Virtual lumbar spine of multi-body model based on simbody

The spine is an important and complex skeletal structure in the human body. It is a vulnerable part of our skeleton that is open to many medical problems. Hence it is necessary to establish a virtual spine model to assist surgeons to understand biomechanics of the spine. In this study, we aim to propose a virtual spine multi-body model. The computational biomechanical modeling of the spine is based on the theory of multi-body dynamics and implemented with SimBody open-source SDK. Simbody was then used to solve the kinetic equations and simulate the movement of spine. The spine model was validated by comparing its simulation results with experimental results from literature. The spine model will be helpful to understand biomechanics of the spine under loading.

Characterizing the molecular phenotype of an Atp7a(T985I) conditional knock in mouse model for X-linked distal hereditary motor neuropathy (dHMNX)

ATP7A is a P-type ATPase essential for cellular copper (Cu) transport and homeostasis. Loss-of-function ATP7A mutations causing systemic Cu deficiency are associated with severe Menkes disease or its milder allelic variant, occipital horn syndrome. We previously identified two rare ATP7A missense mutations (P1386S and T994I) leading to a non-fatal form of motor neuron disorder, X-linked distal hereditary motor neuropathy (dHMNX), without overt signs of systemic Cu deficiency. Recent investigations using a tissue specific Atp7a knock out model have demonstrated that Cu plays an essential role in motor neuron maintenance and function, however the underlying pathogenic mechanisms of ATP7A mutations causing axonal degeneration remain unknown. We have generated an Atp7a conditional knock in mouse model of dHMNX expressing Atp7a(T985I), the orthologue of the human ATP7A(T994I) identified in dHMNX patients. Although a degenerative motor phenotype is not observed, the knock in Atp7a(T985I/Y) mice show altered Cu levels within the peripheral and central nervous systems, an increased diameter of the muscle fibres and altered myogenin and myostatin gene expression. Atp7a(T985I/Y) mice have reduced Atp7a protein levels and recapitulate the defective trafficking and altered post-translational regulatory mechanisms observed in the human ATP7A(T994I) patient fibroblasts. Our model provides a unique opportunity to characterise the molecular phenotype of dHMNX and the time course of cellular events leading to the process of axonal degeneration in this disease.

In vitro strain measurements in cerebral aneurysm models for cyber-physical diagnosis

Background: The development of new diagnostic technologies for cerebrovascular diseases requires an understanding of the mechanism behind the growth and rupture of cerebral aneurysms. To provide a comprehensive diagnosis and prognosis of this disease, it is desirable to evaluate wall shear stress, pressure, deformation and strain in the aneurysm region, based on information provided by medical imaging technologies. Methods: In this research, we propose a new cyber-physical system composed of in vitro dynamic strain experimental measurements and computational fluid dynamics (CFD) simulation for the diagnosis of cerebral aneurysms. A CFD simulation and a scaled-up membranous silicone model of a cerebral aneurysm were completed, based on patient-specific data recorded in August 2008. In vitro blood flow simulation was realized with the use of a specialized pump. A vision system was also developed to measure the strain at different regions on the model by way of pulsating blood flow circulating inside the model. Results: Experimental results show that distance and area strain maxima were larger near the aneurysm neck (0.042 and 0.052), followed by the aneurysm dome (0.023 and 0.04) and finally the main blood vessel section (0.01 and 0.014). These results were complemented by a CFD simulation for the addition of wall shear stress, oscillatory shear index and aneurysm formation index. Diagnosis results using imaging obtained in August 2008 are consistent with the monitored aneurysm growth in 2011. Conclusion: The presented study demonstrates a new experimental platform for measuring dynamic strain within cerebral aneurysms. This platform is also complemented by a CFD simulation for advanced diagnosis and prediction of the growth tendency of an aneurysm in endovascular surgery.

Patient admission prediction using a pruned fuzzy min–max neural network with rule extraction

A useful patient admission prediction model that helps the emergency department of a hospital admit patients efficiently is of great importance. It not only improves the care quality provided by the emergency department but also reduces waiting time of patients. This paper proposes an automatic prediction method for patient admission based on a fuzzy min–max neural network (FMM) with rules extraction. The FMM neural network forms a set of hyperboxes by learning through data samples, and the learned knowledge is used for prediction. In addition to providing predictions, decision rules are extracted from the FMM hyperboxes to provide an explanation for each prediction. In order to simplify the structure of FMM and the decision rules, an optimization method that simultaneously maximizes prediction accuracy and minimizes the number of FMM hyperboxes is proposed. Specifically, a genetic algorithm is formulated to find the optimal configuration of the decision rules. The experimental results using a large data set consisting of 450740 real patient records reveal that the proposed method achieves comparable or even better prediction accuracy than state-of-the-art classifiers with the additional ability to extract a set of explanatory rules to justify its predictions.

Toxicity prediction in cancer using multiple instance learning in a multi-task framework

Treatments of cancer cause severe side effects called toxicities. Reduction of such effects is crucial in cancer care. To impact care, we need to predict toxicities at fortnightly intervals. This toxicity data differs from traditional time series data as toxicities can be caused by one treatment on a given day alone, and thus it is necessary to consider the effect of the singular data vector causing toxicity. We model the data before prediction points using the multiple instance learning, where each bag is composed of multiple instances associated with daily treatments and patient-specific attributes, such as chemotherapy, radiotherapy, age and cancer types. We then formulate a Bayesian multi-task framework to enhance toxicity prediction at each prediction point. The use of the prior allows factors to be shared across task predictors. Our proposed method simultaneously captures the heterogeneity of daily treatments and performs toxicity prediction at different prediction points. Our method was evaluated on a real-word dataset of more than 2000 cancer patients and had achieved a better prediction accuracy in terms of AUC than the state-of-art baselines.

A domain-specific approach for assessing physical activity efficacy in adolescents: from scale conception to predictive validity

Objective: To develop and test the utility of a domain-specific physical activity efficacy scale in adolescents for predicting physical activity behaviour. Design: Two independent studies were conducted. Study 1 examined the psychometric properties of a newly constructed Domain-Specific Physical Activity Efficacy Questionnaire (DSPAEQ) and study 2 tested the utility of the scale for predicting leisure- and school-time physical activity. Methods: In study 1, descriptive physical activity data were used to generate scale items. The scales factor structure and internal consistency were tested in a sample of 272 adolescents. A subsequent sample of Canadian (N = 104) and New Zealand (N = 29) adolescents, was recruited in study 2 to explore the scale's predictive validity using a subjective measure of leisure- and school-time physical activity. Results: A principle axis factor analysis in study 1 revealed a 26-item, five-factor coherent and interpretable solution; representative of leisure and recreation, household, ambulatory, transportation, and school physical activity efficacy constructs, respectively. The five-factor solution explained 81% of the response variance. In study 2 the domain-specific efficacy model explained 16% and 1% of leisure- and school-time physical activity response variance, respectively, with leisure time physical activity efficacy identified as a unique and significant contributor of leisure-time physical activity. Conclusion: Study 1 provides evidence for the tenability of a five factor DSPEAQ, while study 2 shows that the DSPEAQ has utility in predicting domain-specific physical activity. This latter finding underscores the importance of scale correspondence between the behavioural elements (leisure-time physical activity) and cognitive assessment of those elements (leisure-time physical activity efficacy).

Finding line of action of the force exerted on erect spine based on lateral bending test in personalization of scoliotic spine models

In multi-body models of scoliotic spine, personalization of mechanical properties of joints significantly improves reconstruction of the spine shape. In personalization methods based on lateral bending test, simulation of bending positions is an essential step. To simulate, a force is exerted on the spine model in the erect position. The line of action of the force affects the moment of the force about the joints and thus, if not correctly identified, causes over/underestimation of mechanical properties. Therefore, we aimed to identify the line of action, which has got little attention in previous studies. An in-depth analysis was performed on the scoliotic spine movement from the erect to four spine positions in the frontal plane by using pre-operative X-rays of 18 adolescent idiopathic scoliosis (AIS) patients. To study the movement, the spine curvature was considered as a 2D chain of micro-scale motion segments (MMSs) comprising rigid links and 1-degree-of-freedom (DOF) rotary joints. It was found that two MMSs representing the inflection points of the erect spine had almost no rotation (0.0028° ± 0.0021°) in the movement. The small rotation can be justified by weak moment of the force about these MMSs due to very small moment arm. Therefore, in the frontal plane, the line of action of the force to simulate the left/right bending position was defined as the line that passes through these MMSs in the left/right bending position. Through personalization of a 3D spine model for our patients, we demonstrated that our line of action could result in good estimates of the spine shape in the bending positions and other positions not included in the personalization, supporting our proposed line of action.

Architectural information

Through a study of architectural information as a complex system, a theoretical model relating critical information elements and project knowledge is proposed. The Project Specific Information model articulates distinct information integrities (intellectual, contextual, structural and spatial) that support the knowledge-based decision-making processes controlling information quality in architectural projects.

Physical activity among cancer survivors : a literature review

Aim Physical activity offers a variety of health benefits to cancer survivors, both during and post-treatment. The aim here is to review: the preferences of cancer survivors regarding exercise counselling and participation in a physical activity programme; adherence rates among cancer survivors to physical activity programmes; and predictors of adherence to exercise training.

Methods Two electronic databases, Ovid MEDLINE(R) 1950 to Present with Daily Update and SCOPUS, were used to undertake literature searches for studies examining exercise preferences of adult cancer survivors, and physical activity programmes for adults at any point of the cancer trajectory.

Results Studies suggest that, while physical activity levels are low among cancer survivors, most are interested in increasing their participation. Preferences and adherence to physical activity programmes differ across a range of demographic, medical, and behavioural variables, suggesting the importance of tailoring exercise programmes to patient-specific and disease-specific needs.

Conclusions Current evidence supports the benefits of physical activity for improving risk factors associated with cancer prognosis. Physical activity programmes developed for oncology patients and cancer survivors need to take into account the needs of the target population in order to optimise adherence, outcomes, and long-term behavioural changes in this population.

Comparison of not for resuscitation (NFR) forms across five Victorian health services

Background: 

Validation of DNA methylation biomarkers for diagnosis of acute lymphoblastic leukemia

DNA methylation biomarkers capable of diagnosis and subtyping have been found for many cancers. Fifteen such markers have previously been identified for pediatric acute lymphoblastic leukemia (ALL). Validation of these markers is necessary to assess their clinical utility for molecular diagnostics. Substantial efficiencies could be achieved with these DNA methylation markers for disease tracking with potential to replace patient-specific genetic testing.

Simplifying medical additive manufacturing: making the surgeon the designer

Additive Manufacturing, a technology which has been in existence since three decades, is now successfully being transitioned from a research setting to finding technologically and financially viable end-user applications. A key sector in which Additive Manufacturing is being used is the medical devices and healthcare sector. Drivers in this sector include the ability to create customized, patient specific devices and implants with quick turnaround time in a cost-effective manner. Doctors and surgeons are important change agents and innovators in the creation of new healthcare devices as well as surgical methods. Often times, they may find it necessary at first to build devices and plan surgeries which are not even being thought of or acted upon by the major healthcare companies. In this sense, they perform the roles of designers, creating new ideas and improving on them until they can be implemented and adopted by others. However, the scope for performing this creative activity is often limited in their workplaces, with resource, time and financial impediments often being present. Additive Manufacturing can be helpful to speed up the iterative process of designing such medical devices or planning surgeries as well as help convince people outside of the surgery room of the feasibility and business case for such innovations. This paper proposes to introduce a framework of design, processes and tools which will enable non-engineers (specifically surgeons) to create custom-built products. It is hoped that this paper will motivate more surgeons and non-engineers to get involved in the process of designing for additive manufacturing.