From education to research: A journey of utilising virtual training

© 2015 Cambridge University Press.Background London South Bank University (LSBU) has successfully implemented Virtual Environment for Radiotherapy Training (VERT) across the therapeutic radiography training curricula and are now supporting the use of VERT for patient education in clinical departments. A number of publications have reported on the use of VERT in education and training; more recent literature has focused on the use of VERT for patient education. Materials and methods The successful introduction of VERT before students' first clinical placements resulted in the development of a 'Pre-Clinical week' where students practice and improve their technical skills, using the hand controls without a patient present, leading to increased confidence in clinical practice. Other examples of VERT curriculum integration at LSBU focused on the use of VERT for anatomy teaching. The more recent innovation at LSBU relevant to VERT integration has been the design, development and implementation of collaborative research projects where the aims of the studies were to explore patients' perceptions of VERT as an information giving resource before radiotherapy delivery. Summary The introduction of VERT as education tool has enabled academic staff to develop a range of teaching methods to embed virtual training into the traditional classroom setting, demonstrating innovation and collaboration

Evaluating VERT as a radiotherapy plan evaluation tool: comparison with treatment planning software

AbstractIntroduction:The virtual environment for radiotherapy training (VERT) helps students to gain technical skills and understanding of 3D anatomy and dosimetry. It has potential as a tool for treatment plan evaluation, although little formal evidence currently supports this.Aim:This paper reports findings from a plan evaluation workshop that facilitated comparison of VERT plan evaluation tools with those provided by conventional treatment planning software (TPS).Method:Students on a pre-registration Post-Graduate Diploma in Radiotherapy worked in small groups evaluating lung plans using both VERT and Eclipse TPS tools. All students were invited to provide ratings concerning how helpful each modality was for a range of evaluation parameters and preferences for use.Results:Most students (11 out of 14) found the session useful and expressed a desire to use VERT in future plan evaluation. The TPS was perceived to be more helpful with constraint-based evaluation while VERT was more helpful with evaluating plans for clinical set-up and delivery (p &amp;lt; 0·001).Conclusion:Student therapeutic radiographers found VERT to be helpful as a plan evaluation tool alongside standard TPS tools, in particular for clinical set-up and delivery aspects of planning. Future work is ongoing to identify the specific impact of VERT as a plan evaluation tool for both students and qualified planners.</jats:sec

Grid-enabled treatment planning for proton therapy using monte carlo simulations

Grid computing is an emerging technology that enables computational tasks to be accomplished in a collaborative approach by using a distributed network of computers. The grid approach is especially important for computationally intensive problems that are not tractable with a single computer or even with a small cluster of computers, e.g., radiation transport calculations for cancer therapy. The objective of this work was to extend a Monte Carlo (MC) transport code used for proton radiotherapy to utilize grid computing techniques and demonstrate its promise in reducing runtime from days to minutes. As proof of concept we created the Medical Grid between Texas Tech University and Rice University. Preliminary computational experiments were carried out in the GEANT4 simulation environment for transport of 25 × 106 200 MeVprotons in a prostate cancer treatment plan. The simulation speedup was approximately linear; deviations were attributed to the spectrum of parallel runtimes and communication overhead due to Medical Grid computing. The results indicate that ∼3 × 105 to 5 ×105 proton events with processor core would result in 65 to 83% efficiency. Extrapolation of our results indicates that about 103 processor cores of the class used here would reduce the MC simulation runtime from 18.3 days to ∼1 h

The utilisation of virtual images in patient information giving sessions for prostate cancer patients prior to radiotherapy

© 2016 The College of RadiographersThe aim of the study was to explore the prostate patients' perceptions of a Virtual Environment for Radiotherapy Training (VERT) as an information giving resource prior to radiotherapy delivery. A survey design was used to determine the level of knowledge of those patients who attended VERT for a pre-treatment talk and identify the benefits and limitations of using VERT as pre-treatment information giving resource. Participants were invited to attend a VERT patient information session four weeks prior to their planning CT scan, and then complete a questionnaire two weeks after start of radiotherapy treatment. A sample of n = 38 patients were recruited over a five month data collection period. Results showed that patient perceptions on the use of VERT as information giving tool prior to radiotherapy treatment were very positive. The sessions enable patients to understand the potential impact of treatment volumes if the internal organ shape and location differed from that originally planned, enabling them to comply with radiotherapy treatment instructions. Additional key findings have demonstrated excellent levels of communication associated with the use of VERT emphasising the need for future patient preparation strategies to consider the use of virtual technology

Immersive Visualization for Enhanced Computational Fluid Dynamics Analysis

Modern biomedical computer simulations produce spatiotemporal results that are often viewed at a single point in time on standard 2D displays. An immersive visualization environment (IVE) with 3D stereoscopic capability can mitigate some shortcomings of 2D displays via improved depth cues and active movement to further appreciate the spatial localization of imaging data with temporal computational fluid dynamics (CFD) results. We present a semi-automatic workflow for the import, processing, rendering, and stereoscopic visualization of high resolution, patient-specific imaging data, and CFD results in an IVE. Versatility of the workflow is highlighted with current clinical sequelae known to be influenced by adverse hemodynamics to illustrate potential clinical utility