Dataset Information

A statistical skull geometry model for children 0-3 years old.

ABSTRACT: Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0-3 YO population. In this study, head CT scans from fifty-six 0-3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models.

SUBMITTER: Li Z

PROVIDER: S-EPMC4436309 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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A statistical skull geometry model for children 0-3 years old.

Li Zhigang Z Park Byoung-Keon BK Liu Weiguo W Zhang Jinhuan J Reed Matthew P MP Rupp Jonathan D JD Hoff Carrie N CN Hu Jingwen J

PloS one 20150518 5

Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0-3 YO population. In this study, head CT scans from fifty-six 0-3 YO children were used to develop a statisti ...[more]

PMID: 25992998

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Project description:BackgroundThis study aims to capture the 3D shape of the human skull in a healthy paediatric population (0-4 years old) and construct a generative statistical shape model.MethodsThe skull bones of 178 healthy children (55% male, 20.8 ± 12.9 months) were reconstructed from computed tomography (CT) images. 29 anatomical landmarks were placed on the 3D skull reconstructions. Rotation, translation and size were removed, and all skull meshes were placed in dense correspondence using a dimensionless skull mesh template and a non-rigid iterative closest point algorithm. A 3D morphable model (3DMM) was created using principal component analysis, and intrinsically and geometrically validated with anthropometric measurements. Synthetic skull instances were generated exploiting the 3DMM and validated by comparison of the anthropometric measurements with the selected input population.ResultsThe 3DMM of the paediatric skull 0-4 years was successfully constructed. The model was reasonably compact - 90% of the model shape variance was captured within the first 10 principal components. The generalisation error, quantifying the ability of the 3DMM to represent shape instances not encountered during training, was 0.47 mm when all model components were used. The specificity value was <0.7 mm demonstrating that novel skull instances generated by the model are realistic. The 3DMM mean shape was representative of the selected population (differences <2%). Overall, good agreement was observed in the anthropometric measures extracted from the selected population, and compared to normative literature data (max difference in the intertemporal distance) and to the synthetic generated cases.ConclusionThis study presents a reliable statistical shape model of the paediatric skull 0-4 years that adheres to known skull morphometric measures, can accurately represent unseen skull samples not used during model construction and can generate novel realistic skull instances, thus presenting a solution to limited availability of normative data in this field.

Project description:BackgroundAccurate accelerometer-based methods are required for assessment of 24-h physical behavior in young children. We aimed to summarize evidence on measurement properties of accelerometer-based methods for assessing 24-h physical behavior in young children.MethodsWe searched PubMed (MEDLINE) up to June 2021 for studies evaluating reliability or validity of accelerometer-based methods for assessing physical activity (PA), sedentary behavior (SB), or sleep in 0-5-year-olds. Studies using a subjective comparison measure or an accelerometer-based device that did not directly output time series data were excluded. We developed a Checklist for Assessing the Methodological Quality of studies using Accelerometer-based Methods (CAMQAM) inspired by COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN).ResultsSixty-two studies were included, examining conventional cut-point-based methods or multi-parameter methods. For infants (0-12 months), several multi-parameter methods proved valid for classifying SB and PA. From three months of age, methods were valid for identifying sleep. In toddlers (1-3 years), cut-points appeared valid for distinguishing SB and light PA (LPA) from moderate-to-vigorous PA (MVPA). One multi-parameter method distinguished toddler specific SB. For sleep, no studies were found in toddlers. In preschoolers (3-5 years), valid hip and wrist cut-points for assessing SB, LPA, MVPA, and wrist cut-points for sleep were identified. Several multi-parameter methods proved valid for identifying SB, LPA, and MVPA, and sleep. Despite promising results of multi-parameter methods, few models were open-source. While most studies used a single device or axis to measure physical behavior, more promising results were found when combining data derived from different sensor placements or multiple axes.ConclusionsUp to age three, valid cut-points to assess 24-h physical behavior were lacking, while multi-parameter methods proved valid for distinguishing some waking behaviors. For preschoolers, valid cut-points and algorithms were identified for all physical behaviors. Overall, we recommend more high-quality studies evaluating 24-h accelerometer data from multiple sensor placements and axes for physical behavior assessment. Standardized protocols focusing on including well-defined physical behaviors in different settings representative for children's developmental stage are required. Using our CAMQAM checklist may further improve methodological study quality.Prospero registration numberCRD42020184751.

Project description:BackgroundIt is estimated that less than one third of women (28%) worldwide, are not sufficiently active, and there is evidence indicating physical activity (PA) participation is lower during pregnancy and the postpartum period. Despite the importance of educating and encouraging postpartum women to engage in PA, existing systematic reviews have only focused on examining the impact of individually tailored PA interventions and on specific postpartum populations such as women who are inactive (i.e., do not meet PA recommendations) or women at risk of gestational diabetes mellitus or postnatal depression. This review aims to fill this gap by examining the impact of group-based PA interventions on postpartum women's PA levels or other health behavior outcomes.MethodsA systematic literature search was conducted using four electronic databases (MEDLINE, CINAHL, EMBASE and PsychInfo) of published studies between 1st January 2000 and 31st October 2020. Studies were included if they targeted postpartum women with no current health conditions, had children aged 0-5 years, and engaged postpartum women in a group-based PA program that reported PA or other health behavior outcomes. Out of a total of 1091 articles that were initially identified, six were included.ResultsGroup-based PA interventions were moderately successful in changing or increasing postpartum women's self-reported PA levels and psychological wellbeing in the first 2 years of their offspring's life. Overall, group-based PA interventions were not successful in changing or increasing postpartum women's objectively measured PA levels, but only one study objectively measured postpartum women's PA levels. Narrative synthesis highlights the heterogeneity of the outcomes and methodologies used, and the low to medium risk of bias in the included studies.ConclusionTo strengthen the evidence-base for group-based PA programs with postpartum women there is an on-going need for more rigorous randomised controlled trials of appropriate length (at least 3 months in duration) with an adequate dose of group-based PA sessions per week (to meet PA guidelines), and that utilise objective measures of PA. In addition, future PA interventions for this population should include, at the very least, fidelity and process data to capture the characteristics or design features that appeal most to postpartum women.

Project description:ObjectivesShwachman-Diamond syndrome (SDS) is a rare autosomal recessive disorder. Its predominant manifestations include exocrine pancreatic insufficiency, bone marrow failure and skeletal abnormalities. Patients frequently present failure to thrive and susceptibility to short stature. Average birth weight is at the 25th percentile; by the first birthday, >50% of patients drop below the third percentile for height and weight.The study aims at estimating the growth charts for patients affected by SDS in order to give a reference tool helpful for medical care and growth surveillance through the first 8 years of patient's life.Setting and participantsThis retrospective observational study includes 106 patients (64 M) with available information from birth to 8 years, selected among the 122 patients included in the Italian National Registry of SDS and born between 1975 and 2016. Gender, birth date and auxological parameters at repeated assessment times were collected. The General Additive Model for Location Scale and Shape method was applied to build the growth charts. A set of different distributions was used, and the more appropriate were selected in accordance with the smallest Akaike information criterion.ResultsA total of 408 measurements was collected and analysed. The median number of observations per patient amounted to 3, range 1-11. In accordance with the methods described, specific SDS growth charts were built for weight, height and body mass index (BMI), separately for boys and girls.The 50th and 3rd percentiles of weight and height of the healthy population (WHO standard references) respectively correspond to the 97th and 50th percentiles of the SDS population (SDS specific growth charts), while the difference is less evident for the BMI.ConclusionsSpecific SDS growth charts obtained through our analysis enable a more appropriate classification of patients based on auxological parameters, representing a useful reference tool for evaluating their growth during childhood.

Dataset Information

A statistical skull geometry model for children 0-3 years old.

Publications

A statistical skull geometry model for children 0-3 years old.

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