Quantifying regional growth patterns through longitudinal analysis of distances between multimodal MR intensity distributions

pre-printQuantitative analysis of early brain development through imaging is critical for identifying pathological development, which may in turn affect treatment procedures. We propose a framework for analyzing spatiotemporal patterns of brain maturation by quantifying intensity changes in longitudinal MR images. We use a measure of divergence between a pair of intensity distributions to study the changes that occur within specific regions, as well as between a pair of anatomical regions, over time. The change within a specific region is measured as the contrast between white matter and gray matter tissue belonging to that region. The change between a pair of regions is measured as the divergence between regional image appearances, summed over all tissue classes. We use kernel regression to integrate the temporal information across different subjects in a consistent manner. We applied our method on multimodal MRI data with T1-weighted (T1W) and T2-weighted (T2W) scans of each subject at the approximate ages of 6 months, 12 months, and 24 months. The results demonstrate that brain maturation begins at posterior regions and that frontal regions develop later, which matches previously published histological, qualitative and morphometric studies. Our multi-modal analysis also confirms that T1W and T2W modalities capture different properties of the maturation process, a phenomena referred to as T2 time lag compared to T1. The proposed method has potential for analyzing regional growth patterns across different populations and for isolating specific critical maturation phases in different MR modalities

Early changes in brain structure correlate with language outcomes in children with neonatal encephalopathy.

Global patterns of brain injury correlate with motor, cognitive, and language outcomes in survivors of neonatal encephalopathy (NE). However, it is still unclear whether local changes in brain structure predict specific deficits. We therefore examined whether differences in brain structure at 6 months of age are associated with neurodevelopmental outcomes in this population. We enrolled 32 children with NE, performed structural brain MR imaging at 6 months, and assessed neurodevelopmental outcomes at 30 months. All subjects underwent T1-weighted imaging at 3 T using a 3D IR-SPGR sequence. Images were normalized in intensity and nonlinearly registered to a template constructed specifically for this population, creating a deformation field map. We then used deformation based morphometry (DBM) to correlate variation in the local volume of gray and white matter with composite scores on the Bayley Scales of Infant and Toddler Development (Bayley-III) at 30 months. Our general linear model included gestational age, sex, birth weight, and treatment with hypothermia as covariates. Regional brain volume was significantly associated with language scores, particularly in perisylvian cortical regions including the left supramarginal gyrus, posterior superior and middle temporal gyri, and right insula, as well as inferior frontoparietal subcortical white matter. We did not find significant correlations between regional brain volume and motor or cognitive scale scores. We conclude that, in children with a history of NE, local changes in the volume of perisylvian gray and white matter at 6 months are correlated with language outcome at 30 months. Quantitative measures of brain volume on early MRI may help identify infants at risk for poor language outcomes

Biomechanical Analysis of Normal Brain Development during the First Year of Life Using Finite Strain Theory

The first year of life is the most critical time period for structural and functional development of the human brain. Combining longitudinal MR imaging and finite strain theory, this study aimed to provide new insights into normal brain development through a biomechanical framework. Thirty-three normal infants were longitudinally imaged using MRI from 2 weeks to 1 year of age. Voxel-wise Jacobian determinant was estimated to elucidate volumetric changes while Lagrange strains (both normal and shear strains) were measured to reveal directional growth information every 3 months during the first year of life. Directional normal strain maps revealed that, during the first 6 months, the growth pattern of gray matter is anisotropic and spatially inhomogeneous with higher left-right stretch around the temporal lobe and interhemispheric fissure, anterior-posterior stretch in the frontal and occipital lobes, and superior-inferior stretch in right inferior occipital and right inferior temporal gyri. In contrast, anterior lateral ventricles and insula showed an isotropic stretch pattern. Volumetric and directional growth rates were linearly decreased with age for most of the cortical regions. Our results revealed anisotropic and inhomogeneous brain growth patterns of the human brain during the first year of life using longitudinal MRI and a biomechanical framework

Non-Euclidean statistics for covariance matrices with applications to diffusion tensor imaging

The statistical analysis of covariance matrix data is considered and, in particular, methodology is discussed which takes into account the nonEuclidean nature of the space of positive semi-definite symmetric matrices. The main motivation for the work is the analysis of diffusion tensors in medical image analysis. The primary focus is on estimation of a mean covariance matrix and, in particular, on the use of Procrustes size-and-shape space. Comparisons are made with other estimation techniques, including using the matrix logarithm, matrix square root and Cholesky decomposition. Applications to diffusion tensor imaging are considered and, in particular, a new measure of fractional anisotropy called Procrustes Anisotropy is discussed

Efficient probabilistic and geometric anatomical mapping using particle mesh approximation on GPUs

pre-printDeformable image registration in the presence of considerable contrast differences and large size and shape changes presents significant research challenges. First, it requires a robust registration framework that does not depend on intensity measurements and can handle large nonlinear shape variations. Second, it involves the expensive computation of nonlinear deformations with high degrees of freedom. Often it takes a significant amount of computation time and thus becomes infeasible for practical purposes. In this paper, we present a solution based on two key ideas: a new registration method that generates a mapping between anatomies represented as a multicompartment model of class posterior images and geometries and an implementation of the algorithm using particle mesh approximation on Graphical Processing Units (GPUs) to fulfill the computational requirements. We show results on the registrations of neonatal to 2-year old infant MRIs. Quantitative validation demonstrates that our proposed method generates registrations that better maintain the consistency of anatomical structures over time and provides transformations that better preserve structures undergoing large deformations than transformations obtained by standard intensity-only registration. We also achieve the speedup of three orders of magnitudes compared to a CPU reference implementation, making it possible to use the technique in time-critical applications

Increased Vesicular Monoamine Transporter 2 (VMAT2) and Dopamine Transporter (DAT) Expression in Adolescent Brain Development: A Longitudinal Micro-PET/CT Study in Rodent

Background: Brain development and maturation in adolescence is a complex process with active changes of metabolic and neurotransmission pathways. Positron emission tomography (PET) is a useful imaging modality for tracking metabolic and functional changes in adolescent brain. In this study, changes of glucose metabolism, expression of vesicular monoamine transporter 2 and dopamine transporter during adolescent brain development in rats were investigated with PET/CT.Methods: A longitudinal PET/CT study of age-dependent changes of VMAT2, DAT and glucose metabolism in adolescent brain was conducted in a group of Wistar rats (n = 6) post sequential intravenous injection of 18F-PF-(+)-DTBZ, 11C-CFT, and 18F-FDG, respectively. PET acquisition was performed at 2, 4, 9, and 12 months of age. Radiotracer uptake in different brain regions, including the striatum, cerebellum, and hippocampus, were quantified and recorded as Standardized uptake value (SUV) and striatal specific uptake ratio (SUVR: SUV in brain regions/SUV in cerebellum).Results: Variable uptake of 18F-PF-(+)-DTBZ and 11C-CFT were detected, with highest level uptake in the striatum and accumbens. There was significant age-dependent increase of 18F-PF-(+)-DTBZ and 11C-CFT uptake in the striatum from 2 months of age (SUV: 1.36 ± 0.22, 1.37 ± 0.39, respectively), to 4 months (SUV: 2.22 ± 0.29, 2.04 ± 0.33), 9 months (1.98 ± 0.34, 2.09 ± 0.18), 12 months (SUV: 1.93 ± 0.19, 2.00 ± 0.17) of age, SUV of 18F-FDG also increased from 2 months of age to older ages (SUV in the striatum: 3.71 ± 0.78 at 2 month, 5.28 ± 0.81, 5.14 ± 0.73, 4.94 ± 0.50 at 4, 9, 12 month, respectively).Conclusion: Age-dependent increases of striatal of 18F-FDG, 18F-PF-(+)-DTBZ, and 11C-CFT uptake were detected in rats from 2 to 4 month of age, demonstrating striatal development presents over the first 4 months of age. Four months of age can be considered a safe threshold to launch brain disease studies for exclusion of confusion of continuing tissue development. These findings support further investigation of age-dependent changes in expression of DAT, VMAT2, and glucose metabolism for their potential use as a new imaging biomarker for study of brain development and functional maturation

Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs

Deformable image registration in the presence of considerable contrast differences and large size and shape changes presents significant research challenges. First, it requires a robust registration framework that does not depend on intensity measurements and can handle large nonlinear shape variations. Second, it involves the expensive computation of nonlinear deformations with high degrees of freedom. Often it takes a significant amount of computation time and thus becomes infeasible for practical purposes. In this paper, we present a solution based on two key ideas: a new registration method that generates a mapping between anatomies represented as a multicompartment model of class posterior images and geometries and an implementation of the algorithm using particle mesh approximation on Graphical Processing Units (GPUs) to fulfill the computational requirements. We show results on the registrations of neonatal to 2-year old infant MRIs. Quantitative validation demonstrates that our proposed method generates registrations that better maintain the consistency of anatomical structures over time and provides transformations that better preserve structures undergoing large deformations than transformations obtained by standard intensity-only registration. We also achieve the speedup of three orders of magnitudes compared to a CPU reference implementation, making it possible to use the technique in time-critical applications

Segmentation of Brain Magnetic Resonance Images (MRIs): A Review

Abstract MR imaging modality has assumed an important position in studying the characteristics of soft tissues. Generally, images acquired by using this modality are found to be affected by noise, partial volume effect (PVE) and intensity nonuniformity (INU). The presence of these factors degrades the quality of the image. As a result of which, it becomes hard to precisely distinguish between different neighboring regions constituting an image. To address this problem, various methods have been proposed. To study the nature of various proposed state-of-the-art medical image segmentation methods, a review was carried out. This paper presents a brief summary of this review and attempts to analyze the strength and weaknesses of the proposed methods. The review concludes that unfortunately, none of the proposed methods has been able to independently address the problem of precise segmentation in its entirety. The paper strongly favors the use of some module for restoring pixel intensity value along with a segmentation method to produce efficient results

Mid-space-independent deformable image registration

Aligning images in a mid-space is a common approach to ensuring that deformable image registration is symmetric – that it does not depend on the arbitrary ordering of the input images. The results are, however, generally dependent on the mathematical definition of the mid-space. In particular, the set of possible solutions is typically restricted by the constraints that are enforced on the transformations to prevent the mid-space from drifting too far from the native image spaces. The use of an implicit atlas has been proposed as an approach to mid-space image registration. In this work, we show that when the atlas is aligned to each image in the native image space, the data term of implicit-atlas-based deformable registration is inherently independent of the mid-space. In addition, we show that the regularization term can be reformulated independently of the mid-space as well. We derive a new symmetric cost function that only depends on the transformation morphing the images to each other, rather than to the atlas. This eliminates the need for anti-drift constraints, thereby expanding the space of allowable deformations. We provide an implementation scheme for the proposed framework, and validate it through diffeomorphic registration experiments on brain magnetic resonance images

Segmentation of brain MRI during early childhood

The objective of this thesis is the development of automatic methods to measure the changes in volume and growth of brain structures in prematurely born infants. Automatic tools for accurate tissue quantification from magnetic resonance images can provide means for understanding how the neurodevelopmental effects of the premature birth, such as cognitive, neurological or behavioural impairment, are related to underlying changes in brain anatomy. Understanding these changes forms a basis for development of suitable treatments to improve the outcomes of premature birth. In this thesis we focus on the segmentation of brain structures from magnetic resonance images during early childhood. Most of the current brain segmentation techniques have been focused on the segmentation of adult or neonatal brains. As a result of rapid development, the brain anatomy during early childhood differs from anatomy of both adult and neonatal brains and therefore requires adaptations of available techniques to produce good results. To address the issue of anatomical differences of the brain during early childhood compared to other age-groups, population-specific deformable and probabilistic atlases are introduced. A method for generation of population-specific prior information in form of a probabilistic atlas is proposed and used to enhance existing segmentation algorithms. The evaluation of registration-based and intensity-based approaches shows the techniques to be complementary in the quality of automatic segmentation in different parts of the brain. We propose a novel robust segmentation method combining the advantages of both approaches. The method is based on multiple label propagation using B-spline non-rigid registration followed by EM segmentation. Intensity inhomogeneity is a shading artefact resulting from the acquisition process, which significantly affects modern high resolution MR data acquired at higher magnetic field strengths. A novel template based method focused on correcting the intensity inhomogeneity in data acquired at higher magnetic field strengths is therefore proposed. The proposed segmentation method combined with proposed intensity inhomogeneity correction method offers a robust tool for quantification of volumes and growth of brain structures during early childhood. The tool have been applied to 67 T1-weigted images of subject at one and two years of age