Detecting corpus callosum abnormalities in autism based on anatomical landmarks

Statistical shape analysis of corpus callosum in delusional disorder

Neurobiological foundations of delusional disorder (DD) have been studied less with neuroimaging techniques when compared to other psychotic disorders. The present study aimed to delineate the neural substrates of DD by investigating neuroanatomical characteristics of the corpus callosum (CC) with statistical shape analysis (SSA) conducted on magnetic resonance images (MRI). Twenty (female:male=1:1) DSM-5 DD patients and 20 age- and gender-matched healthy individuals were included. High-resolution 3D T1 Turbo Field Echo MRI images were scanned with a 1.5 T MR device. The landmarks that were selected to determine the shape differences in CC were identified based on previous studies. Furthermore, constructed landmarks were determined and employed to better assess regional shape differences. There was no significant difference in the CC area in the mid-sagittal images between the DD patients and controls. However, DD patients exhibited a pattern of structural CC changes in various regions. The study findings emphasizes the variable subregional nature of CC in DD patients. Future SSA studies with larger samples could shed further light on DD etiology, diagnosis, classification and treatment options.

Are Essential Trace Elements Effective in Modulation of Mental Disorders? Update and Perspectives

The emergence of mental disorders is associated with several risk factors including genetic and environmental susceptibility. A group of nutrients serves an especially important role in a number of essential neurodevelopmental processes through brain areas promoting the high degree of brain metabolism during early life, although almost all nutrients are needed. These include macronutrients and micronutrients (e.g., iron, magnesium, zinc, copper, selenium). Numerous nutritional psychiatry trials have been performed to examine the correlation of many individual nutrients with mental health, such as essential trace elements. The increased accumulation or lack of such components will facilitate an alternative metabolic pathway that can lead to many diseases and conditions of neurodevelopment. Mental functions have biochemical bases, so the impairment of such neurochemical mechanisms due to lack of trace elements can have mental effects. In psychological conditions such as depression, anxiety, schizophrenia, and autism, scientific studies demonstrate the putative role of trace element deficiency. Therefore, given the critical roles played by essential trace elements in the neurodevelopment and mental health, the effect of these elements' intake on the modulation of psychological functioning is reviewed.

Statistical shape analysis of putamen in early-onset Parkinson's disease

OBJECTIVE

To investigate the shape differences in the putamen of early-onset Parkinson's patients compared with healthy controls and to assess and to assess sub-regional brain abnormalities.

METHODS

This study was conducted using the 3-T MRI scans of 23 early-onset Parkinson's patients and age and gender matched control subjects. Landmark coordinate data obtained and Procrustes analysis was used to compare mean shapes. The relationships between the centroid sizes of the left and right putamen, and the durations of disease examined using growth curve models.

RESULTS

While there was a significant difference between the right putamen shape of control and patient groups, there was not found a significant difference in terms of left putamen. Sub-regional analyses showed that for the right putamen, the most prominent deformations were localized in the middle-posterior putamen and minimal deformations were seen in the anterior putamen.

CONCLUSION

Although they were not as pronounced as those in the right putamen, the deformations in the left putamen mimic the deformations in the right putamen which are found mainly in the middle-posterior putamen and at a lesser extend in the anterior putamen.

Statistical shape analysis of gravid uteri throughout pregnancy by a ray description technique

In order to study the anatomical variability of the uterus induced by pregnancy, a parametrization of gravid uterine geometry based on principal component analysis (PCA) is proposed. Corresponding meshes used for PCA are created by a ray description technique applied to a reference mesh. A smoothed voxel-based methodology is applied to determine the reference mesh from a database of 11 real shapes produced by the FEMONUM project. The ray-based correspondence technique is compared to two existing methods (He, Giessen) as well as a proposed mixed method. Principal component analysis results are based on a database of 11 existing shapes. Results of the parametrization show that 90% of the total variance of the database can be represented with four new shape parameters and that a wide spectrum of shapes can be generated. Graphical Abstract Proposed correspondence technique compared to existing methods.

Sexual dimorphism of the mandibular conformational changes in aging human adults: A multislice computed tomographic study by geometric morphometrics

The aging process has an impact on mandibular bone morphology and can therefore affect shape sexual dimorphism. Understanding the effect of senescence on mandibular shape changes is particularly important to correctly estimate the sex of an individual and predict age-related conformational modifications. The purpose of this study was to assess age-related changes in mandibular shape and sexual dimorphism. The study sample comprised 160 Multi Slice Computed Tomography examinations of individuals aged 40 to 79 years. Geometric morphometric analysis of fourteen osteometric landmarks was used to examine sexual dimorphism and patterns of mandibular shape variation with age. Results showed that mandibular sexual dimorphism of shape remained significant with aging. Conformational changes occurred between 50 and 70 years and were different for male and female individuals. Females presented earlier and more marked age-related shape changes than males. These observations suggest that mandibular senescence is a sexually dimorphic process since its onset, rate, and the areas subjected to conformational changes differ from male to female individuals. Senescence-related changes present substantial variability, and further investigation is required to determine precisely the age that marks their onset.

Characteristics of 43 multiple auricular deformity case families and auricle morphology in 463 microtia patients in South China

Background

Earlier studies have suggested that microtia is a genetic disease with a worldwide incidence of microtia is between 0.83/10,000 and 17.40/10,000. For microtia, auricle morphology is the most crucial characteristic. However, no studies have been performed to characterize the genetic similarity of microtia and auricle morphology similarity. For the sporadic patients, the relationship between the gestational age of parents and the incidence of microtia is unclear. To obtain the characteristics of auricular deformity multiple case family (AD-MCF) and clarify the relationship between genetic similarity and auricle morphology similarity in AD-MCF.

Methods

This study included 463 AD patients who were diagnosed by Sun Yat-sen Memorial Hospital, Sun Yat-sen University, from 2013 to 2019. Among these patients, 116 are from 43 MCF and the other 347 patients are sporadic. For the patients from families, the disease status of the four generations of immediate family members and the family tree map were collected to analyze the similarity of auricle shape in family members. A score evaluated the similarity of auricle shape according to the structure of the residual ear and the similarity in the morphology of each auricle. Moreover, the population distribution of AD and the gestational age of patients were further analyzed.

Results

From 2013 to 2019, a total of 463 patients were diagnosed as microtia in our hospital. There were 427 patients with unilateral disease and 36 patients with bilateral disease. Among them, 116 patients were from 34 families and 9 de novo families. The total scores of patients in different genetic difference levels were compared and were found significantly different (P<0.001). Moreover, 58.14% of families were consistent with the law of chromosomal recessive genetic diseases. Importantly, we found that the gestational age of father in microtia de novo families is 30.94±0.75, and mother in de novo is 28.39±0.73 that is significantly higher than the gestational ages of parents from microtia families with P value =0.0001.

Conclusions

The auricle similarity between family members is positively related to the genetic distance between family members. The microtia patients are potentially associated with the gestational ages of parents.

Sex estimation in the cranium and mandible: a multislice computed tomography (MSCT) study using anthropometric and geometric morphometry methods

INTRODUCTION

The purpose of this study was to analyze the respective contribution of the skull and mandible to sex estimation in an entire cranium using metric and geometric morphometric methods and multislice computed tomography (MSCT) analysis.

MATERIALS

The study sample comprised 120 individuals aged 23 to 84 years and divided into three groups (whole sample and over or under 40 years of age).

METHODS

Forty-eight osteometric landmarks were positioned using Osirix®, 34 for the cranium and 14 for the mandible. The data were analyzed using univariate analyses and logistic regression using backward stepwise selection with cross-validation of the classification results. Generalized procrustes analysis (GPA) was used, and Goodall's F test and Mahalanobis D² matrices allowed an assessment of statistical significance.

RESULTS

The classification accuracy of cranium models ranged from 87% to 88.3%, and from 68% to 81.4% for the mandibular models. With geometric morphometry, accuracy was of 94-100% for the cranium and 84.2% for the mandible.

DISCUSSION

We conclude that the mandible had a higher accuracy rate for individuals over 40 years than individuals under 40 years of age, although the accuracy of geometric morphometry did not differ significantly between the age groups. The cranium, however, presented greater predictability for all the parameters assessed.

Diffusional kurtosis imaging of the corpus callosum in autism

Background

The corpus callosum is implicated in the pathophysiology of autism spectrum disorder (ASD). However, specific structural deficits and underlying mechanisms are yet to be well defined.

Methods

We employed diffusional kurtosis imaging (DKI) metrics to characterize white matter properties within five discrete segments of the corpus callosum in 17 typically developing (TD) adults and 16 age-matched participants with ASD without co-occurring intellectual disability (ID). The DKI metrics included axonal water fraction (f_axon) and intra-axonal diffusivity (D_axon), which reflect axonal density and caliber, and extra-axonal radial (RD_extra) and axial (AD_extra) diffusivities, which reflect myelination and microstructural organization of the extracellular space. The relationships between DKI metrics and processing speed, a cognitive feature known to be impaired in ASD, were also examined.

Results

ASD group had significantly decreased callosal f_axon and D_axon (p = .01 and p = .045), particularly in the midbody, isthmus, and splenium. Regression analysis showed that variation in DKI metrics, primarily in the mid and posterior callosal regions explained up to 70.7% of the variance in processing speed scores for TD (p = .001) but not for ASD (p > .05).

Conclusion

Decreased DKI metrics suggested that ASD may be associated with axonal deficits such as reduced axonal caliber and density in the corpus callosum, especially in the mid and posterior callosal areas. These data suggest that impaired interhemispheric connectivity may contribute to decreased processing speed in ASD participants.

Electronic supplementary material

The online version of this article (10.1186/s13229-018-0245-1) contains supplementary material, which is available to authorized users.

Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis

Brain disorders, such as Autism Spectrum Disorder (ASD), alter brain functional (from fMRI) and structural (from diffusion MRI) connectivities at multiple levels and in varying degrees. While unraveling such alterations have been the focus of a large number of studies, morphological brain connectivity has been out of the research scope. In particular, shape-to-shape relationships across brain regions of interest (ROIs) were rarely investigated. As such, the use of networks based on morphological brain data in neurological disorder diagnosis, while leveraging the advent of machine learning, could complement our knowledge on brain wiring alterations in unprecedented ways. In this paper, we use conventional T1-weighted MRI to define morphological brain networks (MBNs), each quantifying shape relationship between different cortical regions for a specific cortical attribute at both low-order and high-order levels. While typical brain connectomes investigate the relationship between two ROIs, we propose high-order MBN which better captures brain complex interactions by modeling the morphological relationship between pairs of ROIs. For ASD identification, we present a connectomic manifold learning framework, which learns multiple kernels to estimate a similarity measure between ASD and normal controls (NC) connectional features, to perform dimensionality reduction for clustering ASD and NC subjects. We benchmark our ASD identification method against both supervised and unsupervised state-of-the-art methods, while depicting the most discriminative high- and low-order relationships between morphological regions in the left and right hemispheres.

A statistical geometrical description of the human liver for probabilistic occupant models

Realistic numerical assessments of liver injury risk for the entire occupant population require incorporating inter-subject variations into numerical models. Statistical shape models of the abdominal organs have been shown to be useful tools for the investigation of the organ variations and could be applied to the development of statistical computational models. The main objective of this study was to establish a standard procedure to quantify the shape variations of a human liver in a seated posture, and construct three-dimensional (3D) statistical shape boundary models. Statistical shape analysis was applied to construct shape models of 15 adult human livers. Principal component analysis (PCA) was then utilized to obtain the modes of variation, the mean model, and a set of statistical boundary shape models, which were constructed using the q-hyper-ellipsoid approach. The first five modes of a human liver accounted for the major anatomical variations. The modes were highly correlated to the height, thickness, width, and curvature of the liver, and the concavity of the right lobe. The mean model and the principal components were utilized to construct four boundary models of human liver. The statistical boundary model approach presented in this study could be used to develop probabilistic finite element (FE) models. In the future, the probabilistic liver models could be used in FE simulations to better understand the variability in biomechanical responses and abdominal injuries under impact loading.

Statistical modeling of human liver incorporating the variations in shape, size, and material properties

The liver is one of the most frequently injured abdominal organs during motor vehicle crashes. Realistic numerical assessments of liver injury risk for the entire occupant population require incorporating inter-subject variations into numerical models. The main objective of this study was to quantify the shape variations of human liver in a seated posture and the statistical distributions of its material properties. Statistical shape analysis was applied to construct shape models of the livers of 15 adult human subjects, recorded in a typical seated (occupant) posture. The principal component analysis was then utilized to obtain the modes of variation, the mean model, and 95% statistical boundary shape models. In addition, a total of 52 tensile tests were performed on the parenchyma of three fresh human livers at four loading rates (0.01, 0.1, 1, and 10 s^-1) to characterize the rate-dependent and failure properties of the human liver. A FE-based optimization approach was employed to identify the material parameters of an Ogden material model for each specimen. The mean material parameters were then determined for each loading rate from the characteristic averages of the stress-strain curves, and a stochastic optimization approach was utilized to determine the standard deviations of the material parameters. Results showed that the first five modes of the human liver shape models account for more than 60% of the overall anatomical variations. The distributions of the material parameters combined with the mean and statistical boundary shape models could be used to develop probabilistic finite element (FE) models, which may help to better understand the variability in biomechanical responses and injuries to the abdominal organs under impact loading.

Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study

There are at least two fundamental unanswered questions in the literature on autism spectrum disorders (ASD): Are abnormalities in white (WM) and gray matter (GM) consistent with one another? Are WM morphometric alterations consistent with alterations in the GM of regions connected by these abnormal WM bundles and vice versa? The aim of this work is to bridge this gap. After selecting voxel-based morphometry and diffusion tensor imaging studies comparing autistic and normally developing groups of subjects, we conducted an activation likelihood estimation (ALE) meta-analysis to estimate consistent brain alterations in ASD. Multidimensional scaling was used to test the similarity of the results. The ALE results were then analyzed to identify the regions of concordance between GM and WM areas. We found statistically significant topological relationships between GM and WM abnormalities in ASD. The most numerous were negative concordances, found bilaterally but with a higher prevalence in the right hemisphere. Positive concordances were found in the left hemisphere. Discordances reflected the spatial distribution of negative concordances. Thus, a different hemispheric contribution emerged, possibly related to pathogenetic factors affecting the right hemisphere during early developmental stages. Besides, WM fiber tracts linking the brain structures involved in social cognition showed abnormalities, and most of them had a negative concordance with the connected GM regions. We interpreted the results in terms of altered brain networks and their role in the pervasive symptoms dramatically impairing communication and social skills in ASD patients.

How does the corpus callosum mediate interhemispheric transfer? A review

The corpus callosum is the largest white matter structure in the human brain, connecting cortical regions of both hemispheres. Complete and partial callosotomies or callosal lesion studies have granted more insight into the function of the corpus callosum, namely the facilitation of communication between the cerebral hemispheres. How the corpus callosum mediates this information transfer is still a topic of debate. Some pose that the corpus callosum maintains independent processing between the two hemispheres, whereas others say that the corpus callosum shares information between hemispheres. These theories of inhibition and excitation are further explored by reviewing recent behavioural studies and morphological findings to gain more information about callosal function. Additional information regarding callosal function in relation to altered morphology and dysfunction in disorders is reviewed to add to the discussion of callosal involvement in interhemispheric transfer. Both the excitatory and inhibitory theories seem likely candidates to describe callosal function, however evidence also exists for both functions within the same corpus callosum. For future research it would be beneficial to investigate the functional role of the callosal sub regions to get a better understanding of function and use more appropriate experimental methods to determine functional connectivity when looking at interhemispheric transfer.