In vivo imaging of the tonoplast intrinsic protein family in Arabidopsis roots

Background: Tonoplast intrinsic proteins (TIPs) are widely used as markers for vacuolar compartments in higher plants. Ten TIP isoforms are encoded by the Arabidopsis genome. For several isoforms, the tissue and cell specific pattern of expression are not known. Results: We generated fluorescent protein fusions to the genomic sequences of all members of the Arabidopsis TIP family whose expression is predicted to occur in root tissues (TIP1;1 and 1;2; TIP2;1, 2;2 and 2;3; TIP4;1) and expressed these fusions, both individually and in selected pairwise combinations, in transgenic Arabidopsis. Analysis by confocal microscopy revealed that TIP distribution varied between different cell layers within the root axis, with extensive co-expression of some TIPs and more restricted expression patterns for other isoforms. TIP isoforms whose expression overlapped appeared to localise to the tonoplast of the central vacuole, vacuolar bulbs and smaller, uncharacterised structures. Conclusion: We have produced a comprehensive atlas of TIP expression in Arabidopsis roots, which reveals novel expression patterns for not previously studied TIPs

Modelling human skull growth: a validated computational model

© 2017 The Author(s) Published by the Royal Society. All rights reserved. During the first year of life, the brain grows rapidly and the neurocranium increases to about 65% of its adult size. Our understanding of the relationship between the biomechanical forces, especially from the growing brain, the craniofacial soft tissue structures and the individual bone plates of the skull vault is still limited. This basic knowledge could help in the future planning of craniofacial surgical operations. The aim of this study was to develop a validated computational model of skull growth, based on the finite-element (FE) method, to help understand the biomechanics of skull growth. To do this, a two-step validation study was carried out. First, an in vitro physical three-dimensional printed model and an in silico FE model were created from the same micro-CT scan of an infant skull and loaded with forces from the growing brain from zero to two months of age. The results from the in vitro model validated the FE model before it was further developed to expand from 0 to 12 months of age. This second FE model was compared directly with in vivo clinical CT scans of infants without craniofacial conditions (n = 56). The various models were compared in terms of predicted skull width, length and circumference, while the overall shape was quantified using three-dimensional distance plots. Statistical analysis yielded no significant differences between the male skull models. All size measurements from the FE model versus the in vitro physical model were within 5%, with one exception showing a 7.6% difference. The FE model and in vivo data also correlated well, with the largest percentage difference in size being 8.3%. Overall, the FE model results matched well with both the in vitro and in vivo data. With further development and model refinement, this modelling method could be used to assist in preoperative planning of craniofacial surgery procedures and could help to reduce reoperation rates

Normal human craniofacial growth and development from 0 to 4 years

Knowledge of human craniofacial growth (increase in size) and development (change in shape) is important in the clinical treatment of a range of conditions that afects it. This study uses an extensive collection of clinical CT scans to investigate craniofacial growth and development over the frst 48 months of life, detail how the cranium changes in form (size and shape) in each sex and how these changes are associated with the growth and development of various soft tissues such as the brain, eyes and tongue and the expansion of the nasal cavity. This is achieved through multivariate analyses of cranial form based on 3D landmarks and semi-landmarks and by analyses of linear dimensions, and cranial volumes. The results highlight accelerations and decelerations in cranial form changes throughout early childhood. They show that from 0 to 12 months, the cranium undergoes greater changes in form than from 12 to 48 months. However, in terms of the development of overall cranial shape, there is no signifcant sexual dimorphism in the age range considered in this study. In consequence a single model of human craniofacial growth and development is presented for future studies to examine the physio-mechanical interactions of the craniofacial growth

Icex: Advances in the automatic extraction and volume calculation of cranial cavities

The use of non-destructive approaches for digital acquisition (e.g. computerised tomography-CT) allows detailed qualitative and quantitative study of internal structures of skeletal material. Here, we present a new R-based software tool, Icex, applicable to the study of the sizes and shapes of skeletal cavities and fossae in 3D digital images. Traditional methods of volume extraction involve the manual labelling (i.e. segmentation) of the areas of interest on each section of the image stack. This is time-consuming, error-prone and challenging to apply to complex cavities. Icex facilitates rapid quantification of such structures. We describe and detail its application to the isolation and calculation of volumes of various cranial cavities. The R tool is used here to automatically extract the orbital volumes, the paranasal sinuses, the nasal cavity and the upper oral volumes, based on the coordinates of 18 cranial anatomical points used to define their limits, from 3D cranial surface meshes obtained by segmenting CT scans. Icex includes an algorithm (Icv) for the calculation of volumes by defining a 3D convex hull of the extracted cavity. We demonstrate the use of Icex on an ontogenetic sample (0-19 years) of modern humans and on the fossil hominin crania Kabwe (Broken Hill) 1, Gibraltar (Forbes' Quarry) and Guattari 1. We also test the tool on three species of non-human primates. In the modern human subsample, Icex allowed us to perform a preliminary analysis on the absolute and relative expansion of cranial sinuses and pneumatisations during growth. The performance of Icex, applied to diverse crania, shows the potential for an extensive evaluation of the developmental and/or evolutionary significance of hollow cranial structures. Furthermore, being open source, Icex is a fully customisable tool, easily applicable to other taxa and skeletal regions

New diagnostic criteria for metopic ridges and trigonocephaly: a 3D geometric approach

Background: Trigonocephaly occurs due to the premature fusion of the metopic suture, leading to a triangular forehead and hypotelorism. This condition often requires surgical correction for morphological and functional indications. Metopic ridges also originate from premature metopic closure but are only associated with mid-frontal bulging; their surgical correction is rarely required. Differential diagnosis between these two conditions can be challenging, especially in minor trigonocephaly.// Methods: Two hundred seven scans of patients with trigonocephaly (90), metopic rigdes (27), and controls (90) were collected. Geometric morphometrics were used to quantify skull and orbital morphology as well as the interfrontal angle and the cephalic index. An innovative method was developed to automatically compute the frontal curvature along the metopic suture. Different machine-learning algorithms were tested to assess the predictive power of morphological data in terms of classification.// Results: We showed that control patients, trigonocephaly and metopic rigdes have distinctive skull and orbital shapes. The 3D frontal curvature enabled a clear discrimination between groups (sensitivity and specificity > 92%). Furthermore, we reached an accuracy of 100% in group discrimination when combining 6 univariate measures.// Conclusion: Two diagnostic tools were proposed and demonstrated to be successful in assisting differential diagnosis for patients with trigonocephaly or metopic ridges. Further clinical assessments are required to validate the practical clinical relevance of these tools

New diagnostic criteria for metopic ridges and trigonocephaly:a 3D geometric approach

Background: Trigonocephaly occurs due to the premature fusion of the metopic suture, leading to a triangular forehead and hypotelorism. This condition often requires surgical correction for morphological and functional indications. Metopic ridges also originate from premature metopic closure but are only associated with mid-frontal bulging; their surgical correction is rarely required. Differential diagnosis between these two conditions can be challenging, especially in minor trigonocephaly. Methods: Two hundred seven scans of patients with trigonocephaly (90), metopic rigdes (27), and controls (90) were collected. Geometric morphometrics were used to quantify skull and orbital morphology as well as the interfrontal angle and the cephalic index. An innovative method was developed to automatically compute the frontal curvature along the metopic suture. Different machine-learning algorithms were tested to assess the predictive power of morphological data in terms of classification. Results: We showed that control patients, trigonocephaly and metopic rigdes have distinctive skull and orbital shapes. The 3D frontal curvature enabled a clear discrimination between groups (sensitivity and specificity &gt; 92%). Furthermore, we reached an accuracy of 100% in group discrimination when combining 6 univariate measures. Conclusion: Two diagnostic tools were proposed and demonstrated to be successful in assisting differential diagnosis for patients with trigonocephaly or metopic ridges. Further clinical assessments are required to validate the practical clinical relevance of these tools.</p

New diagnostic criteria for metopic ridges and trigonocephaly:a 3D geometric approach

Background: Trigonocephaly occurs due to the premature fusion of the metopic suture, leading to a triangular forehead and hypotelorism. This condition often requires surgical correction for morphological and functional indications. Metopic ridges also originate from premature metopic closure but are only associated with mid-frontal bulging; their surgical correction is rarely required. Differential diagnosis between these two conditions can be challenging, especially in minor trigonocephaly. Methods: Two hundred seven scans of patients with trigonocephaly (90), metopic rigdes (27), and controls (90) were collected. Geometric morphometrics were used to quantify skull and orbital morphology as well as the interfrontal angle and the cephalic index. An innovative method was developed to automatically compute the frontal curvature along the metopic suture. Different machine-learning algorithms were tested to assess the predictive power of morphological data in terms of classification. Results: We showed that control patients, trigonocephaly and metopic rigdes have distinctive skull and orbital shapes. The 3D frontal curvature enabled a clear discrimination between groups (sensitivity and specificity &gt; 92%). Furthermore, we reached an accuracy of 100% in group discrimination when combining 6 univariate measures. Conclusion: Two diagnostic tools were proposed and demonstrated to be successful in assisting differential diagnosis for patients with trigonocephaly or metopic ridges. Further clinical assessments are required to validate the practical clinical relevance of these tools.</p

Growth Patterns and Shape Development of the Paediatric Mandible &amp;#8211; a 3d Statistical Model

Background/Aim:To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females.Methods:Computed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 &amp;#177; 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, whilst size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and gender. Growth curves were constructed for anthropometric measurements.Results:A 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Pearson&amp;#8217;s r = 0.92, p &amp;#60; 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Pearson&amp;#8217;s r = -0.9, p &amp;#60;0.01). Little correlation was observed between extracted shape modes and gender with either PCA or PLS for this study population.Conclusion:The presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and gender. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up

Growth Patterns and Shape Development of the Paediatric Mandible &amp;#8211; a 3d Statistical Model

Background/Aim:To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females.Methods:Computed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 &amp;#177; 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, whilst size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and gender. Growth curves were constructed for anthropometric measurements.Results:A 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Pearson&amp;#8217;s r = 0.92, p &amp;#60; 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Pearson&amp;#8217;s r = -0.9, p &amp;#60;0.01). Little correlation was observed between extracted shape modes and gender with either PCA or PLS for this study population.Conclusion:The presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and gender. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up

Growth patterns and shape development of the paediatric mandible – A 3D statistical model

BACKGROUND/AIM: To develop a 3D morphable model of the normal paediatric mandible to analyse shape development and growth patterns for males and females. METHODS: Computed tomography (CT) data was collected for 242 healthy children referred for CT scan between 2011 and 2018 aged between 0 and 47 months (mean, 20.6 ± 13.4 months, 59.9% male). Thresholding techniques were used to segment the mandible from the CT scans. All mandible meshes were annotated using a defined set of 52 landmarks and processed such that all meshes followed a consistent triangulation. Following this, the mandible meshes were rigidly aligned to remove translation and rotation effects, while size effects were retained. Principal component analysis (PCA) was applied to the processed meshes to construct a generative 3D morphable model. Partial least squares (PLS) regression was also applied to the processed data to extract the shape modes with which to evaluate shape differences for age and sex. Growth curves were constructed for anthropometric measurements. RESULTS: A 3D morphable model of the paediatric mandible was constructed and validated with good generalisation, compactness, and specificity. Growth curves of the assessed anthropometric measurements were plotted without significant differences between male and female subjects. The first principal component was dominated by size effects and is highly correlated with age at time of scan (Spearman's r = 0.94, p < 0.01). As with PCA, the first extracted PLS mode captures much of the size variation within the dataset and is highly correlated with age (Spearman's r = −0.94, p < 0.01). Little correlation was observed between extracted shape modes and sex with either PCA or PLS for this study population. CONCLUSION: The presented 3D morphable model of the paediatric mandible enables an understanding of mandibular shape development and variation by age and sex. It allowed for the construction of growth curves, which contains valuable information that can be used to enhance our understanding of various disorders that affect the mandibular development. Knowledge of shape changes in the growing mandible has potential to improve diagnostic accuracy for craniofacial conditions that impact the mandibular morphology, objective evaluation, surgical planning, and patient follow-up