Use of Instant Messaging Applications by General Practitioners During Overseas Deployment: A Survey of the French Military Health Service.

Introduction: Instant messaging applications (MAs) represent a major component of modern telecommunications for data transmission. During overseas deployments, military doctors increasingly rely on MAs due to their availability and the urgent need to obtain advice from specialists for optimal patient management. In this study, we aimed to describe and analyze the context and usage characteristics of these MAs for transmitting medical data by military general practitioners (GPs) during overseas missions.

Dynamic multi feature-class Gaussian process models.

In model-based medical image analysis, three relevant features are the shape of structures of interest, their relative pose, and image intensity profiles representative of some physical properties. Often, these features are modelled separately through statistical models by decomposing the object's features into a set of basis functions through principal geodesic analysis or principal component analysis. However, analysing articulated objects in an image using independent single object models may lead to large uncertainties and impingement, especially around organ boundaries.

Comprehensive personalized ankle joint shape analysis of children with cerebral palsy from pediatric MRI.

Cerebral palsy, a common physical disability in childhood, often causes abnormal patterns of movement and posture. To better understand the pathology and improve rehabilitation of patients, a comprehensive bone shape analysis approach is proposed in this article. First, a group analysis is performed on a clinical MRI dataset using two state-of-the-art shape analysis methods: ShapeWorks and a voxel-based method relying on Advanced Normalization Tools (ANTs) registration.

Multi-structure bone segmentation in pediatric MR images with combined regularization from shape priors and adversarial network.

Morphological and diagnostic evaluation of pediatric musculoskeletal system is crucial in clinical practice. However, most segmentation models do not perform well on scarce pediatric imaging data. We propose a new pre-trained regularized convolutional encoder-decoder network for the challenging task of segmenting heterogeneous pediatric magnetic resonance (MR) images.

Cross-Modality Image Adaptation Based on Volumetric Intensity Gaussian Process Models (VIGPM).

Image-based diagnosis routinely depends on more that one image modality for exploiting the complementary information they provide. However, it is not always possible to obtain images from a secondary modality for several reasons such as cost, degree of invasiveness and non-availability of scanners. Three-dimensional (3D) morphable models have made a significant contribution to the field of medical imaging for feature-based analysis.

Generalizable multi-task, multi-domain deep segmentation of sparse pediatric imaging datasets via multi-scale contrastive regularization and multi-joint anatomical priors.

Clinical diagnosis of the pediatric musculoskeletal system relies on the analysis of medical imaging examinations. In the medical image processing pipeline, semantic segmentation using deep learning algorithms enables an automatic generation of patient-specific three-dimensional anatomical models which are crucial for morphological evaluation. However, the scarcity of pediatric imaging resources may result in reduced accuracy and generalization performance of individual deep segmentation models.

Assessment and comparison of image quality between two real-time sequences for dynamic MRI of distal joints at 3.0 Tesla.

Background: Real-time sequences allow functional evaluation of various joint structures during a continuous motion and help understand the pathomechanics of underlying musculoskeletal diseases.

Purpose: To assess and compare the image quality of the two most frequently used real-time sequences for joint dynamic magnetic resonance imaging (MRI), acquired during finger and ankle joint motion.

Material And Methods: A real-time dynamic acquisition protocol, including radiofrequency (RF)-spoiled and balanced steady-state free precession (bSSFP) sequences, optimized for temporal resolution with similar spatial resolution, was performed using a 3.

Optimal definitions for computing HKA angle in caos: an comparison study.

The goal of this study was to assess and compare the precision and accuracy of nine and seven methods usually used in Computer Assisted Orthopedic Surgery (CAOS) to estimate respectively the Knee Center (KC) and the Frontal Plane (FP) for the determination of the HKA angle (HKAA). An in-vitro experiment has been realized on thirteen cadaveric lower limbs. A CAOS software application was developed and allowed the computation of the HKAA according to these nine KC and seven FP methods.

Anatomically Parameterized Statistical Shape Model: Explaining Morphometry Through Statistical Learning.

Objective: Statistical shape models (SSMs) are a popular tool to conduct morphological analysis of anatomical structures which is a crucial step in clinical practices. However, shape representations through SSMs are based on shape coefficients and lack an explicit one-to-one relationship with anatomical measures of clinical relevance. While a shape coefficient embeds a combination of anatomical measures, a formalized approach to find the relationship between them remains elusive in the literature.

A Musculoskeletal Model Customized for Sagittal and Frontal Knee Kinematics With Improved Knee Joint Stability.

Current lower limb musculoskeletal (MSK) models focus on sagittal plane kinematics. However, abnormal gait is typically associated with sagittal plane motions crossing into other planes, limiting the use of current MSK models. The purpose of this study was twofold, first, to extend the capability of a full-body MSK model from the literature to include frontal knee plane kinematics during healthy gait, and second, to propose and implement a realistic muscle discretization technique.

Ultrasound Ulnar Nerve Measurement in a Healthy Population.

Introduction: Ulnar tunnel syndrome at the elbow is a common pathology. The ultrasound cross-sectional area is a well-known metric widely accepted in radiology for the description of nerve entrapment. However, the pathological cut-off value remains challenging.

Dynamic MRI for articulating joint evaluation on 1.5 T and 3.0 T scanners: setup, protocols, and real-time sequences.

Dynamic magnetic resonance imaging (MRI) is a non-invasive method that can be used to increase the understanding of the pathomechanics of joints. Various types of real-time gradient echo sequences used for dynamic MRI acquisition of joints include balanced steady-state free precession sequence, radiofrequency-spoiled sequence, and ultra-fast gradient echo sequence. Due to their short repetition time and echo time, these sequences provide high temporal resolution, a good signal-to-noise ratio and spatial resolution, and soft tissue contrast.

Clinical relevance of augmented statistical shape model of the scapula in the glenoid region.

Objective: To illustrate (a) whether a statistical shape model (SSM) augmented with anatomical landmark set(s) performs better fitting and provides improved clinical relevance over non-augmented SSM and (b) which anatomical landmark set provides the best augmentation strategy for predicting the glenoid region of the scapula.

Methods: Scapula SSM was built using 27 dry bone CT scans and augmented with three anatomical landmark sets (16 landmarks each) resulting in three augmented SSMs (aSSM, aSSM, aSSM). The non-augmented and three augmented SSMs were then used in a non-rigid registration (regression) algorithm to fit to six external scapular shapes.

Statistical Shape Modeling Approach to Predict Missing Scapular Bone.

Prediction of complete and premorbid scapular anatomy is an important aspect of successful shoulder arthroplasty surgeries to treat glenohumeral arthritis and which remains elusive in the current literature. We proposed to build a statistical shape model (SSM) of the scapula and use it to build a framework to predict a complete scapular shape from virtually created scapular bone defects. The bone defects were synthetically created to imitate bone loss in the glenoid region and missing bony part in inferior and superior scapular regions.

3-D lower extremity bone morphology in ambulant children with cerebral palsy and its relation to gait.

Changes in lower-extremity bone morphology are potential mid- to long-term secondary consequences of cerebral palsy (CP), affecting activity. Little is known about the 3-D morphology of lower-extremity bones in children with CP and the association with gait deviations. The main aim of this study was to describe and compare 3-D lower-extremity bone morphology in ambulant children with unilateral or bilateral CP.

Predicting epiphyseal screw length in anterior plating of distal radial fractures.

The purpose of this study was to determine whether optimal epiphyseal screw length could be predicted with reference to a given diaphyseal screw length when fixating a plate to the anterior surface of the distal radius. Computerized tomography scans of 40 wrists of 28 men and 12 women were semi-automatically segmented. A virtual anterior plate model was fixed to the distal radius.

Effects of gleno-humeral joint centre mislocation on gleno-humeral kinematics and kinetics.

The gleno-humeral (GH) rotation centre is typically estimated using predictive or functional methods, however these methods may lead to location errors. This study aimed at determining a location error threshold above which statistically significant changes in the values of kinematic and kinetic GH parameters occur. The secondary aims were to quantify the effects of the direction of mislocation (X, Y or Z axis) of the GH rotation centre on GH kinematic and kinetic parameters.

In vivo ankle joint kinematics from dynamic magnetic resonance imaging using a registration-based framework.

In this paper, we propose a method for non-invasively measuring three-dimensional in vivo kinematics of the ankle joint from a dynamic MRI acquisition of a single range-of-motion cycle. The proposed approach relies on an intensity-based registration method to estimate motion from multi-plane dynamic MRI data. Our approach recovers not only the movement of the skeleton, but also the possibly non-rigid temporal deformation of the joint.

Quantifying skeletal muscle volume and shape in humans using MRI: A systematic review of validity and reliability.

Aims: The aim of this study was to report the metrological qualities of techniques currently used to quantify skeletal muscle volume and 3D shape in healthy and pathological muscles.

Methods: A systematic review was conducted (Prospero CRD42018082708). PubMed, Web of Science, Cochrane and Scopus databases were searched using relevant keywords and inclusion/exclusion criteria.

Dynamic MRI to quantify musculoskeletal motion: A systematic review of concurrent validity and reliability, and perspectives for evaluation of musculoskeletal disorders.

Purpose: To report evidence for the concurrent validity and reliability of dynamic MRI techniques to evaluate in vivo joint and muscle mechanics, and to propose recommendations for their use in the assessment of normal and impaired musculoskeletal function.

Materials And Methods: The search was conducted on articles published in Web of science, PubMed, Scopus, Academic search Premier, and Cochrane Library between 1990 and August 2017. Studies that reported the concurrent validity and/or reliability of dynamic MRI techniques for in vivo evaluation of joint or muscle mechanics were included after assessment by two independent reviewers.

Subject-specific shoulder muscle attachment region prediction using statistical shape models: A validity study.

Subject-specific musculoskeletal models can predict accurate joint and muscle biomechanics thereby helping clinicians and surgeons. Current modeling strategies do not incorporate accurate subject-specific muscle parameters. This study reports a statistical shape model (SSM) based method to predict subject-specific muscle attachment regions on shoulder bones and illustrates the concurrent validity of the predictions.

Assessment of 3D morphological characteristics of the shoulder bones using statistical shape modeling: Prospective application to handedness.

In this study we have described the use of statistical shape modeling (SSM) technique in evaluating the morphological variation of shoulder bones from a South African population. The anatomical landmark selections were carried out, followed by the registration of the meshes which were validated before establishing the dense correspondence. The SSMs were built and average shape comparison from each side for each bone were made in order to evaluate handedness.