In vivo positive contrast IRON sequence and quantitative T2* measurement confirms inflammatory burden in a patient with asymptomatic carotid atheroma after USPIO-enhanced MR Imaging

The authors report an in vivo human examination of carotid atheroma by using the inversion-recovery ON resonance (IRON) sequence, which is able to produce positive contrast after the infusion of an ultrasmall super paramagnetic iron oxide (USPIO) contrast medium. This technique provides a method of potentially identifying inflammatory burden within carotid atheroma. This may be particularly useful in patients who currently do not meet criteria for intervention (ie, moderate symptomatic stenosis or <70% asymptomatic stenosis) to further risk-stratify this important patient cohort. A 63-year-old man was imaged at 1.5 T before and 36 hours after USPIO infusion by using the IRON sequence. Regions of interest showing profound signal loss at T2*-weighted imaging corresponded well with regions of positive contrast at IRON imaging after the administration of USPIO. These regions also showed a profound decrease in T2* measurements after USPIO infusion, whereas surrounding tissue did not. It has been shown that such strong signal loss on T2*-weighted images after USPIO infusion is indicative of USPIO uptake.

Structural analysis and magnetic resonance imaging predict plaque vulnerability: A study comparing symptomatic and asymptomatic individuals

Background: More than half of all cerebral ischemic events are the result of rupture of extracranial plaques. The clinical determination of carotid plaque vulnerability is currently based solely on luminal stenosis; however, it has been increasingly suggested that plaque morphology and biomechanical stress should also be considered. We used finite element analysis based on in vivo magnetic resonance imaging (MRI) to simulate the stress distributions within plaques of asymptomatic and symptomatic individuals. Methods: Thirty nonconsecutive subjects (15 symptomatic and 15 asymptomatic) underwent high-resolution multisequence in vivo MRI of the carotid bifurcation. Stress analysis was performed based on the geometry derived from in vivo MRI of the carotid artery at the point of maximal stenosis. The finite element analysis model considered plaque components to be hyperelastic. The peak stresses within the plaques of symptomatic and asymptomatic individuals were compared. Results: High stress concentrations were found at the shoulder regions of symptomatic plaques, and the maximal stresses predicted in this group were significantly higher than those in the asymptomatic group (508.2 ± 193.1 vs 269.6 ± 107.9 kPa; P = .004). Conclusions: Maximal predicted plaque stresses in symptomatic patients were higher than those predicted in asymptomatic patients by finite element analysis, suggesting the possibility that plaques with higher stresses may be more prone to be symptomatic and rupture. If further validated by large-scale longitudinal studies, biomechanical stress analysis based on high resolution in vivo MRI could potentially act as a useful tool for risk assessment of carotid atheroma. It may help in the identification of patients with asymptomatic carotid atheroma at greatest risk of developing symptoms or mild-to-moderate symptomatic stenoses, which currently fall outside current clinical guidelines for intervention.

Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

Blended learning in medical imaging pre-clinical skills training – does it work?

Undergraduate Medical Imaging (MI)students at QUT attend their first clinical placement towards the end of semester two. Students undertake two (pre)clinical skills development units – one theory and one practical. Students gain good contextual and theoretical knowledge during these units via a blended learning model with multiple learning methods employed. Students attend theory lectures, practical sessions, tutorial sessions in both a simulated and virtual environment and also attend pre-clinical scenario based tutorial sessions. The aim of this project is to evaluate the use of blended learning in the context of 1st year Medical Imaging Radiographic Technique and its effectiveness in preparing students for their first clinical experience. It is hoped that the multiple teaching methods employed within the pre-clinical training unit at QUT builds students clinical skills prior to the real situation. A quantitative approach will be taken, evaluating via pre and post clinical placement surveys. This data will be correlated with data gained in the previous year on the effectiveness of this training approach prior to clinical placement. In 2014 59 students were surveyed prior to their clinical placement demonstrated positive benefits of using a variety of learning tools to enhance their learning. 98.31%(n=58)of students agreed or strongly agreed that the theory lectures were a useful tool to enhance their learning. This was followed closely by 97% (n=57) of the students realising the value of performing role-play simulation prior to clinical placement. Tutorial engagement was considered useful for 93.22% (n=55) whilst 88.14% (n=52) reasoned that the x-raying of phantoms in the simulated radiographic laboratory was beneficial. Self-directed learning yielded 86.44% (n=51). The virtual reality simulation software was valuable for 72.41% (n=42) of the students. Of the 4 students that disagreed or strongly disagreed with the usefulness of any tool they strongly agreed to the usefulness of a minimum of one other learning tool. The impact of the blended learning model to meet diverse student needs continues to be positive with students engaging in most offerings. Students largely prefer pre -clinical scenario based practical and tutorial sessions where 'real-world’ situations are discussed.

A Petrov-Galerkin method for a singularly perturbed ordinary differential equation with non-smooth data

In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.