Faculty Bibliography

Establishing optimal correspondence across object populations is essential to statistical shape analysis. Minimizing the description length (MDL) is a popular method for finding correspondence. In this work, we extend the MDL method by incorporating various local curvature metrics. Using local curvature can improve performance by ensuring that corresponding points exhibit similar local geometric characteristics that can't always be captured by mere point locations. We illustrate results on a variety of anatomical structures. The MDL method with a combination of point locations and curvature outperforms all the other methods we analyzed, including traditional MDL and spherical harmonics (SPHARM) correspondence, when the analyzed object population exhibits complex structure. When the objects are of simple nature, however, there's no added benefit to using the local curvature. In our experiments, we did not observe a significant difference in the correspondence quality when different curvature metrics (e.g. principal curvatures, mean curvature, Gaussian curvature) were used.

The topic of studying the growth of human brain development has become of increasing interest in the neuroimaging community. Cross-sectional studies may allow comparisons between means of different age groups, but they do not provide a growth model that integrates the continuum of time, nor do they present any information about how individuals/population change over time. Longitudinal data analysis method arises as a strong tool to address these questions. In this paper, we use longitudinal analysis methods to study tissue development in early brain growth. A novel approach of multivariate longitudinal analysis is applied to study the associations between the growth of different brain tissues. In this paper, we present the methodologies to statistically study scalar (univariate) and vector (multivariate) longitudinal data, and demonstrate exploratory results in a neuroimaging study of early brain tissue development. We obtained growth curves as a quadratic function of time for all three tissues. The quadratic terms were tested to be statistically significant, showing that there was indeed a quadratic growth of tissues in early brain development. Moreover, our result shows that there is a positive correlation between repeated measurements of any single tissue, and among those of different tissues. Our approach is generic in natural and thus can be applied to any longitudinal data with multiple outcomes, even brain structures. Also, our joint mixed model is flexible enough to allow incomplete and unbalanced data, i.e. subjects do not need to have the same number of measurements, or be measured at the exact time points.

BACKGROUND AND PURPOSE: The early postnatal period is perhaps the most dynamic phase of white matter development. We hypothesized that the early postnatal development of the corpus callosum and corticospinal tracts could be studied in unsedated healthy neonates by using novel approaches to diffusion tensor imaging (DTI) and quantitative tractography. MATERIALS AND METHODS: Isotropic 2 x 2 x 2 mm(3) DTI and structural images were acquired from 47 healthy neonates. DTI and structural images were coregistered and fractional anisotropy (FA), mean diffusivity (MD), and normalized T1-weighted (T1W) and T2-weighted (T2W) signal intensities were determined in central midline and peripheral cortical regions of the white matter tracts of the genu and splenium of the corpus callosum and the central midbrain and peripheral cortical regions of the corticospinal tracts by using quantitative tractography. RESULTS: We observed that central regions exhibited lower MD, higher FA values, higher T1W intensity, and lower T2W intensity than peripheral cortical regions. As expected, MD decreased, FA increased, and T2W signal intensity decreased with increasing age in the genu and corticospinal tract, whereas there was no significant change in T1W signal intensity. The central midline region of the splenium fiber tract has a unique pattern, with no change in MD, FA, or T2W signal intensity with age, suggesting different growth trajectory compared with the other tracts. FA seems to be more dependent on tract organization, whereas MD seems to be more sensitive to myelination. CONCLUSIONS: Our novel approach may detect small regional differences and age-related changes in the corpus callosum and corticospinal white matter tracts in unsedated healthy neonates and may be used for future studies of pediatric brain disorders that affect developing white matter.

Parkinson's disease (PD) typically manifests with asymmetric motor symptom onset. Ventricular enlargement, a nonspecific measure of brain atrophy, has been associated with cognitive decline in PD, but not with motor symptom asymmetry. Asymmetrical ventricular enlargement on magnetic resonance images was explored in a monozygotic twin pair discordant for PD and in nine healthy monozygotic twin pairs. The left-right lateral ventricular volumetric difference of the PD-twin was greater than that of his twin and all other healthy twins, with the larger ventricle observed contralateral to the more symptomatic side. Moreover, the lateral ventricle asymmetry difference between twin pairs was significantly higher for the discordant PD-twin pair than for the healthy twin pairs. This is the first report to suggest the presence of asymmetrical ventricular enlargement in PD, findings that may be worthy of further study.

We present a novel method of statistical surface-based morphometry based on the use of non-parametric permutation tests and a spherical wavelet (SWC) shape representation. As an application, we analyze two brain structures, the caudate nucleus and the hippocampus, and compare the results obtained to shape analysis using a sampled point representation. Our results show that the SWC representation indicates new areas of significance preserved under the FDR correction for both the left caudate nucleus and left hippocampus. Additionally, the spherical wavelet representation provides a natural way to interpret the significance results in terms of scale in addition to knowing the spatial location of the regions.

Although there has been recent interest in the study of childhood and adolescent brain development, very little is known about normal brain development in the first few months of life. In older children, there are regional differences in cortical gray matter development, whereas cortical gray and white matter growth after birth has not been studied to a great extent. The adult human brain is also characterized by cerebral asymmetries and sexual dimorphisms, although very little is known about how these asymmetries and dimorphisms develop. We used magnetic resonance imaging and an automatic segmentation methodology to study brain structure in 74 neonates in the first few weeks after birth. We found robust cortical gray matter growth compared with white matter growth, with occipital regions growing much faster than prefrontal regions. Sexual dimorphism is present at birth, with males having larger total brain cortical gray and white matter volumes than females. In contrast to adults and older children, the left hemisphere is larger than the right hemisphere, and the normal pattern of fronto-occipital asymmetry described in older children and adults is not present. Regional differences in cortical gray matter growth are likely related to differential maturation of sensory and motor systems compared with prefrontal executive function after birth. These findings also indicate that whereas some adult patterns of sexual dimorphism and cerebral asymmetries are present at birth, others develop after birth.

OBJECTIVE: To provide an overview of diffusion tensor imaging (DTI) and its application to the study of white matter in the developing brain in both healthy and clinical samples. METHOD: The development of DTI and its application to brain imaging of white matter tracts is discussed. Forty-eight studies using DTI to examine diffusion properties of the developing brain are reviewed in the context of the structural magnetic resonance imaging literature. Reports of how brain diffusion properties are affected in pediatric clinical samples and how they relate to cognitive and behavioral phenotypes are reviewed. RESULTS: DTI has been used successfully to describe white matter development in pediatric samples. Changes in white matter diffusion properties are consistent across studies, with anisotropy increasing and overall diffusion decreasing with age. Diffusion measures in relevant white matter regions correlate with behavioral measures in healthy children and in clinical pediatric samples. CONCLUSIONS: DTI is an important tool for providing a more detailed picture of developing white matter than can be obtained with conventional magnetic resonance imaging alone.