The Brush Foundation studies on human growth and development, begun in 1931 and terminated in 1942, have been intensively reviewed and studied by Dr Greulich and Miss Pyle in the formulation of this Radiographic Atlas of Skeletal Development of the Hand and Wrist Serial radiographs of from 2 to 20 hand-films made at successive examinations of each of 1000 boys and girls made up the radiographic material Standards were selected that were judged to be the most representative of the central tendency or anatomic mode of each chronologic age group from birth through 18 years

Radiographic Atlas of Skeletal Development of the Hand and Wrist

https://www.dentalage.co.uk/wp-content/uploads/2014/09/cunha_e_et_al_2009_aging-human-remains-a-review.pdf

The problem of aging human remains and living individuals: a review.

Low vitamin D levels during pregnancy may account for reduced fetal growth and for altered neonatal development. The present study explored the association between maternal vitamin D status measured early in pregnancy and birth weight, prevalence of small-for-gestational-age (SGA) infants and postnatal growth (weight and length), as well as the potential role of vitamin D status in explaining ethnic disparities in these outcomes. Data were derived from a large multi-ethnic cohort in The Netherlands (Amsterdam Born Children and their Development (ABCD) cohort), and included 3730 women with live-born singleton term deliveries. Maternal serum vitamin D was measured during early pregnancy (median 13 weeks, interquartile range: 12-14), and was labelled 'deficient' ( or= 50 nmol/l). Six ethnic groups were distinguished: Dutch, Surinamese, Turkish, Moroccan, other non-Western and other Western. Associations with neonatal outcomes were analysed using multivariate regression analyses. Results showed that compared with women with adequate vitamin D levels, women with deficient vitamin D levels had infants with lower birth weights ( - 114.4 g, 95 % CI - 151.2, - 77.6) and a higher risk of SGA (OR 2.4, 95 % CI 1.9, 3.2). Neonates born to mothers with a deficient vitamin D status showed accelerated growth in weight and length during the first year of life. Although a deficient vitamin D status influenced birth weight, SGA risk and neonatal growth, it played a limited role in explaining ethnic differences. Although vitamin D supplementation might be beneficial to those at risk of a deficient vitamin D status, more research is needed before a nationwide policy on the subject can be justified.

/pdf/maternal-early-pregnancy-vitamin-d-status-in-relation-to-3qichmxue0.pdf

Maternal early pregnancy vitamin D status in relation to fetal and neonatal growth: results of the multi-ethnic Amsterdam Born Children and their Development cohort.

A deep-learning convolutional neural network model can estimate skeletal maturity with accuracy similar to that of an expert radiologist and to that of current state-of-the-art feature extraction–based automated models for assessment of bone age.

Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs.

Deep Learning for Automated Skeletal Bone Age Assessment in X-Ray Images

Bone age assessment of children using a digital hand atlas.

Our results show the cross-racial differences between the skeletal growth patterns of Asian and Hispanic children and skeletal growth patterns of white and African American children.

https://pubs.rsna.org/doi/pdf/10.1148/radiol.2493080468

Racial differences in growth patterns of children assessed on the basis of bone age.

Automatic bone age assessment for young children from newborn to 7-year-old using carpal bones.

Storage and retrieval technology for large-scale medical image systems has matured significantly during the past ten years but many implementations still lack cost-effective backup and recovery solutions. As an example, a PACS (Picture Archiving and Communication system) in a general medical center requires about 40 Terabytes of storage capacity for seven years. Despite many healthcare centers are relying on PACS for 24/7 clinical operation, current PACS lacks affordable fault-tolerance storage strategies for archive, backup, and disaster recovery. Existing solutions are difficult to administer, and often time consuming for effective recovery after a disaster. For this reason, PACS still encounters unexpected downtime for hours or days, which could cripple daily clinical service and research operations. Grid Computing represents the latest and most exciting technology to evolve from the familiar realm of parallel, peer-to-peer, and client-server models that can address the problem of fault-tolerant storage for backup and recovery of medical images. We have researched and developed a novel Data Grid testbed involving several federated PAC systems based on grid computing architecture. By integrating grid architecture to the PACS DICOM (Digital Imaging and Communication in Medicine) environment, in addition to use its own storage device, a PACS also uses a federated Data Grid composing of several PAC systems for off-site backup archive. In case its own storage fails, the PACS can retrieve its image data from the Data Grid timely and seamlessly. The design reflects the Globus Toolkit 3.0 five-layer architecture of the grid computing: Fabric, Resource, Connectivity, Collective, and Application Layers. The testbed consists of three federated PAC systems, the Fault-Tolerant PACS archive server at the Image Processing and Informatics Laboratory, the clinical PACS at Saint John's Health Center, and the clinical PACS at the Healthcare Consultation Center II, USC Health Science Campus.In the testbed, we also implement computational services in the Data Grid for image analysis and data mining. The federated PAC systems can use this resource by sharing image data and computational services available in the Data Grid for image analysis and data mining application.In the paper, we first review PACS and its clinical operation, followed by the description of the Data Grid architecture in the testbed. Different scenarios of using the DICOM store and query/retrieve functions of the laboratory model to demonstrate the fault-tolerance features of the Data Grid are illustrated. The status of current clinical implementation of the Data Grid is reported. An example of using the digital hand atlas for bone age assessment of children is presented to describe the concept of computational services in the Data Grid.

Data grid for large-scale medical image archive and analysis

A computer-aided-diagnosis (CAD) method has been previously developed based on features extracted from phalangeal
regions of interest (ROI) in a digital hand atlas, which can assess bone age of children from ages 7 to 18 accurately.
Therefore, in order to assess the bone age of children in younger ages, the inclusion of carpal bones is necessary. In this
paper, we developed and implemented a knowledge-based method for fully automatic carpal bone segmentation and
morphological feature analysis. Fuzzy classification was then used to assess the bone age based on the selected features.
Last year, we presented carpal bone segmentation algorithm. This year, research works on procedures after carpal bone
segmentation including carpal bone identification, feature analysis and fuzzy system for bone age assessment is
presented. This method has been successfully applied on all cases in which carpal bones have not overlapped. CAD
results of total about 205 cases from the digital hand atlas were evaluated against subject chronological age as well as
readings of two radiologists. It was found that the carpal ROI provides reliable information in determining the bone age
for young children from newborn to 7-year-old.

Aifeng Zhang

Papers

Bone age assessment of children using a digital hand atlas.

Racial differences in growth patterns of children assessed on the basis of bone age.

Automatic bone age assessment for young children from newborn to 7-year-old using carpal bones.

Data grid for large-scale medical image archive and analysis

Bone age assessment for young children from newborn to 7-year-old using carpal bones