Virtual reality in interventional radiology education: a systematic review

The Virtual Reality Radiology Workstation: Current Technology and Future Applications

Virtual reality (VR) and augmented reality (AR) technology hold potential across many disciplines in medicine to expand the delivery of education and healthcare. VR-AR applications in radiology, in particular, have gained prominence and have demonstrated advantages in many areas within the field. Recently, VR software has emerged to redesign the physical radiology workstation (ie, reading room) to expand the possibilities of diagnostic interpretation. Given the novelty of this technology, there is limited research investigating the potential applications of a simulated radiology workstation. In this review article, we explore VR-simulated reading room technology in its current form and illustrate the practical applications this technology will bring to future radiologists and learners. We also discuss the limitations and barriers to adopting this technology that must be overcome to truly understand its potential benefits. VR reading room technology offers great potential in radiology, but further research is needed to appreciate its benefits and identify areas for improvement. The findings and insights presented in this review contribute to the ongoing discourse on future technological advancements in radiology and healthcare, offering valuable recommendations for further research and practical implementation.

Mixed reality in interventional radiology: a focus on first clinical use of XR90 augmented reality-based visualization and navigation platform

INTRODUCTION

Augmented reality (AR) and virtual reality (VR) are emerging tools in interventional radiology (IR), enhancing IR education, preprocedural planning, and intraprocedural guidance.

AREAS COVERED

This review identifies current applications of AR/VR in IR, with a focus on studies that assess the clinical impact of AR/VR. We outline the relevant technology and assess current limitations and future directions in this space. We found that the use of AR in IR lags other surgical fields, and the majority of the data exists in case series or small-scale studies. Educational use of AR/VR improves learning anatomy, procedure steps, and procedural learning curves. Preprocedural use of AR/VR decreases procedure times, especially in complex procedures. Intraprocedural AR for live tracking is accurate within 5 mm live patients and has up to 0.75 mm in phantoms, offering decreased procedure time and radiation exposure. Challenges include cost, ergonomics, rapid segmentation, and organ motion.

EXPERT OPINION

The use of AR/VR in interventional radiology may lead to safer and more efficient procedures. However, more data from larger studies is needed to better understand where AR/VR is confers the most benefit in interventional radiology clinical practice.

Reviewing the current state of virtual reality integration in medical education - a scoping review

BACKGROUND

In medical education, new technologies like Virtual Reality (VR) are increasingly integrated to enhance digital learning. Originally used to train surgical procedures, now use cases also cover emergency scenarios and non-technical skills like clinical decision-making. This scoping review aims to provide an overview of VR in medical education, including requirements, advantages, disadvantages, as well as evaluation methods and respective study results to establish a foundation for future VR integration into medical curricula.

METHODS

This review follows the updated JBI methodology for scoping reviews and adheres to the respective PRISMA extension. We included reviews in English or German language from 2012 to March 2022 that examine the use of VR in education for medical and nursing students, registered nurses, and qualified physicians. Data extraction focused on medical specialties, subjects, curricula, technical/didactic requirements, evaluation methods and study outcomes as well as advantages and disadvantages of VR.

RESULTS

A total of 763 records were identified. After eligibility assessment, 69 studies were included. Nearly half of them were published between 2021 and 2022, predominantly from high-income countries. Most reviews focused on surgical training in laparoscopic and minimally invasive procedures (43.5%) and included studies with qualified physicians as participants (43.5%). Technical, didactic and organisational requirements were highlighted and evaluations covering performance time and quality, skills acquisition and validity, often showed positive outcomes. Accessibility, repeatability, cost-effectiveness, and improved skill development were reported as advantages, while financial challenges, technical limitations, lack of scientific evidence, and potential user discomfort were cited as disadvantages.

DISCUSSION

Despite a high potential of VR in medical education, there are mandatory requirements for its integration into medical curricula addressing challenges related to finances, technical limitations, and didactic aspects. The reported lack of standardised and validated guidelines for evaluating VR training must be overcome to enable high-quality evidence for VR usage in medical education. Interdisciplinary teams of software developers, AI experts, designers, medical didactics experts and end users are required to design useful VR courses. Technical issues and compromised realism can be mitigated by further technological advancements.

Large Language Models as Tools to Generate Radiology Board-Style Multiple-Choice Questions

RATIONALE AND OBJECTIVES

To determine the potential of large language models (LLMs) to be used as tools by radiology educators to create radiology board-style multiple choice questions (MCQs), answers, and rationales.

METHODS

Two LLMs (Llama 2 and GPT-4) were used to develop 104 MCQs based on the American Board of Radiology exam blueprint. Two board-certified radiologists assessed each MCQ using a 10-point Likert scale across five criteria-clarity, relevance, suitability for a board exam based on level of difficulty, quality of distractors, and adequacy of rationale. For comparison, MCQs from prior American College of Radiology (ACR) Diagnostic Radiology In-Training (DXIT) exams were also assessed using these criteria, with radiologists blinded to the question source.

RESULTS

Mean scores (±standard deviation) for clarity, relevance, suitability, quality of distractors, and adequacy of rationale were 8.7 (±1.4), 9.2 (±1.3), 9.0 (±1.2), 8.4 (±1.9), and 7.2 (±2.2), respectively, for Llama 2; 9.9 (±0.4), 9.9 (±0.5), 9.9 (±0.4), 9.8 (±0.5), and 9.9 (±0.3), respectively, for GPT-4; and 9.9 (±0.3), 9.9 (±0.2), 9.9 (±0.2), 9.9 (±0.4), and 9.8 (±0.6), respectively, for ACR DXIT items (p < 0.001 for Llama 2 vs. ACR DXIT across all criteria; no statistically significant difference for GPT-4 vs. ACR DXIT). The accuracy of model-generated answers was 69% for Llama 2 and 100% for GPT-4.

CONCLUSION

A state-of-the art LLM such as GPT-4 may be used to develop radiology board-style MCQs and rationales to enhance exam preparation materials and expand exam banks, and may allow radiology educators to further use MCQs as teaching and learning tools.

Virtual reality experiential learning improved undergraduate students' knowledge and evaluation skills relating to assistive technology for older adults and individuals with disabilities

BACKGROUND

The aging population has caused assistive technology (AT) to receive attention. Thus, ensuring accurate user comprehension of AT has become increasingly crucial, and more specialized education for students in relevant fields is necessary. The goal of this study was to explore the learning outcomes in the context of AT for older adults and individuals with disabilities through the use of VR experiential learning.

METHODS

A parallel-group design was used. Sixty third-year university students studying gerontology and long-term-care-related subjects in Taiwan were enrolled, with the experimental (VR) and control (two-dimensional [2D] video) groups each comprising 30 participants. Both groups received the same 15-minute lecture. Subsequently, the experimental group received experiential learning through a VR intervention, whereas the control group watched a 2D video to learn. The students' knowledge of AT was assessed using a pretest and posttest. Additionally, their skills in evaluation of residential environments were assessed using the Residential Environment Assessment (REA) Form for Older Adults. All data analyses were performed with SPSS version 22.

RESULTS

In the posttest conducted after the intervention, the experimental group exhibited a significant 20.67 point improvement (p < 0.05), whereas the control group only exhibited improvement of 3.67 points (p = 0.317). Furthermore, the experimental group demonstrated a significantly higher score (+ 2.17 points) on the REA Form for Older Adults than did the control group (p < 0.05).

CONCLUSION

VR experiential learning can significantly improve undergraduate students' knowledge and evaluation skills in relation to AT for older adults and individuals with disabilities.

Undergraduate radiodiagnostic professors

The international literature on university teaching, has insisted on the need to combine a double component in the professional profile of teachers: content knowledge and pedagogical content knowledge. Regarding the content, the area of knowledge of radiology and physical medicine is made up of different medical specialties, among which are radiodiagnosis, nuclear medicine, radiation oncology, physical medicine and rehabilitation. On the other hand, the pedagogical content knowledge is framed by framework that the Bologna Declaration (1999). Focusing on radiodiagnosis, the ideal candidates must be professionals in this medical specialty, vocational teachers and people who find in the undergraduate teaching process an opportunity to transmit their knowledge, experiences and values in an entertaining and understandable way for students who are incorporated into medical knowledge.

Imaging in interventional oncology, the better you see, the better you treat

Imaging and image processing is the fundamental pillar of interventional oncology in which diagnostic, procedure planning, treatment and follow-up are sustained. Knowing all the possibilities that the different image modalities can offer is capital to select the most appropriate and accurate guidance for interventional procedures. Despite there is a wide variability in physicians preferences and availability of the different image modalities to guide interventional procedures, it is important to recognize the advantages and limitations for each of them. In this review, we aim to provide an overview of the most frequently used image guidance modalities for interventional procedures and its typical and future applications including angiography, computed tomography (CT) and spectral CT, magnetic resonance imaging, Ultrasound and the use of hybrid systems. Finally, we resume the possible role of artificial intelligence related to image in patient selection, treatment and follow-up.

Exposure to, understanding of and interest in interventional radiology among Pakistani medical students: a cross-sectional study

Background

Medical students need more awareness regarding minimally invasive image-guided procedures carried out by interventional radiological approach. This study analyzed the knowledge and attitudes of medical students regarding interventional radiology (IR) and the factors influencing their decision to choose IR as a specialty in the future.

Methods

A cross-sectional, web-based study was conducted among medical students across Pakistan. The data were collected from October 14, 2021, to November 14, 2021. The questionnaire included demographic variables, exposure, interest, and self-reported knowledge of IR, interventions, instruments utilized in IR, and the responsibilities of the interventional radiologist. Variables affecting the possible choice of IR as a future career were analyzed using logistic regression analysis.

Results

The median age was 22 years, with a male predominance. 65.5% exhibited an interest in radiology, and 20.2% in IR. The majority, 83.5%, perceived IR. As having good to adequate prospects. Male participants preferred IR more as compared to females. Participants willing to attend IR rotation and had an excellent view of IR as a specialty had higher propensity towards IR as a future career than their counterparts. The majority opted for IR as a better-paying job with lots of intellectual stimulation and career flexibility.

Conclusion

IR is a demanding specialty with rigorous routines but reasonable monetary compensation. Lack of infrastructure and low numbers of trained specialists limit medical students' exposure to IR in developing health economies like Pakistan. Clinical rotations in IR departments would help raise awareness about the field and bridging this gap.

The digital future of nursing: making sense of taxonomies and key concepts

Digital technology is becoming increasingly common in routine nursing practice. The adoption of digital technologies such as video calling, and other digital communication, has been hastened by the recent COVID-19 pandemic. Use of these technologies has the potential to revolutionise nursing practice, leading to potentially more accurate patient assessment, monitoring processes and improved safety in clinical areas. This article outlines key concepts related to the digitalisation of health care and the implications for nursing practice. The aim of this article is to encourage nurses to consider the implications, opportunities and challenges associated with the move towards digitalisation and advances in technology. Specifically, this means understanding key digital developments and innovations associated with healthcare provision and appreciating the implications of digitalisation for the future of nursing practice.

Artificial Intelligence, Augmented Reality, and Virtual Reality Advances and Applications in Interventional Radiology

Artificial intelligence (AI) uses computer algorithms to process and interpret data as well as perform tasks, while continuously redefining itself. Machine learning, a subset of AI, is based on reverse training in which evaluation and extraction of data occur from exposure to labeled examples. AI is capable of using neural networks to extract more complex, high-level data, even from unlabeled data sets, and better emulate, or even exceed, the human brain. Advances in AI have and will continue to revolutionize medicine, especially the field of radiology. Compared to the field of interventional radiology, AI innovations in the field of diagnostic radiology are more widely understood and used, although still with significant potential and growth on the horizon. Additionally, AI is closely related and often incorporated into the technology and programming of augmented reality, virtual reality, and radiogenomic innovations which have the potential to enhance the efficiency and accuracy of radiological diagnoses and treatment planning. There are many barriers that limit the applications of artificial intelligence applications into the clinical practice and dynamic procedures of interventional radiology. Despite these barriers to implementation, artificial intelligence in IR continues to advance and the continued development of machine learning and deep learning places interventional radiology in a unique position for exponential growth. This review describes the current and possible future applications of artificial intelligence, radiogenomics, and augmented and virtual reality in interventional radiology while also describing the challenges and limitations that must be addressed before these applications can be fully implemented into common clinical practice.

The objective structured clinical examination (OSCE): Main aspects and the role of imaging

The objective structured clinical examination (OSCE) is a format of examination that enables students to be evaluated in a uniform, standardized, reliable, and objective way. It is carried out in different clinical stations that simulate real clinical situations and scenarios. Numerous universities in Spain and other countries employ this approach for the final examination for medical school students. This update describes the organization, design, and fundamentals for the OSCE, proposing that radiology should form part of multidisciplinary OSCEs to the extent that it forms part of clinical practice. Moreover, it is interesting and opportune to introduce the OSCE in undergraduate and postgraduate training in radiology. Online platforms enable bidimensional OSCEs that are cost-effective in terms of staff, resources, and physical space, although this approach has certain limitations. Virtual world technologies make it possible to reproduce OSCE stations in three-dimensional scenarios; recent experiences in radiology have shown that this approach interests and motivates students and is widely accepted by them.

Augmented reality in interventional radiology education: a systematic review of randomized controlled trials

BACKGROUND

Augmented reality (AR) involves digitally overlapping virtual objects onto physical objects in real space so that individuals can interact with both at the same time. AR in medical education seeks to reduce surgical complications through high-quality education. There is uncertainty in the use of AR as a learning tool for interventional radiology procedures.

OBJECTIVE

To compare AR with other learning methods in interventional radiology.

DESIGN AND SETTING

Systematic review of comparative studies on teaching techniques.

METHODS

We searched the Cochrane Library, MEDLINE, Embase, Tripdatabase, ERIC, CINAHL, SciELO and LILACS electronic databases for studies comparing AR simulation with other teaching methods in interventional radiology. This systematic review was performed in accordance with PRISMA and the BEME Collaboration. Eligible studies were evaluated using the quality indicators provided in the BEME Collaboration Guide no. 11, and the Kirkpatrick model.

RESULTS

Four randomized clinical trials were included in this review. The level of educational evidence found among all the papers was 2B, according to the Kirkpatrick model. The Cochrane Collaboration tool was applied to assess the risk of bias for individual studies and across studies. Three studies showed an improvement in teaching of the proposed procedure through AR; one study showed that the participants took longer to perform the procedure through AR.

CONCLUSION

AR, as a complementary teaching tool, can provide learners with additional skills, but there is still a lack of studies with a higher evidence level according to the Kirkpatrick model.

SYSTEMATIC REVIEW REGISTRATION NUMBER

DOI 10.17605/OSF.IO/ACZBM in the Open Science Framework database.

The Role of Three-Dimensional Reconstruction of Medical Images and Virtual Reality in Nursing Experimental Teaching

With the continuous advancement of medicine and computer science, medical image processing technology is also constantly advancing, and at the same time, it puts forward the needs of its own development. The purpose of this article is to combine the three-dimensional reconstruction of medical images and virtual reality (VR) technology in nursing experiment teaching to help students understand more easily and to simplify the teachers' teaching process and make the VR application technology. It is the most popular and effective in medical teaching. This article proposes the C-V model and the geometric active contour model to help us more clearly understand the pathology in this environment, where the specific symptoms appear, and bring a more easy-to-understand model for teaching and improving teaching quality. This article also designs nursing experiment teaching. The experimental results of this paper show that, after using VR courseware for teaching, the optimal test rate of the experimental class is 15% higher than that of the control class, and the transition rate is 8%. The actual test excellent rate and success rate of the experimental class are much higher than those of the control class. Therefore, it can be concluded that the application of VR technology in nursing teaching helps teachers improve their practical ability. The excellent teaching feedback rate is 95%, which is higher than 80.5% in the control group, indicating that the patient teaching simulation is approved by the observation group. The program can effectively improve the feedback rate of excellent teaching and provide students with better teaching services.