Background: Computer-assisted learning has been shown to be an effective means of teaching anatomy, with 3-D visualization technology more successfully improving participants' factual and spatial knowledge in comparison to traditional methods. To date, however, the effectiveness of teaching ear anatomy using 3-D holographic technology has not been studied. The present study aimed to evaluate the feasibility and effectiveness of learning ear anatomy using a holographic (HG) anatomic model in comparison to didactic lecture (DL) and a computer module (CM). Methods: A 3-D anatomic model of the middle and inner ear was created and displayed using presentation slides in a lecture, computer module, or via the Microsoft HoloLens. Twenty-nine medical students were randomized to one of the three interventions. All participants underwent assessment of baseline knowledge of ear anatomy. Immediately following each intervention, testing was repeated along with completion of a satisfaction survey. Results: Baseline test scores did not differ across intervention groups. All groups showed an improvement in anatomic knowledge post-intervention (p < 0.001); the improvement was equal across all interventions (p = 0.06). Participants rated the interventions equally for delivery of factual content (p = 0.96), but rated the HG higher than the DL and CM for overall effectiveness, ability to convey spatial relationships, and for learner engagement and motivation (p < 0.001). Conclusions: These results suggest that 3-D holographic technology is an effective method of teaching ear anatomy as compared to DLs and CMs. Furthermore, it is better at engaging and motivating learners compared to traditional methods, meriting its inclusion as a tool in undergraduate medical education curriculum.

Birth ball exercise could be an alternative means of relieving back pain and labour pain in the labour ward, and could decrease pethidine consumption in labouring women.

Background: Planning radiosurgery to multiple intracranial metastases is complex and shows large variability in dosimetric quality among planners and treatment planning systems (TPS). This project aimed to determine whether autoplanning using the Muliple Brain Mets (AutoMBM) software can improve plan quality and reduce inter-planner variability by crowdsourcing results from prior international planning study. Methods: Twenty-four institutions autoplanned with AutoMBM on a five metastases case from a prior international planning competition from which population statistics (means and variances) of 23 dosimetric metrics and resulting composite plan score (maximum score = 150) of other TPS (Eclipse, Monaco, RayStation, iPlan, GammaPlan, MultiPlan) were crowdsourced. Plan results of AutoMBM and each of the other TPS were compared using two sample t-tests for means and Levene's tests for variances. Plan quality of AutoMBM was correlated with the planner' experience and compared between academic and non-academic centers. Results: AutoMBM produced plans with comparable composite plan score to GammaPlan, MultiPlan, Eclipse and iPlan (127.6 vs. 131.7 vs. 127.3 vs. 127.3 and 126.7; all p > 0.05) and superior to Monaco and RayStation (118.3 and 108.6; both p < 0.05). Inter-planner variability of overall plan quality was lowest for AutoMBM among all TPS (all p < 0.05). AutoMBM's plan quality did not differ between academic and non-academic centers and uncorrelated with planning experience (all p > 0.05).

No abstract

No abstract