

Haselgrove

McInerney

2003

Ment. Retard. Dev. Disabil. Res. Rev.

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The neuroinformatics landscape in which human brain morphometry occurs has advanced dramatically over the past few years. Rapid advancement in image acquisition methods, image analysis tools and interpretation of morphometric results make the study of in vivo anatomic analysis both challenging and rewarding. This has revolutionized our expectations for current and future diagnostic and investigative work with the developing brain. This paper will briefly cover the methods of morphometric analysis that available for neuroanatomic analysis, and tour some sample results from a prototype retrospective database of neuroanatomic volumetric information. From these observations, issues regarding the anatomic variability of developmental maturation of neuroanatomic structures in both typically and atypically developing populations can be discussed.

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A Unified Statistical Approach to Deformation-Based Morphometry

Cited by 385 publications

References 31 publications

Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study

Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study

Less white matter concentration in autism: 2D voxel-based morphometry

MRI‐based morphometric analysis of typical and atypical brain development

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