Conference Paper

Multivariate tensor-based morphometry on surfaces: Application to mapping ventricular changes in HIV/AIDS

Sch. of Med., Lab. of Neuro Imaging, UCLA Sch. of Med., Los Angeles, CA, USA
DOI: 10.1109/ISBI.2009.5193000 Conference: Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Source: IEEE Xplore

ABSTRACT We apply multivariate tensor-based morphometry to study lateral ventricular surface abnormalities associated with HIV/AIDS. We use holomorphic one-forms to obtain a conformal parameterization of ventricular geometry, and to register lateral ventricular surfaces across subjects. In a new development, we computed new statistics on the Riemannian surface metric tensors that encode the full information in the deformation tensor fields. We applied this framework to 3D brain MRI data, to map the profile of lateral ventricular surface abnormalities in HIV/AIDS (11 subjects). Experimental results demonstrated that our method powerfully detected brain surface abnormalities. Multivariate Hotelling's T2 statistics on the local Riemannian metric tensors, computed in a log-Euclidean framework, detected group differences with greater power than other surface-based statistics including the Jacobian determinant, largest and least eigenvalue, or the pair of eigenvalues of the Jacobian matrix. Computational anatomy studies may therefore benefit from surface parameterization using differential forms and tensor-based morphometry, in the log-Euclidean domain, on the resulting surface tensors.

0 Followers
 · 
92 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Statistical shape analysis is a tool that allows to quantify the shape variability of a population of shapes. Traditional tools to perform statistical shape analysis compute variations that reflect both shape and posture changes simultaneously. In many applications, such as ergonomic design applications, we are only interested in shape variations. With traditional tools, it is not straightforward to separate shape and posture variations. To overcome this problem, we propose an approach to perform statistical shape analysis in a posture-invariant way. The approach is based on a local representation that is obtained using the Laplace operator.
    Computers & Graphics 08/2012; 36(5):410–416. DOI:10.1016/j.cag.2012.03.026 · 1.03 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD.
    NeuroImage 10/2014; 104. DOI:10.1016/j.neuroimage.2014.09.062 · 6.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Many children born preterm exhibit frontal executive dysfunction, behavioral problems including attentional deficit/hyperactivity disorder and attention related learning disabilities. Anomalies in regional specificity of cortico-striato-thalamo-cortical circuits may underlie deficits in these disorders. Nonspecific volumetric deficits of striatal structures have been documented in these subjects, but little is known about surface deformation in these structures. For the first time, here we found regional surface morphological differences in the preterm neonatal ventral striatum. We performed regional group comparisons of the surface anatomy of the striatum (putamen and globus pallidus) between 17 preterm and 19 term-born neonates at term-equivalent age. We reconstructed striatal surfaces from manually segmented brain magnetic resonance images and analyzed them using our in-house conformal mapping program. All surfaces were registered to a template with a new surface fluid registration method. Vertex-based statistical comparisons between the two groups were performed via four methods: univariate and multivariate tensor-based morphometry, the commonly used medial axis distance, and a combination of the last two statistics. We found statistically significant differences in regional morphology between the two groups that are consistent across statistics, but more extensive for multivariate measures. Differences were localized to the ventral aspect of the striatum. In particular, we found abnormalities in the preterm anterior/inferior putamen, which is interconnected with the medial orbital/prefrontal cortex and the midline thalamic nuclei including the medial dorsal nucleus and pulvinar. These findings support the hypothesis that the ventral striatum is vulnerable, within the cortico-stiato-thalamo-cortical neural circuitry, which may underlie the risk for long-term development of frontal executive dysfunction, attention deficit hyperactivity disorder and attention-related learning disabilities in preterm neonates.
    PLoS ONE 07/2013; 8(7):e66736. DOI:10.1371/journal.pone.0066736 · 3.53 Impact Factor

Full-text (2 Sources)

Download
70 Downloads
Available from
May 29, 2014

Jie Zhang