Extended Reality at Bedside: Point-of-Care Simulation for Learning Point-of-Care Ultrasound

Simulation-based education has transformed the training of healthcare professionals by enabling learners to develop clinical competence in a safe and controlled environment. Today, simulation-based learning entails a wide spectrum ranging from simple task trainers to high-fidelity manikins to the immersive environments of extended reality (XR). Each modality has sought to enhance learner engagement, facilitate skill acquisition, and ultimately improve patient care.¹ However, it is important to note that the simulation session does not depend solely on the degree of realism offered by a technology, but is also aligned with the intended learning outcomes.

Extended reality is the creation of a virtual environment as an extension of and in conjunction with our real environment, in a way that facilitates a seamless interaction with the components of this new digitally amalgamated environment. Extended reality includes virtual reality (VR), augmented reality (AR), and mixed reality (MR). Virtual reality involves complete immersion in a virtual environment of digitally generated 3D images; AR involves a digital overlay of virtual 3D images into the real environment. MR blends virtual and real images to create an environment in which the virtual image can interact with the real image, and the user can interact with the complete environment, thus generating a superior learning experience. The learning experience is highly dependent on the quality of interactions with the environment, which are based on visual, auditory, and haptic (touch) stimuli, with the latter adding to an enriched experience.²

Extended reality has been extensively explored in healthcare for learning anatomy, chest compressions, and procedures, especially surgical procedures, where it provides a stress-free, risk-free, and safe environment conducive for repetitive learning along with simultaneous team interactions promoting skill acquisition and retention.³

Training in echocardiography and point-of-care ultrasound (PoCUS) has traditionally involved instructor-led workshops, imparting instruction using healthy volunteers or patients. This approach has been aptly supported by the use of high-fidelity simulators located in the simulation lab. Both of these approaches require a designated time, place, instructor, a team of trainees, and technical support staff.

Synonymous with the evolution of high-quality, hand-held ultrasound machines from the traditional bulky ones, the development of XR provides a virtual learning environment based on a headset and controller, which can be used as an adjunct for learning echocardiography at any location, versus the traditional approach of using the high-fidelity simulators located in the simulation lab. This makes XR-based simulation affordable and accessible in any part of the world.⁴

Echocardiography and PoCUS training is another area which is evolving, and there is an increasing requirement to train professionals from specialties like critical care, emergency medicine, and anesthesiology in PoCUS.⁵ This demand stems from the integration of PoCUS into clinical decision-making algorithms across these specialties. Understanding anatomy, spatial orientation, image acquisition, and probe manipulation is the cornerstone of this training, rather than replicating every aspect of a clinical encounter.⁶

The number of POCUS courses is restricted by the availability of trained instructors, ultrasound machines, suitable locations, and in India, by the Pre-Conception and Pre-Natal Diagnostic Techniques (PC & PNDT) Act, which restricts the use of ultrasound machines to registered users in a hospital premises.

In this regard, XR technologies offer an appropriate combination of physical, functional, and psychological fidelity while maintaining flexibility and scalability.⁷ This is particularly relevant for echocardiography and PoCUS training, which have traditionally depended on instructor-led workshops, patient-based teaching, and high-fidelity simulators. While these approaches have been invaluable in helping learners develop psychomotor and image acquisition skills without compromising patient safety, they remain resource-intensive and are often difficult to scale. Extended reality-based solutions offer an exciting opportunity to address these challenges by making high-quality ultrasound education more accessible, flexible, and learner-centered.⁸

In this issue of the journal, Rajamani et al. put forth a pilot study exploring the feasibility, user experience, and the effect on total time to acquire a stipulated number of actual echocardiographic images of novice critical care trainees, while using an ultraportable, MR simulator as an adjunct in echocardiography training.⁹

In their parallel group feasibility study, 14 novice trainees received a standalone 45-minute interactive session on how to create a two-dimensional ultrasound image of the heart facilitated by the dissection of a clay model of the heart, followed by a lecture on ideal echocardiographic windows. They were then split into two groups of seven trainees each; the first group scanned an intensive care unit patient, followed by a second intensive care unit patient. The second group first scanned using the MR simulator, followed by scanning the same second intensive care unit patient as used by the first group. The first group of trainees thereafter used the simulator, and all fourteen trainees provided feedback on the simulator. A single, unblinded experienced echocardiography educator validated the quality of images using the predefined criteria from the Learning Ultrasound in Critical Care (LUCC) consensus statement for all four scans.¹⁰

The authors are innovative in building an ultraportable MR simulator. The MR simulator comprises a head-mounted display (HMD), a 3D printed probe, and a thoracic manikin, which dispels the requirement of using a computer or an ultrasound machine. The 3D printed probe simulates a real ultrasound probe, while the thoracic manikin provides the haptic experience of a real patient interaction. The simulator has echocardiographic training modules with digital overlays of internal anatomy and ultrasound beam, facilitating the understanding of probe position, beam orientation, and image output, in an effort to improve spatial orientation and psychomotor skills. There is also provision for immediate feedback, in-built guidance, self-assessment tools, along with echocardiography lectures and pathology modules. All these features are designed to provide a degree of autonomy for the trainee while reducing the demand for constant supervision. The authors did not assess the impact of these latter additional features in the current study.

The study demonstrated the operational feasibility and positive feedback of using the MR simulator. They studied the feasibility of the device in a small number of critical care trainees. The results are encouraging, with short boot-up and handover times making the teaching session more efficient for a larger number of learners. The feedback provided by trainees, including the image quality, suggests satisfaction with the simulator. The feedback, however, is subjective and not measured objectively on a psychometric survey tool like the Likert scale, which converts qualitative training experiences into quantitative data to evaluate the effectiveness and validity of a simulation curriculum.¹¹ The feedback is also limited by the fact that the authors did not explore all the teaching features of the simulator in this study.

The impact of echocardiography training using a simulator is objectively assessed using pre- and post-intervention matrices either in a randomized controlled trial or in paired testing, by simulator-generated technical analysis, by using blinded objective structured assessments, and last but most importantly, by assessing the long-term retention of skills by the human transfer test or longitudinal decay testing. The authors should ideally assess the same in long-term follow-up studies for better validation of the impact of the simulator.

The authors also demonstrated a statistically significant difference in the time to acquire all acceptable echocardiographic windows in favor of the group that initially scanned on the MR simulator as compared to the group that scanned on the patient. The statistical significance and the effect size measure, suggesting a large effect, are undermined by the small sample size of fourteen trainees and two patients.

A more appropriate goal would have been to compare the learning efficiency of both groups by the Objective Structured Assessment of Ultrasound Skills (OSAUS) tool as exemplified by Anderson et al., in their randomized controlled trial comparing the learning efficacy of a traditional instructor-led lesson with a complete virtual self-directed lesson using VR in teaching basic POCUS skills. They found both instructor-led and VR-based lessons to be of comparable learning efficacy.¹² Todsen et al. have demonstrated the high reliability as well as evidence of construct validity of the OSAUS scale for assessment of competence in POCUS. Hence, the OSAUS scale may be suitable for both in-training as well as end-of-training assessment for POCUS.¹³ The long-term retention of these skills also needs to be explored.

The challenges of this simulator included the inability to use the headset with spectacles, short battery life, and the need to troubleshoot alignment between the cardiothoracic anatomy and the thoracic manikin.

There are several advantages of MR-based immersive technology over VR and AR. Mixed reality provides a complete sense of awareness of one's real environment as the headset glasses are transparent. This provides a medium-high immersive environment with real-world visibility as compared to VR. The digital images align in correct proportion, location, and depth with the subject's real environment, permitting a complete physical interaction between the user and their environment, which enhances the learning experience.² The best effect in echocardiography training is in 3D anatomy teaching and guided hands-on learning. The cost is lower compared to a high-fidelity simulator.

In VR, the trainee is placed in a fully simulated environment with no view of the real world, thus providing a complete immersive environment, disconnecting the user from reality, as the headset glasses are opaque. This can reduce distractions but increase the sense of isolation and can result in symptoms of giddiness and motion sickness. Too much data presented in VR can result in cognitive overload, limiting the usefulness of learning.² It is ideal for repeated practice of anatomy recognition, cognitive skill acquisition, and controlled practice, without the need for a real patient or manikin. There is only a controller, but no real probe, reducing the haptic effect of the simulator. The cost is in the low-mid range as compared to a high-fidelity simulator.

In AR, digital cues are overlaid on the real world so that the trainee can still see the real probe, manikin, or patient while getting guidance for image acquisition. This provides a low-to-medium immersion environment as compared to VR.² This is best suited for point-of-care guidance, probe orientation, and mapping anatomy overlays. The main drawback is the limited depth perception. It has a low-mid cost range as compared to a high-fidelity simulator.

High-fidelity simulators provide a very high level of immersion with a physical probe, a full tissue manikin, a very high cost, and are appropriate for full procedural skill acquisition. They need instructors and are mostly restricted to simulation labs.

This study is conducted as a standalone experiment. It will be more appropriate to have these sessions integrated into a formal PoCUS program. Experiential learning, as described by David Kolb, involves a cyclical process of concrete experience, reflective observation, abstract conceptualization, and active experimentation. By supporting experiential learning through repeated practice, reflection, feedback, and application, XR has the potential to enhance both skill acquisition and learner engagement.¹⁴

Furthermore, the ability of XR platforms to support repetitive, self-directed practice aligns closely with established principles of simulation-based education, including deliberate practice and mastery learning. Learners can practice independently, receive feedback, and progress toward competency at their own pace, potentially bridging the gap between simulation-based skill acquisition and clinical performance.¹⁵ The curriculum for the PoCUS program thus must be designed keeping a higher purpose of learning in mind. As these technologies continue to evolve, curriculum design must remain guided by educational principles and learner needs rather than technology alone.

The authors must be applauded for designing an MR simulator with good image quality and portability and demonstrating its utility in a small study. The scanning of the patient immediately following the scanning using the simulator is indeed innovative and will make a deep mark in the learning process. With the MR simulator available at bedside, it is time to re-examine the design of PoCUS programs to focus on more effective forms of learning.

Future studies should evaluate not only learner satisfaction and procedural efficiency, but also competency attainment, skill retention, transfer to clinical performance, and ultimately impact on patient care. The promise of XR lies not merely in creating more immersive simulations but in enabling more effective, scalable, and learner-centered approaches to healthcare education.

Orcid

Vivek Kumar https://orcid.org/0000-0002-6914-5422

Suchitra Mohite https://orcid.org/0009-0006-2484-5712

Parag Rishipathak https://orcid.org/0000-0003-4916-0841

Shrimathy Vijayaraghavan https://orcid.org/0000-0002-0007-1381