•A cortical shape-adaptive kernel is proposed to quantify cortical folding patterns.•The proposed method captures cortical folding in a biologically relevant way.•The proposed method achieves a high ...reproducibility in multi-scan dataset.•Novel associations with demographic effects are revealed in the early postnatal phase.
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The amount of cortical folding, or gyrification, is typically measured within local cortical regions covered by an equidistant geodesic or nearest neighborhood-ring kernel. However, without careful design, such a kernel can easily cover multiple sulcal and gyral regions that may not be functionally related. Furthermore, this can result in smoothing out details of cortical folding, which consequently blurs local gyrification measurements. In this paper, we propose a novel kernel shape to locally quantify cortical gyrification within sulcal and gyral regions. We adapt wavefront propagation to generate a spatially varying kernel shape that encodes cortical folding patterns: neighboring gyral crowns, sulcal fundi, and sulcal banks. For this purpose, we perform anisotropic wavefront propagation that runs fast along gyral crowns and sulcal fundi by solving a static Hamilton–Jacobi partial differential equation. The resulting kernel adaptively elongates along gyral crowns and sulcal fundi, while keeping a uniform shape over flat regions like sulcal banks. We then measure local gyrification within the proposed spatially varying kernel. The experimental results show that the proposed kernel-based gyrification measure achieves a higher reproducibility than the conventional method in a multi-scan dataset. We further apply the proposed kernel to a brain development study in the early postnatal phase from neonate to 2 years of age. In this study we find that our kernel yields both positive and negative associations of gyrification with age, whereas the conventional method only captures positive associations. In general, our method yields sharper and more detailed statistical maps that associate cortical folding with sex and gestational age.
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Tracing the early paths leading to developmental disorders is critical for prevention. In previous work, we detected an interaction between genomic risk scores for schizophrenia (GRSs) and early-life ...complications (ELCs), so that the liability of the disorder explained by genomic risk was higher in the presence of a history of ELCs, compared with its absence. This interaction was specifically driven by loci harboring genes highly expressed in placentae from normal and complicated pregnancies G. Ursini et al.,
24, 792-801 (2018). Here, we analyze whether fractionated genomic risk scores for schizophrenia and other developmental disorders and traits, based on placental gene-expression loci (PlacGRSs), are linked with early neurodevelopmental outcomes in individuals with a history of ELCs. We found that schizophrenia's PlacGRSs are negatively associated with neonatal brain volume in singletons and offspring of multiple pregnancies and, in singletons, with cognitive development at 1 y and, less strongly, at 2 y, when cognitive scores become more sensitive to other factors. These negative associations are stronger in males, found only with GRSs fractionated by placental gene expression, and not found in PlacGRSs for other developmental disorders and traits. The relationship of PlacGRSs with brain volume persists as an anlage of placenta biology in adults with schizophrenia, again selectively in males. Higher placental genomic risk for schizophrenia, in the presence of ELCs and particularly in males, alters early brain growth and function, defining a potentially reversible neurodevelopmental path of risk that may be unique to schizophrenia.
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Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic ...influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At present, there is little guidance available to help clinical research groups in choosing such tools. Thus, our goal was to compare the performance of two popular and fully automated tools, FSL/FIRST and FreeSurfer, to expert hand tracing in the measurement of the hippocampus and amygdala. Volumes derived from each automated measurement were compared to hand tracing for percent volume overlap, percent volume difference, across-sample correlation, and 3-D group-level shape analysis. In addition, sample size estimates for conducting between-group studies were computed for a range of effect sizes. Compared to hand tracing, hippocampal measurements with FreeSurfer exhibited greater volume overlap, smaller volume difference, and higher correlation than FIRST, and sample size estimates with FreeSurfer were closer to hand tracing. Amygdala measurement with FreeSurfer was also more highly correlated to hand tracing than FIRST, but exhibited a greater volume difference than FIRST. Both techniques had comparable volume overlap and similar sample size estimates. Compared to hand tracing, a 3-D shape analysis of the hippocampus showed FreeSurfer was more accurate than FIRST, particularly in the head and tail. However, FIRST more accurately represented the amygdala shape than FreeSurfer, which inflated its anterior and posterior surfaces.
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Objective: To examine patterns of early brain growth in young children with fragile X syndrome (FXS) compared with a comparison group (controls) and a group with idiopathic autism. Method: The study ...included 53 boys 18 to 42 months of age with FXS, 68 boys with idiopathic autism (autism spectrum disorder), and a comparison group of 50 typically developing and developmentally delayed controls. Structural brain volumes were examined using magnetic resonance imaging across two time points, at 2 to 3 and again at 4 to 5 years of age, and total brain volumes and regional (lobar) tissue volumes were examined. In addition, a selected group of subcortical structures implicated in the behavioral features of FXS (e.g., basal ganglia, hippocampus, amygdala) was studied. Results: Children with FXS had larger global brain volumes compared with controls but were not different than children with idiopathic autism, and the rate of brain growth from 2 to 5 years of age paralleled that seen in controls. In contrast to children with idiopathic autism who had generalized cortical lobe enlargement, children with FXS showed specific enlargement in the temporal lobe white matter, cerebellar gray matter, and caudate nucleus, but a significantly smaller amygdala. Conclusions: This structural longitudinal magnetic resonance imaging study of preschoolers with FXS observed generalized brain overgrowth in children with FXS compared with controls, evident at age 2 and maintained across ages 4 to 5. In addition, different patterns of brain growth that distinguished boys with FXS from boys with idiopathic autism were found. (Contains 3 figures and 7 tables.)
A proper geometric representation of the cortical regions is a fundamental task for cortical shape analysis and landmark extraction. However, a significant challenge has arisen due to the highly ...variable, convoluted cortical folding patterns. In this paper, we propose a novel topological graph representation for automatic sulcal curve extraction (TRACE). In practice, the reconstructed surface suffers from noise influences introduced during image acquisition/surface reconstruction. In the presence of noise on the surface, TRACE determines stable sulcal fundic regions by employing the line simplification method that prevents the sulcal folding pattern from being significantly smoothed out. The sulcal curves are then traced over the connected graph in the determined regions by the Dijkstra's shortest path algorithm. For validation, we used the state-of-the-art surface reconstruction pipelines on a reproducibility data set. The experimental results showed higher reproducibility and robustness to noise in TRACE than the existing method (Li et al. 2010) with over 20% relative improvement in error for both surface reconstruction pipelines. In addition, the extracted sulcal curves by TRACE were well-aligned with manually delineated primary sulcal curves. We also provided a choice of parameters to control quality of the extracted sulcal curves and showed the influences of the parameter selection on the resulting curves.
Specific differences in visual orienting, critical in social-cognitive development, are associated with differences in white matter microstructure of the splenium.
ObjectiveThe authors sought to ...determine whether specific patterns of oculomotor functioning and visual orienting characterize 7-month-old infants who later meet criteria for an autism spectrum disorder (ASD) and to identify the neural correlates of these behaviors.MethodData were collected from 97 infants, of whom 16 were high-familial-risk infants later classified as having an ASD, 40 were high-familial-risk infants who did not later meet ASD criteria (high-risk negative), and 41 were low-risk infants. All infants underwent an eye-tracking task at a mean age of 7 months and a clinical assessment at a mean age of 25 months. Diffusion-weighted imaging data were acquired for 84 of the infants at 7 months. Primary outcome measures included average saccadic reaction time in a visually guided saccade procedure and radial diffusivity (an index of white matter organization) in fiber tracts that included corticospinal pathways and the splenium and genu of the corpus callosum.ResultsVisual orienting latencies were longer in 7-month-old infants who expressed ASD symptoms at 25 months compared with both high-risk negative infants and low-risk infants. Visual orienting latencies were uniquely associated with the microstructural organization of the splenium of the corpus callosum in low-risk infants, but this association was not apparent in infants later classified as having an ASD.ConclusionsFlexibly and efficiently orienting to salient information in the environment is critical for subsequent cognitive and social-cognitive development. Atypical visual orienting may represent an early prodromal feature of an ASD, and abnormal functional specialization of posterior cortical circuits directly informs a novel model of ASD pathogenesis.
Abstract Background Autism Spectrum Disorder (ASD) is a developmental disorder defined by behavioural features that emerge during the first years of life. Research indicates that abnormalities in ...brain connectivity are associated with these behavioural features. However, inclusion of individuals past the age of onset of the defining behaviours complicates interpretation of the observed abnormalities: they may be cascade effects of earlier neuropathology and behavioural abnormalities. Our recent study of network efficiency in a cohort of 24-month-olds at high and low familial risk for ASD reduced this confound; we reported reduced network efficiencies in toddlers classified as ASD. The current study maps the emergence of these inefficiencies in the first year of life. Methods The study utilizes data from 260 infants at 6 and 12 months of age, including 116 infants with longitudinal data. As in our earlier study, we use diffusion data to obtain measures of the length and strength of connections between brain regions in order to compute network efficiency. We assess group differences in efficiency within linear mixed-effects models determined by the Akaike information criterion. Results Inefficiencies in high-risk infants later classified as ASD were detected from 6 months onward in regions involved in low-level sensory processing. Additionally, within the high-risk infants, these inefficiencies predicted 24-month symptom severity. Conclusion These results suggest that infants with ASD, even before 6 months of age, have deficits in connectivity related to low-level processing, which contribute to a developmental cascade affecting brain organization, and eventually higher-level cognitive processes and social behaviour.
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Three-dimensional (3D) imaging techniques can provide valuable information to clinicians and researchers. But as we move from traditional 2-dimensional (2D) cephalometric analysis to new 3D ...techniques, it is often necessary to compare 2D with 3D data. Cone-beam computed tomography (CBCT) provides simulation tools that can help bridge the gap between image types. CBCT acquisitions can be made to simulate panoramic, lateral, and posteroanterior cephalometric radioagraphs so that they can be compared with preexisting cephalometric databases. Applications of 3D imaging in orthodontics include initial diagnosis and superimpositions for assessing growth, treatment changes, and stability. Three-dimensional CBCT images show dental root inclination and torque, impacted and supernumerary tooth positions, thickness and morphology of bone at sites of mini-implants for anchorage, and osteotomy sites in surgical planning. Findings such as resorption, hyperplasic growth, displacement, shape anomalies of mandibular condyles, and morphological differences between the right and left sides emphasize the diagnostic value of computed tomography acquisitions. Furthermore, relationships of soft tissues and the airway can be assessed in 3 dimensions.
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The quantification of local surface morphology in the human cortex is important for examining population differences as well as developmental changes in neurodegenerative or neurodevelopmental ...disorders. We propose a novel cortical shape measure, referred to as the ‘shape complexity index’ (SCI), that represents localized shape complexity as the difference between the observed distributions of local surface topology, as quantified by the shape index (SI) measure, to its best fitting simple topological model within a given neighborhood. We apply a relatively small, adaptive geodesic kernel to calculate the SCI. Due to the small size of the kernel, the proposed SCI measure captures fine differences of cortical shape. With this novel cortical feature, we aim to capture comparatively small local surface changes that capture a) the widening versus deepening of sulcal and gyral regions, as well as b) the emergence and development of secondary and tertiary sulci. Current cortical shape measures, such as the gyrification index (GI) or intrinsic curvature measures, investigate the cortical surface at a different scale and are less well suited to capture these particular cortical surface changes. In our experiments, the proposed SCI demonstrates higher complexity in the gyral/sulcal wall regions, lower complexity in wider gyral ridges and lowest complexity in wider sulcal fundus regions. In early postnatal brain development, our experiments show that SCI reveals a pattern of increased cortical shape complexity with age, as well as sexual dimorphisms in the insula, middle cingulate, parieto-occipital sulcal and Broca's regions. Overall, sex differences were greatest at 6months of age and were reduced at 24months, with the difference pattern switching from higher complexity in males at 6months to higher complexity in females at 24months. This is the first study of longitudinal, cortical complexity maturation and sex differences, in the early postnatal period from 6 to 24months of age with fine scale, cortical shape measures. These results provide information that complement previous studies of gyrification index in early brain development.
•Shape complexity index was quantified by the distributions of local surface topology.•The adaptive geodesic kernel captures fine differences of the local shape index distribution.•The stability and reliability of shape complexity were showed using a scan/rescan dataset.•The influence of the kernel size is presented using the various kernel sizes.•The complexity changes show a regionally specific pattern over the age.
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