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

Jiaji Liu , Jiahao Cui , Liqun Chi , Jinglun Shen , Shuai Li , Lin Liang

Vessel Plus ›› 2026, Vol. 10 ›› Issue (1) -13.

PDF
Vessel Plus ›› 2026, Vol. 10 ›› Issue (1) -13. DOI: 10.20517/2574-1209.2025.103
Original Article
Research on the learning curve and simulation of proximal anastomosis in minimally invasive coronary artery bypass grafting
Author information +
History +
PDF

Abstract

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.

Keywords

Minimally invasive coronary artery bypass grafting / proximal anastomosis / learning curve / virtual reality

Cite this article

Download citation ▾
Jiaji Liu, Jiahao Cui, Liqun Chi, Jinglun Shen, Shuai Li, Lin Liang. Research on the learning curve and simulation of proximal anastomosis in minimally invasive coronary artery bypass grafting. Vessel Plus, 2026, 10(1): -13 DOI:10.20517/2574-1209.2025.103

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

McGinn JT Jr,Lapierre H,Mesana TG.Minimally invasive coronary artery bypass grafting: dual-center experience in 450 consecutive patients.Circulation2009;120:S78-84

[2]

Guo MH,Glineur D.Minimally Invasive coronary surgery compared to STernotomy coronary artery bypass grafting: the MIST trial.Contemp Clin Trials2019;78:140-5

[3]

Snegirev MA,Denisyuk DO.Minimally invasive multivessel coronary bypass surgery: angiographic patency data.J Card Surg2020;35:620-5

[4]

Nambala S,Ruel M.Less invasive multivessel coronary artery bypass grafting: now is the time.Curr Opin Cardiol2021;36:735-9

[5]

Ruel M.Minimally invasive coronary artery bypass grafting is the future: pro.Semin Thorac Cardiovasc Surg2025;37:34-42

[6]

Sef D,Hashim SA.Minimally invasive coronary artery bypass grafting for multivessel coronary artery disease: a systematic review.Innovations2024;19:351-9

[7]

Une D,Sohmer B,Ruel M.Can minimally invasive coronary artery bypass grafting be initiated and practiced safely?: a learning curve analysis.Innovations2013;8:403-9

[8]

Rodriguez ML,Sohmer B,Ruel MA.Predictors and outcomes of sternotomy conversion and cardiopulmonary bypass assistance in minimally invasive coronary artery bypass grafting.Innovations2016;11:315-20

[9]

Rodriguez ML,Sohmer B,Ruel M.Mid-term follow-up of minimally invasive multivessel coronary artery bypass grafting: is the early learning phase detrimental?.Innovations2017;12:116-20

[10]

Kikuchi K.Assistive techniques for proximal anastomosis in minimally invasive coronary artery bypass grafting.Innovations.2017;12:224-6

[11]

Une D.Initiation and modification of minimally invasive coronary artery bypass grafting.Gen Thorac Cardiovasc Surg2019;67:349-54

[12]

Qureshi SH.The 7 pillars of multivessel minimally invasive coronary surgery.Innovations2021;16:216-7 PMCID:PMC8640263

[13]

Ocagli H,Stivanello L,Canova C.The Barthel index as an indicator of hospital outcomes: a retrospective cross-sectional study with healthcare data from older people.J Adv Nurs2021;77:1751-61

[14]

Yushkevich PA,Gerig G.ITK-SNAP: an interactive tool for semi-automatic segmentation of multi-modality biomedical images.Annu Int Conf IEEE Eng Med Biol Soc2016;2016:3342-5 PMCID:PMC5493443

[15]

Li S,Hao A,Zhao Q.Design and evaluation of personalized percutaneous coronary intervention surgery simulation system.IEEE Trans Vis Comput Graph2021;27:4150-60

[16]

De Boer A,Bijl H.Mesh deformation based on radial basis function interpolation.Comput Struct2007;85:784-95

[17]

Vardoulakis I.Cosserat Continuum Mechanics. Cham: Springer; 2019.

[18]

Li C,Liu T.MGPBD: a multigrid accelerated global XPBD solver. In: Alford G, Zhang H, Schulz A, editors. Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers, 2025 Aug 10-14; Vancouver, Canada. New York: Association for Computing Machinery; 2025. pp. 1-11.

[19]

Sadeghi AH,Van Schaagen F.Immersive 3D virtual reality imaging in planning minimally invasive and complex adult cardiac surgery.Eur Heart J Digit Health2020;1:62-70 PMCID:PMC9708043

[20]

Liu J,Tang Z.Analysis of the learning curve for minimally invasive coronary artery bypass grafting.Chin J Clin Thorac Cardiovasc Surg2021;28:639-44. (in Chinese)Available from: https://www.cnki.com.cn/Article/CJFDTotal-ZXYX202106006.htm [Last accessed on 16 Apr 2026]

[21]

Wohl H.The cusum plot: its utility in the analysis of clinical data.N Engl J Med1977;296:1044-5

[22]

Chen R,Li S.A coupling physics model for real-time 4D simulation of cardiac electromechanics.Comput Aided Des2024;175:103747

[23]

Shahrezaei A,Taherkhani S.The impact of surgical simulation and training technologies on general surgery education.BMC Med Educ2024;24:1297 PMCID:PMC11558898

[24]

Nia P, Daemen JHT, Maessen JG. Development of a high-fidelity minimally invasive mitral valve surgery simulator.J Thorac Cardiovasc Surg2019;157:1567-74

[25]

Pan J,Yu P.Real-time VR simulation of laparoscopic cholecystectomy based on parallel position-based dynamics in GPU. In: Argelaguet F, Bruder G, Kopper R, et al., editors. 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), 2020 Mar 22-26; Atlanta, USA. New York: IEEE; 2020. pp. 548-56.

[26]

McKnight RR,Buck JS,Hsu JR.Virtual reality and augmented reality-translating surgical training into surgical technique.Curr Rev Musculoskelet Med2020;13:663-74 PMCID:PMC7661680

PDF

0

Accesses

0

Citation

Detail

Sections
Recommended

/