Closing the Learning Gap in Arthroscopy: A Comparison of Conventional Training and Virtual Reality Simulation

Abstract

Backgroud:

To assess the efficacy of arthroscopic simulator training compared to conventional training in enhancing arthroscopic skills among novice orthopedic residents.

Material and methods:

In this single-center study, 30 orthopedic residents with no arthroscopy experience were randomized into simulator-based (E) or conventional (C) training groups. Group E completed 10 sessions each on basic and diagnostic simulator modules; Group C trained through supervised live surgery. All were evaluated using the simulator, and performance scores were compared.

Results:

The experimental group outperformed the control group, demonstrating significantly better structure visualization (14 vs. 13.53, P = 0.022), detailed visualization (25.47 vs. 23.4, P = 0.026), shorter procedure times (137 vs. 165.93 s, P < 0.001), and fewer errors, including misaligned scope horizon (6.27 vs. 11.33, P < 0.001), tibial cartilage scratching (0.93 vs. 1.53, P < 0.001), and femoral cartilage scratching (3.07 vs. 6.33, P < 0.001). Camera path length was also significantly reduced.

Conclusions:

Virtual-reality simulator training offers orthopedic residents a safe, controlled way to build essential skills, improving visualization, scope alignment, tissue handling, and efficiency—supporting its integration into residency programs for better-prepared surgeons.

INTRODUCTION

Preventable medical errors, causing over 400,000 deaths annually in the United States,[1] rank as the third leading cause of death and may pose an even greater risk in developing countries like India. Despite technological advancements, medical training often lacks integration of modern tools such as simulation technologies. Simulation-based learning addresses this gap by offering a safe, controlled environment for repeated skill practice, enhancing both competence and confidence.[2]

Arthroscopic surgery, though minimally invasive and beneficial, has a steep learning curve compared to open surgery, with higher complication rates during training. Limited operating room time and cost concerns further necessitate alternative methods. Virtual-reality-based simulators, like the VirtaMed ArthroS™ knee model, provide realistic, interactive platforms for arthroscopic training, enabling extensive practice and objective performance feedback.[3,4]

This study aimed to evaluate the effectiveness of arthroscopic simulator training versus conventional methods in developing arthroscopic skills, hypothesizing that while both would improve performance, simulator-based training would yield superior results.

MATERIALS AND METHODS

Participants

Thirty orthopedic MS residents from Gandhi Medical College and Hamidia Hospital, Bhopal, with no prior arthroscopy experience, voluntarily participated in the study without compensation. Residents with any arthroscopic experience were excluded. Institutional Ethical approval (Letter No. 49353/MC/IEC/2022) was obtained beforehand.

Study design

A single-center study at Gandhi Medical College, Bhopal (December 2022 to May 2023) involved 30 orthopedic residents randomly assigned to either a simulator-trained experimental group (E) or a conventionally trained control group (C). After training, both groups performed diagnostic knee arthroscopy on a simulator, and their performances were compared.

Procedures

After consent, participants completed a questionnaire and attended an orientation with a simulator demo. Baseline performance was recorded using the “Knee Arthroscopy Diagnostic Module 1” with minimal guidance.

Participants were randomized into experimental (E) and control (C) groups using a random number generator. Group E received brief instruction on the VirtaMed ArthroS™ knee simulator under mentor guidance. Training, designed with input from senior consultants, included two phases.

Phase 1 involved 10 unrestricted sessions on a non-anatomical model (FAST) to build basic arthroscopic skills like camera control, line tracing, probing, and star collection, with continuous scope-handling guidance.

Phase 2, participants trained on an anatomical knee simulator module to visualize 15 key structures with guided paths and real-time feedback. Each completed 10 sessions, tracked individually, with progression based on session completion.

Control group (C) underwent conventional training with no simulator use, while the experimental group (E) had simulator-only training. Post-training, all participants were evaluated on the same simulator module, and scores were compared.

Outcome measures

The outcome of our study is solely dependent on the simulator-generated scoring on different parameters. The following parameters are evaluated in “Diagnostic knee arthroscopy module 1:”

1. Structure visualization

2. Detailed visualization score

3. Procedure time

4. Misalignment of scope horizon

5. Scratching of femur cartilage

6. Scratching of tibia cartilage

7. Camera path length.

Statistical analysis

Data were entered in Microsoft Excel 2010 and analyzed using SPSS v23. Descriptive statistics were presented as mean ± standard deviation. Intergroup comparisons used the unpaired t-test, while intragroup comparisons used the paired t-test. Bar charts were used for graphical representation, with P < 0.05 considered statistically significant.

OBSERVATION AND RESULTS

The study included 15 first-year and 15 second-year male residents, all right-handed with prior video gaming experience. There were no dropouts. Table 1 shows no significant difference in baseline diagnostic arthroscopy performance between the experimental and control groups.

Table 1.

Baseline performance on the knee simulator in both groups

		Mean±SD				P
		Experimental group		Control group
Number of structures visualized		9±1.134		8.87±1.06		0.742
Detailed structure visualized		15.2±1.781		15.53±1.457		0.579
Procedure time (seconds)		363.4±27.619		360.73±28.149		0.795
Misalignment of scope horizon (%)		21.8±6.394		21.33±5.122		0.827
Scratching of tibia cartilage (%)		6.73±1.28		6.67±1.047		0.877
Scratching of femur cartilage (%)		15±3.817		16.07±2.738		0.387
Camera path length (cm)		292.87±43.433		302.0±33.724		0.525

SD=Standard deviation

Results of the final simulator score are summarized in Table 2, indicating the statistical significance of the improvements in the experimental group.

Table 2.

Result of final simulator score among two groups

		Mean±SD				P
		Experimental group		Control group
Number of structures visualized		14±0		13.53±0.743		0.022
Detailed structure visualized		25.47±2.167		23.4±2.613		0.026
Procedure time (s)		137±7.625		165.93±8.631		<0.001
Misalignment of scope horizon (%)		6.27±1.534		11.33±3.244		<0.001
Scratching of tibia cartilage (%)		0.93±0.884		1.53±0.915		<0.001
Scratching of femur cartilage (%)		3.07±1.335		6.33±2.059		<0.001
Camera path length (cm)		70.8±6.826		127.53±17.033		<0.001

SD=Standard deviation

Comparison of various parameter scores before and after training in the experimental group is summarized in Table 3.

Table 3.

Comparison of various parameter scores before and after training in the experimental group

		Mean±SD				P
		Baseline score		Post-training
Number of structures visualized		9±1.134		14±0		<0.001
Detailed structure visualized		15.2±1.781		25.47±2.167		<0.001
Procedure time (s)		363.4±27.619		137±7.625		<0.001
Misalignment of scope horizon (%)		21.8±6.394		6.27±1.534		<0.001
Scratching of tibia cartilage (%)		6.73±1.28		0.93±0.884		<0.001
Scratching of femur cartilage (%)		15±3.817		3.07±1.335		<0.001

SD=Standard deviation

DISCUSSION

Simulator training significantly improved arthroscopic skills, including visualization, scope alignment, and efficiency. It emphasized accurate structure identification and reduced errors, though the most effective module and ideal training duration remain unclear.

Though goal values were provided, training emphasized overall improvement over strict targets. Real-time guidance improved scope control, reducing camera path length and cartilage damage. Our findings align with Cychosz et al., but with structured training for both groups and a significant reduction in cartilage damage, highlighting simulator effectiveness.[5]

Our findings align with those of Putzer et al. and Anderson et al., showing improved efficiency, reduced tissue damage, and better hand-eye coordination. Unlike Anderson et al., we used a larger sample size (15 per group), improving statistical reliability.[6,7]

Rebolledo et al. reported improved shoulder arthroscopy skills with simulators but lacked significant knee arthroscopy results due to a small sample size and limited practice.[8] Our study addressed this with more participants and structured training, yielding significant improvements. By using simulator-generated scores, we ensured objective assessment, avoiding subjective bias.[9] Cannon et al. further support our findings, demonstrating that simulator-trained skills transfer effectively to real surgeries, reinforcing the need for simulation in residency curricula.[10]

Limitations

Limitations include lack of real OR assessment, inability to teach certain skills, high simulator cost, limited realism, and use of a single simulator. Broader studies are needed.

CONCLUSIONS

Simulator training provides a safe, effective way for orthopedic residents to build key arthroscopic skills without patient risk. Significant gains in visualization, scope alignment, tissue handling, and efficiency support its integration into residency programs, ensuring more competent and confident surgeons from the start.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.