Abstract：
Medical Extended Reality (MXR), encompassing augmented reality (AR), virtual reality (VR), and mixed reality (MR), presents a novel paradigm in radiology training by offering immersive, interactive, and realistic learning experiences in healthcare. While traditional educational tools in the field of radiology are essential, it is necessary to capitalize on the innovative and emerging educational applications of XR technologies. At the most basic level of learning anatomy, XR has been extensively utilized with an emphasis on its superiority over conventional learning methods, especially in spatial understanding and recall. For imaging interpretation, XR has fostered the concepts of virtual reading rooms by enabling collaborative learning environments and enhancing image analysis and understanding. Moreover, image-guided interventions in interventional radiology have witnessed an uptick in XR utilization, illustrating its effectiveness in procedural training and skill acquisition for medical students and residents in a safe and risk-free environment. However, there remain several challenges and limitations for XR in radiology education, including technological, economic, ergonomic, and integration into existing curricula. This review explores the transformative potential of MXR in radiology education and training along with insights on the future of XR in radiology education, forecasting advancements in immersive simulations, AI integration for personalized learning, and the potential of cloud-based XR platforms for remote and collaborative training. In summation, MXR\'s burgeoning role in reshaping radiology education offers a safer, scalable, and more efficient training model that aligns with the dynamic healthcare landscape.
摘要：
医学扩展现实（MXR）包括增强现实(AR)，虚拟现实(VR)和混合现实（MR），通过提供身临其境的放射学培训，提出了一种新的范式，互动式,和医疗保健方面的现实学习经验。虽然放射学领域的传统教育工具是必不可少的，有必要利用XR技术的创新和新兴教育应用。在学习解剖学的最基本水平上，XR已被广泛使用，强调其优于传统学习方法，特别是在空间理解和回忆方面。对于成像解释，XR通过启用协作学习环境并增强图像分析和理解，促进了虚拟阅览室的概念。此外，介入放射学中的图像引导干预见证了XR利用率的上升，说明其在安全和无风险环境中为医学生和居民提供程序培训和技能获取的有效性。然而,XR在放射学教育中仍然存在一些挑战和局限性，包括技术,经济,符合人体工程学,并融入现有课程。这篇综述探讨了MXR在放射学教育和培训中的变革潜力，以及对XR在放射学教育中的未来的见解。预测沉浸式模拟的进步，用于个性化学习的AI集成，以及基于云的XR平台用于远程和协作培训的潜力。总之，MXR在重塑放射学教育方面的新兴作用提供了更安全的，可扩展，和更有效的培训模式，与动态的医疗保健格局保持一致。
