Thorac Cardiovasc Surg 2022; 70(04): 355-360
DOI: 10.1055/s-0041-1731783
Original Thoracic

Development of a 3D Printed Lung Model Made of Synthetic Materials for Simulation

Ganwei Liu*
1   Peking University People's Hospital, Beijing, China
,
Wenjie Bian*
1   Peking University People's Hospital, Beijing, China
,
Guili Zu
1   Peking University People's Hospital, Beijing, China
,
Jing Liu
1   Peking University People's Hospital, Beijing, China
,
Guoxin Zhang
2   Jucheng Teaching Technology Development Co. Ltd, Yingkou, Liaoning, China
,
Changji Li
2   Jucheng Teaching Technology Development Co. Ltd, Yingkou, Liaoning, China
,
Guanchao Jiang
1   Peking University People's Hospital, Beijing, China
› Author Affiliations
Funding This study was supported by National Natural Science Foundation of China (Grant No. 61877001).

Abstract

Background Considering the complexity of lung structures and the difficulty of thoracoscopic surgery, simulation-based training is of paramount importance for junior surgeons. Here, we aim to design a high-fidelity lung model through utilizing the three-dimensional (3D) printing technology combined with synthetic materials to mimic the real human lung.

Methods The 3D printed lung model was manufactured based on the computed tomography images of a randomly selected male patient. Synthetic materials were used for the construction of lung parenchyma, blood vessels, and bronchi. Then, the model was assessed in terms of its visual, tactile, and operational features by participants (the senior surgeons, junior surgeons, and medical students), who were asked to complete the specially designed survey-questionnaires.

Results A 3D printed model of the right lung made of synthetic materials was successfully fabricated. Thirty subjects participated in our study (10 senior surgeons, 10 junior surgeons, and 10 medical students). The average visual evaluation scores for senior surgeons, junior surgeons, and medical students were 3.97 ± 0.61, 4.56 ± 0.58, 4.76 ± 0.49, respectively. The average tactile evaluation scores were 3.40 ± 0.50, 4.13 ± 0.68, 4.00 ± 0.64, respectively. The average operation evaluation scores were 3.33 ± 0.83, 3.93 ± 0.66, 4.03 ± 0.66, respectively. Significant lower scores were obtained in the group of the senior surgeons compared with the other two groups.

Conclusion A high level of fidelity was exhibited in our 3D printed lung model and it could be applied as a promising simulator for the surgical training in the future.

Data Availability Statement

Any further inquiries can be directed to the corresponding author.


* Both authors contributed equally to the work.




Publication History

Received: 10 March 2021

Accepted: 18 May 2021

Article published online:
21 September 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 
  • References

  • 1 Xu YJ, Du Y, Fan Y. Long noncoding RNAs in lung cancer: what we know in 2015. Clin Transl Oncol 2016; 18 (07) 660-665
  • 2 Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin 2014; 64 (01) 9-29
  • 3 Whitson BA, Groth SS, Duval SJ, Swanson SJ, Maddaus MA. Surgery for early-stage non-small cell lung cancer: a systematic review of the video-assisted thoracoscopic surgery versus thoracotomy approaches to lobectomy. Ann Thorac Surg 2008; 86 (06) 2008-2016 , discussion 2016–2018
  • 4 Scott WJ, Allen MS, Darling G. et al. Video-assisted thoracic surgery versus open lobectomy for lung cancer: a secondary analysis of data from the American College of Surgeons Oncology Group Z0030 randomized clinical trial. J Thorac Cardiovasc Surg 2010; 139 (04) 976-981 , discussion 981–983
  • 5 Park BJ, Flores RM. Cost comparison of robotic, video-assisted thoracic surgery and thoracotomy approaches to pulmonary lobectomy. Thorac Surg Clin 2008; 18 (03) 297-300 , vii vii.
  • 6 McKenna Jr RJ. Complications and learning curves for video-assisted thoracic surgery lobectomy. Thorac Surg Clin 2008; 18 (03) 275-280
  • 7 Vanderbilt AA, Grover AC, Pastis NJ. et al. Randomized controlled trials: a systematic review of laparoscopic surgery and simulation-based training. Glob J Health Sci 2014; 7 (02) 310-327
  • 8 Reznick RK, MacRae H. Teaching surgical skills--changes in the wind. N Engl J Med 2006; 355 (25) 2664-2669
  • 9 Wang K, Sun J, Gao W. et al. Feasibility, effectiveness, and safety of a novel cryo-balloon targeted lung denervation technique in an animal model. Cryobiology 2020; 93: 27-32
  • 10 Makidono K, Miyata Y, Ikeda T. et al. Investigation of surgical technique for bronchial stump closure after lobectomy in animal model. Gen Thorac Cardiovasc Surg 2020; 68 (06) 609-614
  • 11 Onozato ML, Klepeis VE, Yagi Y, Mino-Kenudson M. A role of three-dimensional (3D) reconstruction in the classification of lung adenocarcinoma. Stud Health Technol Inform 2012; 179: 250-256
  • 12 Hammond I, Karthigasu K. Training, assessment and competency in gynaecologic surgery. Best Pract Res Clin Obstet Gynaecol 2006; 20 (01) 173-187
  • 13 Tong BC, Gustafson MR, Balderson SS, D'Amico TA, Meyerson SL. Validation of a thoracoscopic lobectomy simulator. Eur J Cardiothorac Surg 2012; 42 (02) 364-369 , discussion 369
  • 14 Young JC, Quayle MR, Adams JW, Bertram JF, McMenamin PG. Three-dimensional printing of archived human fetal material for teaching purposes. Anat Sci Educ 2019; 12 (01) 90-96
  • 15 Yang N, Chen H, Han H. et al. 3D printing and coating to fabricate a hollow bullet-shaped implant with porous surface for controlled cytoxan release. Int J Pharm 2018; 552 (1-2): 91-98
  • 16 Kucukgul C, Ozler SB, Inci I. et al. 3D bioprinting of biomimetic aortic vascular constructs with self-supporting cells. Biotechnol Bioeng 2015; 112 (04) 811-821
  • 17 Qiu K, Zhao Z, Haghiashtiani G. et al. 3D printed organ models with physical properties of tissue and integrated sensors. Adv Mater Technol 2018; 3 (03) 3
  • 18 Bjurström JM, Konge L, Lehnert P. et al. Simulation-based training for thoracoscopy. Simul Healthc 2013; 8 (05) 317-323
  • 19 Meyerson SL, LoCascio F, Balderson SS, D'Amico TA. An inexpensive, reproducible tissue simulator for teaching thoracoscopic lobectomy. Ann Thorac Surg 2010; 89 (02) 594-597
  • 20 Jensen K, Ringsted C, Hansen HJ, Petersen RH, Konge L. Simulation-based training for thoracoscopic lobectomy: a randomized controlled trial: virtual-reality versus black-box simulation. Surg Endosc 2014; 28 (06) 1821-1829
  • 21 Monda SM, Weese JR, Anderson BG. et al. Development and validity of a silicone renal tumor model for robotic partial nephrectomy training. Urology 2018; 114: 114-120
  • 22 Glybochko PV, Rapoport LM, Alyaev YG. et al. Multiple application of three-dimensional soft kidney models with localized kidney cancer: a pilot study. Urologia 2018; 85 (03) 99-105