Research trends in virtual reality surgical simulation for education: a systematic review

Abstract

Purpose

Virtual reality (VR) has emerged as a transformative tool in surgical education, offering a controlled and repeatable training environment that mitigates ethical and legal challenges associated with traditional apprenticeship models. By simulating real-life surgical scenarios, VR allows trainees to practice procedures safely while improving skill acquisition and procedural efficiency. In this study, we systematically reviewed research trends in VR-based surgical education to provide insights into its current applications and future potential.

Methods

A comprehensive literature search was conducted on PubMed, identifying 395 studies. Of these, 92 studies met predefined inclusion criteria and were selected for analysis. The selected studies were analyzed based on publication period, surgical procedure, medical specialty, country of origin, and outcome measures.

Results

Study findings revealed that research on VR surgical simulation peaked between 2005 and 2009, followed by a decline in recent years. Laparoscopic and endoscopic training were the most frequently studied procedures, with general surgery and gastroenterology being the most predominant specialties. The United States contributed the highest number of publications. Common outcome measures for evaluating VR training effectiveness included time, movement economy, subject evaluation, error rates, proficiency scales, and accuracy.

Conclusion

These findings illustrate the historical trajectory and current landscape of VR use in surgical training. While the initial surge in interest has waned, VR remains a valuable tool for procedural skill development, particularly in laparoscopic and endoscopic training, and its future potential may depend on improvements in realism, cost-efficiency, and curriculum integration.

INTRODUCTION

The acquisition of surgical expertise extends beyond theoretical knowledge, requiring substantial hands-on experience in the operating room. Repetitive practice is essential for achieving mastery in surgical skills. Traditionally, surgical education has relied on the apprenticeship model, where trainees learn by performing procedures on actual patients under the supervision of experienced surgeons [1–3]. However, this approach raises significant ethical concerns, as surgeries performed by unskilled practitioners can pose risks to patients. Moreover, the apprenticeship model faces mounting legal challenges, further complicating its viability. In response to these concerns, alternative training methods, including the use of cadavers and simulators, have been proposed. While these approaches mitigate the risk to patients, they have notable limitations. Cadavers and simulators cannot fully replicate the complexity of real-world surgical environments or account for the dynamic variables encountered during live surgeries [2–4].

Recent technological advancements have introduced virtual reality (VR) as a promising solution. VR technology can simulate environments that closely mirror actual surgical procedures, providing trainees with accessible and repeatable practice in identical scenarios [1]. These advantages position VR as a novel and effective tool for surgical education. Numerous studies have explored the efficacy of VR in surgical education, and several review papers have summarized these findings [2–4]. However, many of these reviews are constrained to specific medical specialties, excluding a significant number of relevant research. Consequently, a more comprehensive review is needed to accurately reflect the role of VR in surgical education. By conducting a thorough analysis of existing literature, we aimed to comprehend the current status and characteristics of VR in surgical education, to explore how VR can be further utilized in medicine and surgery, and to identify future directions for this field.

METHODS

On September 10, 2024, a search was conducted on the PubMed database for studies related to VR in surgical education using the keywords “virtual reality” AND “surgery education.” This initial search yielded 395 papers, which were then screened based on their abstracts.

A total of 289 papers were excluded during the screening process. The exclusion criteria were as follows: papers not primarily focused on surgical education through VR (n = 130), review articles rather than original research (n = 95), papers for which the original text could not be accessed via the PubMed link (n = 26), papers written in a language other than English (n = 9), papers published before 2000 (n = 18), editorials or comments (n = 5), papers discussing VR in a general context rather than specific applications in surgical education (n = 5), and case reports (n = 1). Afterward, a full-text review was conducted on the remaining papers. Of these, 14 papers were excluded because their primary content did not pertain to surgical practice facilitated by VR (n = 13) or because VR was not employed for a specific surgery or procedure (n = 1). Ultimately, the final review included 92 papers [5–96] (Fig. 1).

Fig. 1.

Flow diagram for research paper selection.

The following values were measured and compiled from the 92 papers included in the review:

1. First author: Defined as the author whose name appears first when the paper is accessed via a PubMed search.

2. Year of publication: Based on the year displayed at the top of the paper when accessed via PubMed.

3. Country of origin: Determined by the country of the research institution listed first in the affiliation section of the paper.

4. Utilized VR: Refers to the specific VR technology or system used in the study.

5. Surgery/procedure name: The name of the specific surgery or procedure performed using VR, as mentioned in the paper. If multiple surgeries or procedures were documented in a single paper, they were enumerated separately. For cases such as laparoscopic instrument manipulation, which do not represent specific surgeries or procedures, they were classified as basic laparoscopic tasks. Similarly, in cases of robotic instrument manipulations, which do not represent specific surgeries or procedures, they were classified as robotic surgical tasks.

6. Medical specialty: Organized by department as follows: the department explicitly mentioned in the paper, or the department that performs the specific surgery and procedure mentioned. However, cases where the procedure is performed across too many departments or involves general tasks (e.g., laparoscopic or robotic instrument manipulation) were excluded.

7. Total participants: The total number of individuals who participated in the study. The number of participants in each group was counted separately, with details of each group recorded alongside the relevant number.

8. Intervention: Refers to the specific actions or measures implemented for a particular group or, in some cases, for all participants included in the study.

9. Outcome measures: Defined as the evaluation indicators mentioned in the paper.

10. Results: A concise summary of the study’s findings.

RESULTS

The 92 papers selected for the review were organized and analyzed based on the following categories: period, surgery or procedure type, medical specialty, country, and outcome measures (Supplementary Table 1).

Classification by time period

Papers spanning 25 years (2000–2024) were grouped into 5-year intervals to analyze the number of papers over time (Fig. 2). The period from 2005 to 2009 had the largest number of related papers, with 36 papers, while the most recent period (2020–2024) had the fewest, with only six papers.

Fig. 2.

Classification of virtual reality surgical simulation research papers by time period.

Classification by surgery or procedure

The frequency of surgical procedures was analyzed, and the results are presented in Fig. 3. The most common topic was basic laparoscopic technique education, with laparoscopic cholecystectomy being the most frequently mentioned specific surgery. Subsequently, a significant number of papers addressed basic techniques of robotic surgery and endoscopic techniques such as colonoscopy. This was followed by papers on colorectal surgery such as colectomy and laparoscopic appendectomy. Notably, specific surgeries or procedures were mentioned in only one or two papers each.

Fig. 3.

Classification of virtual reality surgical simulation research papers by surgery or procedure.

Classification by medical specialty

The papers were classified by the medical specialties performing the above-mentioned surgeries or procedures, as shown in Fig. 4. Basic laparoscopic and robotic surgical techniques are most frequently performed in general surgery, they were excluded from this classification because they are common techniques used across multiple departments, such as gynecology, urology, thoracic surgery, and otolaryngology. Similarly, intravenous catheterization was excluded due to its widespread use across various departments. Only departments performing specific surgeries or procedures were counted. General surgery had the highest number of cases (46), followed by gastroenterology (14). Other departments had three or fewer cases.

Fig. 4.

Classification of virtual reality surgical simulation research papers by medical specialty.

Classification by country

When categorizing the papers by the country of affiliation of the authors, the United States had the highest number of publications (34), followed by the United Kingdom, the Netherlands, Germany, Denmark, Canada, and Spain (Fig. 5). In Asia, papers were published from Hong Kong, Japan, and Taiwan; however, there were relatively fewer papers from these regions than from the United States and Europe.

Fig. 5.

Classification of virtual reality surgical simulation research papers by country. NA, not applicable.

Classification by outcome measures

VR-based surgical education utilizes several performance metrics to assess trainee proficiency and progress (Fig. 6). The most used performance metrics are:

Fig. 6.

Classification of virtual reality surgical simulation research papers by outcome measure.

• Time: A fundamental indicator of procedural efficiency, with reduced execution time often signifying improved expertise.

• Movement economy: Assesses the efficiency and precision of surgical motions, focusing on minimizing unnecessary movements while enhancing dexterity and motor control.

• Subject evaluation: Provides qualitative feedback from expert surgeons or educators, assessing technique, decision-making, and adherence to surgical protocols.

• Errors: A quantitative measure of mistakes made during a procedure, with lower error rates indicating greater accuracy and procedural mastery.

• Proficiency assessment scales: Standardized scoring systems that integrate multiple evaluation criteria to objectively track skill progression.

• Accuracy/precision: Evaluates the consistency and exactness of surgical tasks, emphasizing precise instrument handling and incision control.

DISCUSSION

This review highlights the growing interest among medical professionals in the utilization of VR as a surgical simulator. A significant number of papers were published in the late 2000s, with the majority focusing on laparoscopic and endoscopic surgery. Consequently, a significant proportion of the procedures and surgeries documented in these papers were related to general surgery and gastroenterology. This concentration likely reflects the earlier availability and validation of VR simulators in gastrointestinal surgery, whereas limited use in neurosurgery, orthopedics, and gynecology may relate to procedural complexity, lack of specialty-specific platforms, or differing training needs.

This review differs from existing review papers in several keyways. First, in terms of methodology, most existing reviews conducted reviews on specific departments or surgeries. In contrast, this study utilized simplified search terms to encompass a wide range of papers on surgical VR simulators, regardless of their specific department. Furthermore, review papers demonstrating efficacy often incorporate additional statistical analyses from existing randomized control trial studies [97,98]; however, this review did not exclude papers based on research methodology or conduct statistical analysis. Instead, the focus was on compiling a comprehensive set of papers to provide a broad overview of the subject area.

In VR-based surgical education, multiple performance indicators can be used to evaluate trainee proficiency and progress. In this review, the following key performance metrics are commonly used in VR education research papers: time, movement economy, subject evaluation, errors, proficiency assessment scales, and accuracy/precision. One of the fundamental metrics is time, which measures the total duration required to complete a surgical procedure. As trainees gain experience and improve their techniques, the time taken to complete tasks generally decreases. A reduction in execution time without compromising accuracy often indicates increased proficiency, making this metric essential for assessing the learning curve and efficiency of trainees. Another crucial metric is movement economy, which evaluates the efficiency of a trainee’s surgical movements. This metric assesses the smoothness, precision, and efficiency of hand and instrument movements, aiming to reduce unnecessary actions and improve motor control. Parameters such as movement distance, speed, acceleration, and trajectory are often analyzed to determine how effectively a trainee utilizes their hands and tools during a procedure. Greater movement efficiency is associated with higher dexterity and surgical competence. Subject evaluation refers to qualitative assessments conducted by expert surgeons or educators. These evaluations typically involve reviewing a trainee’s technique, decision-making, and overall performance during a simulated procedure. Subjective assessments provide valuable insights into aspects of performance that may not be fully captured by quantitative measures. They often include feedback on posture, instrument handling, and adherence to surgical protocols, offering a more comprehensive assessment of the trainee’s skills. Errors refer to mistakes made during a procedure, such as incorrect instrument usage, imprecise incisions, excessive tissue damage, or deviations from expected surgical steps. These errors are systematically recorded and quantified to evaluate a trainee’s accuracy and consistency. A lower error rate indicates greater mastery of the procedure and reflects the effectiveness of the training. Reducing errors is a key objective in surgical education, as precision is critical for ensuring patient safety in real-life operations. The proficiency assessment scale is a structured scoring system used to evaluate a trainee’s overall competence. This scale is based on predefined performance benchmarks and often integrates multiple evaluation criteria, including time, accuracy, movement efficiency, and qualitative feedback. By assigning a proficiency score, this assessment provides a standardized method for measuring skill progression and comparing performance across trainees. Finally, accuracy/precision is a critical metric that assesses the degree of exactness and consistency in surgical tasks. This includes the ability to make precise incisions, maintain correct angles during suturing, and position instruments accurately. High accuracy and precision are essential for ensuring optimal surgical outcomes, as even minor deviations can lead to complications in real-world procedures. Trainees who exhibit high accuracy demonstrate refined motor skills and better control over surgical maneuvers. Together, these performance metrics provide a comprehensive evaluation of a trainee’s capabilities in VR-based surgical education. By analyzing both quantitative and qualitative aspects, educators can effectively identify strengths, address weaknesses, and optimize training methodologies. This ensures that surgical trainees develop the necessary skills to perform real-life procedures safely and efficiently.

This review had some limitations. The process of collecting and analyzing existing articles was conducted as a descriptive literature review without statistical analysis. Consequently, the lack of quantitative comparison or objective verification may limit the reliability of the findings, as the influence of individual articles was not systematically assessed. In addition, articles available in databases other than PubMed or in languages other than English may have been omitted, as the search was limited to English-language articles within a single database. Furthermore, not all VR simulators developed for surgery may have been published in medical journals, which could result in certain trends being overlooked. Therefore, expanding the search to include patent databases or other academic repositories could help identify more accurate results and trends, including the latest advancements in VR simulators. Another limitation is the focus of this review on articles addressing surgical practice using VR simulators. As a result, several studies that explored factors affecting surgeons’ use of VR simulators were excluded [99,100]. For example, evaluating the effects of sleep deprivation on laparoscopic surgery in a real clinical setting is challenging due to ethical and environmental constraints. However, VR simulators provide a controlled, repeatable environment, enabling precise assessment of such factors on surgical performance. While common outcome metrics such as time and error rate were summarized, no statistical synthesis or comparative analysis was performed due to variability in study designs. This limits the ability to draw strong conclusions on the effectiveness of VR training. Additionally, the review did not explore cost-effectiveness or implementation challenges in depth. Future studies should address these aspects to support the evidence-based adoption of VR in surgical education.

Interestingly, while the use of VR surgical simulators peaked between 2005 and 2009, the number of related publications has declined in recent years. This trend may be attributed to several factors, including limited realism and haptic feedback in earlier VR platforms, high implementation costs, and challenges in integrating simulators into formal surgical curricula. Additionally, research attention may have shifted toward emerging technologies such as augmented and mixed reality. These observations imply that the early enthusiasm for VR was not always sustained in clinical education contexts. Accordingly, future research should explore whether this decline reflects evolving educational priorities, limitations in clinical applicability, or a reassessment of VR’s effectiveness in surgical training.

In conclusion, this study examined the current status and historical trends of VR simulators in surgical training. While the initial surge in interest has waned, VR remains a promising tool. Future developments in realism, affordability, and curriculum integration may lead to renewed adoption and broader utilization in surgical education.

Supplementary materials

Supplementary materials can be found via https://doi.org/10.7602/jmis.2025.28.2.51.