Virtual reality versus conventional clinical role-play for radiographic positioning training: A students' perception study.

INTRODUCTION: Simulated learning environments (SLEs) are commonly utilised by educational institutions. The aim of this study was to assess if students perceptions varied relating to the effectiveness of either a virtual reality (VR) simulation or traditional clinical role-play scenario in developing radiographic hand positioning skills. METHODS: A split-cohort study was performed with Year 1 Undergraduate Radiography students (n = 76). Students were randomly assigned to undertake training for radiographic hand positioning tasks using either the CETSOL VR Clinic software (Group 1) or traditional clinical role-play (Group 2). Following completion of their positioning training, students' perceived impact of the SLE on developing practical and technical skills were assessed using a 5-point Likert scale questionnaire and free text option. RESULTS: Quantitative student perception scores indicated no significant difference between the two simulation modalities, the mean agreement scores (combined strongly agree + agree) for Groups 1 and 2 were 74.8% and 83.8%, respectively, where χ2 (4, n = 66) = 9.5, p-value = 0.394. Key themes expressed by students following a thematic analysis were "engagement with the learning environment, positioning practice and comparability to clinical practice. CONCLUSION: The perceptions of novice students in training for radiographic hand positioning tasks, using either a VR SLE or clinical role-play scenario, did not differ. There was a strong similarity in common themes, however, a key point of difference identified was the benefit of repetition afforded by the VR simulation, in contrast to the need for more time using traditional role-play in a constrained laboratory setting. IMPLICATIONS FOR PRACTICE: The lack of difference in student perceptions between VR and clinical role-play training, could offer a different approach to clinical training which is easily accessible and allows users to correct mistakes at their own pace.

Semi-supervised labelling of the femur in a whole-body post-mortem CT database using deep learning.

A deep learning pipeline was developed and used to localize and classify a variety of implants in the femur contained in whole-body post-mortem computed tomography (PMCT) scans. The results provide a proof-of-principle approach for labelling content not described in medical/autopsy reports. The pipeline, which incorporated residual networks and an autoencoder, was trained and tested using n = 450 full-body PMCT scans. For the localization component, Dice scores of 0.99, 0.96, and 0.98 and mean absolute errors of 3.2, 7.1, and 4.2 mm were obtained in the axial, coronal, and sagittal views, respectively. A regression analysis found the orientation of the implant to the scanner axis and also the relative positioning of extremities to be statistically significant factors. For the classification component, test cases were properly labelled as nail (N+), hip replacement (H+), knee replacement (K+) or without-implant (I-) with an accuracy >97%. The recall for I- and H+ cases was 1.00, but fell to 0.82 and 0.65 for cases with K+ and N+. This semi-automatic approach provides a generalized structure for image-based labelling of features, without requiring time-consuming segmentation.

Identification of excited states in the T(z) = 1 nucleus (110)Xe: evidence for enhanced collectivity near the N=Z=50 double shell closure.

Gamma-ray transitions have been identified for the first time in the extremely neutron-deficient (N=Z+2) nucleus (110)Xe, and the energies of the three lowest excited states in the ground-state band have been deduced. The results establish a breaking of the normal trend of increasing first excited 2(+) and 4(+) level energies as a function of the decreasing neutron number as the N=50 major shell gap is approached for the neutron-deficient Xe isotopes. This unusual feature is suggested to be an effect of enhanced collectivity, possibly arising from isoscalar n-p interactions becoming increasingly important close to the N=Z line.