Research on the learning curve and simulation of proximal anastomosis in minimally invasive coronary artery bypass grafting

Aim: This study examines the learning curve for vein-to-aorta anastomosis in minimally invasive coronary artery bypass grafting (MICS CABG) and develops a virtual reality (VR) simulation model for this procedure, with validation to confirm its clinical relevance. Methods: We analyzed 132 consecutive off-pump MICS CABG procedures with multi-vessel grafting performed by a single surgeon (January 2017-January 2020). Proximal anastomosis time was plotted against case sequence, and the learning curve was quantified using cumulative summation analysis. A VR simulation platform was developed to reproduce key clinical challenges, using hierarchical geometric modeling and real-time physics simulation of tissue-instrument interactions with haptic feedback. Cardiac surgery experts evaluated the VR simulator via a structured questionnaire. Results: The learning curve for proximal anastomosis followed a three-phase progression, with proficiency achieved after 52 cases (model fit R² (the coefficient of determination) = 0.994). The VR simulation accurately replicated key surgical scenarios, focusing on bimanual suturing mechanics and needle-vessel interactions. Expert validation yielded an overall validity index of 0.78 (exceeding the 0.7 threshold), confirming good construct validity and clinical relevance of the simulator. Conclusion: Proficiency in MICS CABG proximal anastomosis is achieved after 52 cases, marking the inflection point of the learning curve. Our physics-validated VR simulator, supported by expert evaluation, has potential to accelerate surgical skill acquisition and shorten the learning curve.