Faculty Bibliography

This paper describes an automatic tissue segmentation method for newborn brains from magnetic resonance images (MRI). The analysis and study of newborn brain MRI is of great interest due to its potential for studying early growth patterns and morphological changes in neurodevelopmental disorders. Automatic segmentation of newborn MRI is a challenging task mainly due to the low intensity contrast and the growth process of the white matter tissue. Newborn white matter tissue undergoes a rapid myelination process, where the nerves are covered in myelin sheathes. It is necessary to identify the white matter tissue as myelinated or non-myelinated regions. The degree of myelination is a fractional voxel property that represents regional changes of white matter as a function of age. Our method makes use of a registered probabilistic brain atlas. The method first uses robust graph clustering and parameter estimation to find the initial intensity distributions. The distribution estimates are then used together with the spatial priors to perform bias correction. Finally, the method refines the segmentation using training sample pruning and non-parametric kernel density estimation. Our results demonstrate that the method is able to segment the brain tissue and identify myelinated and non-myelinated white matter regions.

INTRODUCTION: The mandibular rami and their endochondrally growing condyles develop in many directions relative to the variable anatomic patterns of the nasomaxilla and middle cranial fossae during growth and response to orthopedic treatment. METHODS: High-resolution magnetic resonance images were used to compare 3-dimensional (3D) growth vectors of skeletal displacement and bone remodeling in 25 untreated subjects with Class II malocclusions, 28 subjects with Class II malocclusions who were treated with Frankel appliance therapy, and 25 subjects with normal occlusions. Marked differences were noted over an 18-month observation period. The 3D coordinates of anatomic landmarks were registered by Procrustes fit to control for rotation, translation, and scale differences. RESULTS: Compared with untreated Class II and normal-occlusion subjects, the treated group showed highly significant differences in the 3D displacement/remodeling vectors of gonion and pterygomaxillary fissure relative to condylion and middle cranial fossae bilateral skeletal landmarks, by using both permutation tests ( P < .001) and a general linear multivariate model ( P < .0001). CONCLUSIONS: In a prospective and systematically controlled study, we quantitatively described significant 3D rami skeletal compensations in the structural assembly of facial morphogenesis at the beginning of the adolescent growth spurt using novel modeling techniques. These techniques have facilitated quantification of relative 3D growth vectors to illustrate skeletal changes with Frankel appliance therapy. Future studies are required to assess the long-term clinical significance of our findings.

INTRODUCTION: Three-dimensional (3D) craniofacial images are commonly used in clinical studies in orthodontics to study developmental and morphologic relationships. METHODS: We used 3D magnetic resonance imaging to study relationships among craniofacial components during the pubertal growth spurt and in response to Frankel appliance therapy. The sample for this prospective study was 156 high-resolution magnetic resonance images with 1 mm isotropic voxel resolution of 78 subjects taken initially (T1) and 18 +/- 1 months (T2) after treatment or an observation period. The subjects were Brazilian children; 28 were treated and 25 were untreated for Class II malocclusion, and 25 were untreated with normal occlusions. A Procrustes geometric transformation of 3D skeletal landmarks was used to assess growth or treatment alterations from T1 to T2. The landmarks were located on the mandibular rami and the other craniofacial parts specifically related to the mandibular growth (the middle cranial fossae and the posterior part of the bilateral nasomaxilla). This allowed visualization of the entire volumetric dataset with an interactive 3D display. RESULTS: Statistically significant differences were found in the relative 3D skeletal growth directions from T1 to T2 for treated vs untreated Class II children (Bonferroni-adjusted P < .001) and for treated Class II vs normal-occlusion subjects ( P < .001). The major differences in the treated group were increased mandibular rami vertical dimensions and more forward rami relative to the posterior nasomaxilla and the middle cranial fossae. Principal component analysis made it possible to show individual variability and group differences in the principal dimensions of skeletal change. CONCLUSIONS: These methods are generalizable to other imaging techniques and 3D samples, and significantly enhance the potential of systematically controlled data collection and analysis of bony structures in 3 dimensions for quantitative assessment of patient parameters in craniofacial biology.

The structural variability of lateral ventricles is poorly understood notwithstanding that enlarged size has been identified as an unspecific marker for psychiatric illness, including schizophrenia. This paper explores the effects of heritability and genetic risk for schizophrenia reflected in ventricular size and structure. We examined ventricular size and shape in the MRI studies of monozygotic (MZ) twin pairs discordant for schizophrenia (DS), healthy MZ twin pairs, healthy dizygotic twin pairs, and healthy nonrelated subject pairs. Heritability and effect due to disease were analyzed in two tests. First, heritability was examined by ventricle similarity between pairs of co-twins. Results show that co-twin ventricle shape similarity decreases with decreasing genetic identity, an effect not seen in the volume analysis. Co-twin shape similarity of healthy MZ twins did not differ from DS MZ twins. Second, the disease effect was examined through the ventricular differences of DS subjects to a template shape representing healthy subjects. Affected DS twins showed shape differences from healthy subjects on the left and right sides. Interestingly, unaffected DS twins also showed significant shape differences from healthy subjects for both sides. Volume comparisons did not show differences between these groups. Locality of shape difference suggests that the ventricular shape of the anterior and posterior regions is under genetic influence in both healthy controls and schizophrenia patients. Affected and unaffected groups demonstrate main shape differences, compared with healthy controls, only in the posterior region. Our results suggest that genetics have a stronger influence on the shape of lateral ventricles than do the disease-related changes in schizophrenia.

BACKGROUND: Reduced hippocampal volume is a consistently described structural abnormality in schizophrenia but its cause and timing are not known. AIMS: To examine the relationship of duration of schizophrenic illness and treatment effects with hippocampal volumes. METHOD: Quantitative 1.5 T magnetic resonance imaging brain scans of young male patients in the early stage of schizophrenic illness were compared with those of chronically ill older patients. Scans were also acquired for controls matched to both patient groups for age and handedness. Duration of illness was recorded and severity of symptoms assessed with the Positive and Negative Syndrome Scale. RESULTS: The patients with schizophrenia had smaller hippocampal volumes than the controls. The volume reduction was larger in older patients than in young, compared with age-matched controls. In the early illness group atypical antipsychotics rather than haloperidol were associated with larger hippocampal volumes even after controlling for differences in illness severity. CONCLUSIONS: The greater reduction of hippocampal volume in people with chronic v. early illness, after controlling for illness severity and age, supports the hypothesis of progressive hippocampal reduction in males with schizophrenia. Atypical antipsychotics early in illness may protect against this.

We present a method for two-sample hypothesis testing for statistical shape analysis using nonlinear shape models. Our approach uses a true multivariate permutation test that is invariant to the scale of different model parameters and that explicitly accounts for the dependencies between variables. We apply our method to m-rep models of the lateral ventricles to examine the amount of shape variability in twins with different degrees of genetic similarity.

A publicly available database of high-quality, multi-modal MR brain images of carefully screened healthy subjects, equally divided by sex, and with an equal number of subjects per age decade, would be of high value to investigators interested in the statistical study of disease. This report describes initial use of an accumulating healthy database currently comprising 50 subjects aged 20-72. We examine changes by age and sex to the volumes of gray matter, white matter and cerebrospinal fluid for subjects within the database. We conclude that traditional views of healthy aging should be revised. Significant atrophy does not appear in healthy subjects 60 or 70 years old. Gray matter loss is not restricted to senility, but begins in early adulthood and is progressive. The percentage of white matter increases with age. A carefully-designed healthy database should be useful in the statistical analysis of many age- and non-age-related diseases.

Diffusion tensor imaging (DTI) has become the major modality to study properties of white matter and the geometry of fiber tracts of the human brain. Clinical studies mostly focus on regional statistics of fractional anisotropy (FA) and mean diffusivity (MD) derived from tensors. Existing analysis techniques do not sufficiently take into account that the measurements are tensors, and thus require proper interpolation and statistics based on tensors, and that regions of interest are fiber tracts with complex spatial geometry. We propose a new framework for quantitative tract-oriented DTI analysis that includes tensor interpolation and averaging, using nonlinear Riemannian symmetric space. As a result, tracts of interest are represented by the geometry of the medial spine attributed with tensor statistics calculated within cross-sections. Examples from a clinical neuroimaging study of the early developing brain illustrate the potential of this new method to assess white matter fiber maturation and integrity.