Objective To evaluate the educational value of a high-fidelity lung model in training foundational skills for thoracoscopic lung resection. Methods A self-controlled study design was employed. Fifteen novice surgeons without prior thoracoscopic surgical experience, who participated in a thoracoscopic skills training program at Peking University People's Hospital from May 2022 to September 2023, were enrolled. The surgeons underwent a two-week structured curriculum covering five core thoracoscopic procedures: thoracic exploration, vascular dissection and division, lymphadenectomy, lung wedge resection, and specimen retrieval using an endoscopic retrieval bag. Skill assessments were conducted before and after training for each procedure. Paired-sample t-tests were used to compare skill scores before and after training. Results Following training, participants demonstrated significant improvements in all five core thoracoscopic skills compared to baseline [(1.0 ± 0) vs. (2.9 ± 0.8), (1.0 ± 0) vs. (3.2 ± 0.9), (1.0 ± 0) vs. (2.9 ± 0.4), (1.4 ± 0.5) vs. (3.7 ± 0.9), and (1.0 ± 0) vs. (2.6 ± 0.6), all P<0.001]. Conclusions Simulation-based training utilizing a high-fidelity lung model significantly enhances thoracoscopic surgical skills among novice surgeons. This approach provides an innovative solution for safe and efficient thoracoscopic skills training.
Liu Ganwei
,
Jiang Guanchao
. Application of high-fidelity lung model in simulation training of thoracoscopic skills[J]. Chinese Journal of Medical Education, 2025
, 45(4)
: 279
-282
.
DOI: 10.3760/cma.j.cn115259-20241105-01148
[1] Thai AA, Solomon BJ, Sequist LV, et al. Lung cancer[J]. Lancet, 2021,398(10299):535-554. DOI: 10.1016/S0140-6736(21)00312-3.
[2] Grossi S, Cattoni M, Rotolo N, et al. Video-assisted thoracoscopic surgery simulation and training: a comprehensive literature review[J]. BMC Med Educ, 2023,23(1):535. DOI: 10.1186/s12909-023-04482-z.
[3] Liu G, Bian W, Zu G, et al. Development of a 3D printed lung model made of synthetic materials for simulation[J]. Thorac Cardiovasc Surg, 2022,70(4):355-360. DOI: 10.1055/s-0041-1731783.
[4] Sato T, Morikawa T. Video-assisted thoracoscopic surgery training with a polyvinyl-alcohol hydrogel model mimicking real tissue[J]. J Vis Surg, 2017,3:65. DOI: 10.21037/jovs.2017.02.07.
[5] Kenny L, Booth K, Freystaetter K, et al. Training cardiothoracic surgeons of the future: the UK experience[J]. J Thorac Cardiovasc Surg, 2018,155(6):2526-2538.e2. DOI: 10.1016/j.jtcvs.2018.01.088.
[6] Jensen K, Ringsted C, Hansen HJ, et al. Simulation-based training for thoracoscopic lobectomy: a randomized controlled trial: virtual-reality versus black-box simulation[J]. Surg Endosc, 2014,28(6):1821-1829. DOI: 10.1007/s00464-013-3392-7.
[7] Solomon B, Bizekis C, Dellis SL, et al. Simulating video-assisted thoracoscopic lobectomy: a virtual reality cognitive task simulation[J]. J Thorac Cardiovasc Surg, 2011,141(1):249-255. DOI: 10.1016/j.jtcvs.2010.09.014.
[8] Martins Neto F, Moura Júnior LG, Rocha H, et al. Development and validation of a simulator for teaching minimally invasive thoracic surgery in Brazil[J]. Acta Cir Bras, 2021,36(5):e360508. DOI: 10.1590/ACB360508.
[9] Lazar A, Sroka G, Laufer S. Automatic assessment of performance in the FLS trainer using computer vision[J]. Surg Endosc, 2023,37(8):6476-6482. DOI: 10.1007/s00464-023-10132-8.
[10] Meyerson SL, LoCascio F, Balderson SS, et al. An inexpensive, reproducible tissue simulator for teaching thoracoscopic lobectomy[J]. Ann Thorac Surg, 2010,89(2):594-597. DOI: 10.1016/j.athoracsur.2009.07.067.
[11] Jensen K, Bjerrum F, Hansen HJ, et al. A new possibility in thoracoscopic virtual reality simulation training: development and testing of a novel virtual reality simulator for video-assisted thoracoscopic surgery lobectomy[J]. Interact Cardiovasc Thorac Surg, 2015,21(4):420-426. DOI: 10.1093/icvts/ivv183.
