Virtual reality in teaching and training of interventional procedures_West China Medical Journal

Authors：

WANG Xiaoze ^1,2 , LUO Xuefeng ^1,2 ,  YANG Li ^1,2

1. Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. The Sichuan University-University of Oxford Huaxi Joint Centre for Gastrointestinal Cancer, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

YANG Li, Email: yangli_hx@scu.edu.cn

Keywords：

Virtual reality; interventional procedures; medical education; procedure training

DOI：

10.7507/1002-0179.202302079

Video：

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Interventional radiology is an emerging discipline based on image-guided minimally invasive diagnosis and treatment. The number of interventional procedures performed is increasing year by year, resulting in a dramatic increase in the demand for interventional radiologists. Procedure training systems based on virtual reality (VR) technology simulate real interventional procedure through real-time interaction between hand manipulators and virtual environments, allowing physicians to experience real interventional procedures during training and reducing training time and costs. A growing number of medical schools are now adopting VR simulated training systems for interventional procedure training. This article reviews the relevant research progress of VR simulation interventional procedure training system in recent years and discusses the development prospects of VR technology in interventional procedure training.

Citation： WANG Xiaoze, LUO Xuefeng, YANG Li. Virtual reality in teaching and training of interventional procedures. West China Medical Journal, 2023, 38(6): 910-913. doi: 10.7507/1002-0179.202302079 Copy

1.	Boeken T, Feydy J, Lecler A, et al. Artificial intelligence in diagnostic and interventional radiology: where are we now?. Diagn Interv Imaging, 2023, 104(1): 1-5.
2.	Frankiewicz M, Vetterlein MW, Matuszewski M, et al. VR, reconstructive urology and the future of surgery education. Nat Rev Urol, 2023: 1-2.
3.	Banerjee S, Pham T, Eastaway A, et al. The use of virtual reality in teaching three-dimensional anatomy and pathology on CT. J Digit Imaging, 2023: 1-6.
4.	韩浩贤, 刘运德, 赵珊, 等. 医学类虚拟仿真实验教学中心建设的 SWOT 分析. 中国高等医学教育, 2018(11): 16-17.
5.	Nielsen CA, Lönn L, Konge L, et al. Simulation-based virtual-reality patient-specific rehearsal prior to endovascular procedures: a systematic review. Diagnostics (Basel), 2020, 10(7): 500.
6.	Bourdillon AT, Garg A, Wang H, et al. Integration of reinforcement learning in a virtual robotic surgical simulation. Surg Innov, 2023, 30(1): 94-102.
7.	Paro MR, Hersh DS, Bulsara KR. History of virtual reality and augmented reality in neurosurgical training. World Neurosurg, 2022, 167: 37-43.
8.	Jung C, Wolff G, Wernly B, et al. Virtual and augmented reality in cardiovascular care: state-of-the-art and future perspectives. JACC Cardiovasc Imaging, 2022, 15(3): 519-532.
9.	Shi P, Guo S, Jin X, et al. A novel catheter interaction simulating method for virtual reality interventional training systems. Med Biol Eng Comput, 2023, 61(3): 685-697.
10.	Suryadevara NC, Reddy A, Bradshaw D, et al. Stroke neurointervention: a novel educational pathway to improve neurology resident training in neurointervention and regional access to thrombectomy. Stroke Vasc Interv Neurol, 2022, 2(6): e000414.
11.	Bao X, Guo S, Xiao N, et al. A cooperation of catheters and guidewires-based novel remote-controlled vascular interventional robot. Biomed Microdevices, 2018, 20(1): 20.
12.	Mascheroni J, Mont L, Stockburger M, et al. A validation study of intraoperative performance metrics for training novice cardiac resynchronization therapy implanters. Int J Cardiol, 2020, 307: 48-54.
13.	El-Andari R, Bozso SJ, Kang JJH, et al. Review of the use of simulators in learning revascularization techniques. Gen Thorac Cardiovasc Surg, 2021, 69(3): 415-424.
14.	张扬, 谢叻, 沈浩, 等. 心血管介入虚拟手术的力反馈研究. 机械设计与研究, 2017, 33(4): 58-62, 67.
15.	陈铁凝, 康瑞瑞, 朱建军, 等. 基于非线性力反馈的血管介入手术训练系统. 光学技术, 2019, 45(2): 129-135.
16.	王宇, 石志航. 血管介入手术 VR 训练系统的力检测装置设计. 机械设计与制造, 2022(6): 149-151.
17.	何昊, 叶子健, 舒畅. 血管介入手术机器人系统关键技术及研发现状. 中国普通外科杂志, 2021, 30(12): 1477-1484.
18.	Johnson SJ, Guediri SM, Kilkenny C, et al. Development and validation of a virtual reality simulator: human factors input to interventional radiology training. Hum Factors, 2011, 53(6): 612-625.
19.	Chaer RA, Derubertis BG, Lin SC, et al. Simulation improves resident performance in catheter-based intervention: results of a randomized, controlled study. Ann Surg, 2006, 244(3): 343-352.
20.	Berry M, Lystig T, Beard J, et al. Porcine transfer study: virtual reality simulator training compared with porcine training in endovascular novices. Cardiovasc Intervent Radiol, 2007, 30(3): 455-461.
21.	Nesbitt CI, Tingle SJ, Williams R, et al. Educational impact of a pulsatile human cadaver circulation model for endovascular training. Eur J Vasc Endovasc Surg, 2019, 58(4): 602-608.
22.	Zaed I, Chibbaro S, Ganau M, et al. Simulation and virtual reality in intracranial aneurysms neurosurgical training: a systematic review. Neurosurg Sci, 2022, 66(6): 494-500.
23.	Gelmini AYP, Duarte ML, de Assis AM, et al. Virtual reality in interventional radiology education: a systematic review. Radiol Bras, 2021, 54(4): 254-260.
24.	Wang HY, Wu JH. A virtual reality based surgical skills training simulator for catheter ablation with real-time and robust interaction. Virtual Real Intell Hardw, 2021, 3(4): 302-314.
25.	Knudsen BE, Matsumoto ED, Chew BH, et al. A randomized, controlled, prospective study validating the acquisition of percutaneous renal collecting system access skills using a computer based hybrid virtual reality surgical simulator: phase Ⅰ. J Urol, 2006, 176(5): 2173-2178.
26.	Berry M, Hellström M, Göthlin J, et al. Endovascular training with animals versus virtual reality systems: an economic analysis. J Vasc Interv Radiol, 2008, 19(2 Pt 1): 233-238.
27.	Mishra R, Narayanan MDK, Umana GE, et al. Virtual reality in neurosurgery: beyond neurosurgical planning. Int J Environ Res Public Health, 2022, 19(3): 1719.
28.	Cohen ER, Feinglass J, Barsuk JH, et al. Cost savings from reduced catheter-related bloodstream infection after simulation-based education for residents in a medical intensive care unit. Simul Healthc, 2010, 5(2): 98-102.
29.	Glaiberman CB, Jacobs B, Street M, et al. Simulation in training: one-year experience using an efficiency index to assess interventional radiology fellow training status. J Vasc Interv Radiol, 2008, 19(9): 1366-1371.
30.	Li S, Guo J, Wang Q, et al. A catheterization-training simulator based on a fast multigrid solver. IEEE Comput Graph Appl, 2012, 32(6): 56-70.
31.	Berry M, Reznick R, Lystig T, et al. The use of virtual reality for training in carotid artery stenting: a construct validation study. Acta Radiol, 2008, 49(7): 801-805.
32.	Van Herzeele I, Aggarwal R, Choong A, et al. Virtual reality simulation objectively differentiates level of carotid stent experience in experienced interventionalists. J Vasc Surg, 2007, 46(5): 855-863.
33.	Faruki A, Nguyen T, Proeschel S, et al. Virtual reality as an adjunct to anesthesia in the operating room. Trials, 2019, 20(1): 782.
34.	Aeckersberg G, Gkremoutis A, Schmitz-Rixen T, et al. The relevance of low-fidelity virtual reality simulators compared with other learning methods in basic endovascular skills training. J Vasc Surg, 2019, 69(1): 227-235.

1. Boeken T, Feydy J, Lecler A, et al. Artificial intelligence in diagnostic and interventional radiology: where are we now?. Diagn Interv Imaging, 2023, 104(1): 1-5.
2. Frankiewicz M, Vetterlein MW, Matuszewski M, et al. VR, reconstructive urology and the future of surgery education. Nat Rev Urol, 2023: 1-2.
3. Banerjee S, Pham T, Eastaway A, et al. The use of virtual reality in teaching three-dimensional anatomy and pathology on CT. J Digit Imaging, 2023: 1-6.
4. 韩浩贤, 刘运德, 赵珊, 等. 医学类虚拟仿真实验教学中心建设的 SWOT 分析. 中国高等医学教育, 2018(11): 16-17.
5. Nielsen CA, Lönn L, Konge L, et al. Simulation-based virtual-reality patient-specific rehearsal prior to endovascular procedures: a systematic review. Diagnostics (Basel), 2020, 10(7): 500.
6. Bourdillon AT, Garg A, Wang H, et al. Integration of reinforcement learning in a virtual robotic surgical simulation. Surg Innov, 2023, 30(1): 94-102.
7. Paro MR, Hersh DS, Bulsara KR. History of virtual reality and augmented reality in neurosurgical training. World Neurosurg, 2022, 167: 37-43.
8. Jung C, Wolff G, Wernly B, et al. Virtual and augmented reality in cardiovascular care: state-of-the-art and future perspectives. JACC Cardiovasc Imaging, 2022, 15(3): 519-532.
9. Shi P, Guo S, Jin X, et al. A novel catheter interaction simulating method for virtual reality interventional training systems. Med Biol Eng Comput, 2023, 61(3): 685-697.
10. Suryadevara NC, Reddy A, Bradshaw D, et al. Stroke neurointervention: a novel educational pathway to improve neurology resident training in neurointervention and regional access to thrombectomy. Stroke Vasc Interv Neurol, 2022, 2(6): e000414.
11. Bao X, Guo S, Xiao N, et al. A cooperation of catheters and guidewires-based novel remote-controlled vascular interventional robot. Biomed Microdevices, 2018, 20(1): 20.
12. Mascheroni J, Mont L, Stockburger M, et al. A validation study of intraoperative performance metrics for training novice cardiac resynchronization therapy implanters. Int J Cardiol, 2020, 307: 48-54.
13. El-Andari R, Bozso SJ, Kang JJH, et al. Review of the use of simulators in learning revascularization techniques. Gen Thorac Cardiovasc Surg, 2021, 69(3): 415-424.
14. 张扬, 谢叻, 沈浩, 等. 心血管介入虚拟手术的力反馈研究. 机械设计与研究, 2017, 33(4): 58-62, 67.
15. 陈铁凝, 康瑞瑞, 朱建军, 等. 基于非线性力反馈的血管介入手术训练系统. 光学技术, 2019, 45(2): 129-135.
16. 王宇, 石志航. 血管介入手术 VR 训练系统的力检测装置设计. 机械设计与制造, 2022(6): 149-151.
17. 何昊, 叶子健, 舒畅. 血管介入手术机器人系统关键技术及研发现状. 中国普通外科杂志, 2021, 30(12): 1477-1484.
18. Johnson SJ, Guediri SM, Kilkenny C, et al. Development and validation of a virtual reality simulator: human factors input to interventional radiology training. Hum Factors, 2011, 53(6): 612-625.
19. Chaer RA, Derubertis BG, Lin SC, et al. Simulation improves resident performance in catheter-based intervention: results of a randomized, controlled study. Ann Surg, 2006, 244(3): 343-352.
20. Berry M, Lystig T, Beard J, et al. Porcine transfer study: virtual reality simulator training compared with porcine training in endovascular novices. Cardiovasc Intervent Radiol, 2007, 30(3): 455-461.
21. Nesbitt CI, Tingle SJ, Williams R, et al. Educational impact of a pulsatile human cadaver circulation model for endovascular training. Eur J Vasc Endovasc Surg, 2019, 58(4): 602-608.
22. Zaed I, Chibbaro S, Ganau M, et al. Simulation and virtual reality in intracranial aneurysms neurosurgical training: a systematic review. Neurosurg Sci, 2022, 66(6): 494-500.
23. Gelmini AYP, Duarte ML, de Assis AM, et al. Virtual reality in interventional radiology education: a systematic review. Radiol Bras, 2021, 54(4): 254-260.
24. Wang HY, Wu JH. A virtual reality based surgical skills training simulator for catheter ablation with real-time and robust interaction. Virtual Real Intell Hardw, 2021, 3(4): 302-314.
25. Knudsen BE, Matsumoto ED, Chew BH, et al. A randomized, controlled, prospective study validating the acquisition of percutaneous renal collecting system access skills using a computer based hybrid virtual reality surgical simulator: phase Ⅰ. J Urol, 2006, 176(5): 2173-2178.
26. Berry M, Hellström M, Göthlin J, et al. Endovascular training with animals versus virtual reality systems: an economic analysis. J Vasc Interv Radiol, 2008, 19(2 Pt 1): 233-238.
27. Mishra R, Narayanan MDK, Umana GE, et al. Virtual reality in neurosurgery: beyond neurosurgical planning. Int J Environ Res Public Health, 2022, 19(3): 1719.
28. Cohen ER, Feinglass J, Barsuk JH, et al. Cost savings from reduced catheter-related bloodstream infection after simulation-based education for residents in a medical intensive care unit. Simul Healthc, 2010, 5(2): 98-102.
29. Glaiberman CB, Jacobs B, Street M, et al. Simulation in training: one-year experience using an efficiency index to assess interventional radiology fellow training status. J Vasc Interv Radiol, 2008, 19(9): 1366-1371.
30. Li S, Guo J, Wang Q, et al. A catheterization-training simulator based on a fast multigrid solver. IEEE Comput Graph Appl, 2012, 32(6): 56-70.
31. Berry M, Reznick R, Lystig T, et al. The use of virtual reality for training in carotid artery stenting: a construct validation study. Acta Radiol, 2008, 49(7): 801-805.
32. Van Herzeele I, Aggarwal R, Choong A, et al. Virtual reality simulation objectively differentiates level of carotid stent experience in experienced interventionalists. J Vasc Surg, 2007, 46(5): 855-863.
33. Faruki A, Nguyen T, Proeschel S, et al. Virtual reality as an adjunct to anesthesia in the operating room. Trials, 2019, 20(1): 782.
34. Aeckersberg G, Gkremoutis A, Schmitz-Rixen T, et al. The relevance of low-fidelity virtual reality simulators compared with other learning methods in basic endovascular skills training. J Vasc Surg, 2019, 69(1): 227-235.

West China Medical Journal

Virtual reality in teaching and training of interventional procedures

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