Simulation training has evolved and is now able to offer numerous training opportunities to supplement the practice of and overcome some of the shortcomings of the traditional Master-Apprentice model currently used in medical training. Simulation training provides new opportunities to practice skills used in clinical procedures, crisis management scenarios, and everyday clinical practice in a risk-free environment. Procedural and nonprocedural skills used in interventional radiology can be taught with the use of simulation devices and technologies. This review will inform the reader of which clinical skills can be trained with simulation, the types of commercially available simulators and their educational validity, and the assessment tools used to evaluate simulation training.
Introduction
Clinical skills training in medical education is on the cusp of change. Increased pressure on the healthcare system to be safer has caused the current Master-Apprentice model of training to fall under scrutiny. The current model has many shortcomings pertaining to patient safety as training is done with real patients; time constraints on training because of shortened resident working hours; and the lack of uniformity in training as trainees are limited to only learning about clinical cases that their patients’ present. Medical simulation can effectively address these shortcomings. Medical simulation is broadly defined as “devices, life-like virtual environments and contrived social situations that mimic problems, events or conditions that arise in professional [medical] encounters” . Medical simulation allows trainees to train in virtual environments or on models, which eliminates the need to train on patients in the early stages of learning. Simulation training is not limited by working hours as training is done outside of the clinical setting. Instead, it can be administered as a self-paced curriculum tailored to a learner’s needs, or as part of a training course. Finally, medical simulation facilitates training uniformity by offering a wide range of scenarios that can be repeated indefinitely.
Interventional radiology (IR) is a specialty where medical simulation training can be especially beneficial. Because of advances in medical imaging, diagnostic angiographic procedures have become less common, reducing the number of opportunities for trainees to practice basic catheter manipulation skills. Additionally, specialists outside of IR are also interested in acquiring these skills . By adopting simulation training, trainees from all specialties will have the opportunity to learn these skills. Adding simulation will bring IR into the new era of medical training pioneered by anesthesiology, gynecology, and emergency medicine, specialities that have already implemented simulation training to supplement the apprenticeship model . The widespread use of simulation in the aforementioned specialities has triggered institutional support with the creation of a Joint Medical Simulation Task Force in 2007 by the Radiology Society of North America, Society of Interventional Radiologists, and Cardiovascular and Interventional Radiological Society of Europe. The Task Force’s mandate is to improve patient care by guiding the implementation of simulation in IR . The Food and Drug Administration is another institution driving the adoption of simulation training by stipulating that physicians must undergo proficiency training on a simulator before performing carotid artery stenting (CAS) .
Historically, simulation in medical education started with the widespread use of standardized patients and animal laboratories . Pigs are widely used for learning vascular and nonvascular interventional procedures guided by fluoroscopy, endoscopy, or cross-sectional imaging . This review paper will not address these types of medical simulation but instead will focus on technologies and devices used in IR simulation training. Some of the earliest technologies used in IR simulation training were computer-based training modules such as Radiology Society of North America’s Medical Imaging Resource Centre and AuntMinnie.com’s case of the day . Nowadays, augmentative reality simulators such as the VIST-Lab endovascular simulator by Mentice and computer-assisted mannequins are available . The sections in this paper will address the following questions: what skills can be taught with simulation; what types of commercially available simulators exist for training IR skills, and what is their educational validity; and what assessment tools can be used to evaluate the skills trained with simulation?
Section 1: Skills Training
Clinical skills can be broadly categorized as either procedural or nonprocedural skills. A growing body of literature shows that simulation can be used to teach both kinds of skills. Procedural skills are defined as practical physical skills performed by a physician to complete a medical procedure. Conversely, nonprocedural skills, which are just as integral to medical practice, include interpersonal, cognitive, and personal resource skills. The following subsections detail the procedural and nonprocedural skills that can be trained with simulation.
Subsection A: Procedural Skills
Vascular Skills
Seldinger technique
The Seldinger technique is an essential skill in vascular IR. Johnson et al. compared IR resident’s Seldinger technique performance in a patient procedure after clinical or clinical and simulation training on the ImaGiNe Seldinger augmented reality simulator . Results showed that the group that got simulation training tended to perform better than the group with just clinical training ( Figs 1, 2 ).
Get Radiology Tree app to read full this article<
Cannulation
Get Radiology Tree app to read full this article<
Catheterization
Get Radiology Tree app to read full this article<
Angiography
Get Radiology Tree app to read full this article<
Angioplasty
Get Radiology Tree app to read full this article<
Stenting
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Nonvascular Skills
Ultrasound
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Fluoroscopy-guided lumbar puncture
Get Radiology Tree app to read full this article<
Percutaneous noncontinuous fluoroscopy-guided computed tomography (CT) procedures
Get Radiology Tree app to read full this article<
Contrast reaction, sedation, and analgesia management
Get Radiology Tree app to read full this article<
Subsection B: Nonprocedural Skills
Get Radiology Tree app to read full this article<
Crisis Resource Management (CRM)
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Task Prioritization
Get Radiology Tree app to read full this article<
Section 2: Technology
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Subsection A: Virtual and Augmented Reality
Ultrasim (MedSim)
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
ORCAMP (Orzone)
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Simsuite (Medical Simulation Corporation)
Get Radiology Tree app to read full this article<
VIST-Lab (Mentice)
Get Radiology Tree app to read full this article<
ANGIO Mentor (Simbionix)
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Subsection B: Computer-Based Simulation
Nightshift
Get Radiology Tree app to read full this article<
Contrast Reaction Management
Get Radiology Tree app to read full this article<
Subsection C: Computer-assisted Mannequins
SimMan (Laerdal)
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
PediaSIM (CAE Healthcare)
Get Radiology Tree app to read full this article<
Patient simulator (Medsim-Eagle simulation)
Get Radiology Tree app to read full this article<
Subsection D: Phantoms/Part-task trainers
Transvaginal ultrasound simulation model (Blue Phantom)
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Central line torso and arm models (Blue Phantom)
Get Radiology Tree app to read full this article<
Soft tissue biopsy ultrasound training block model (Blue Phantom)
Get Radiology Tree app to read full this article<
Section 3: Assessment Tools
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
Procedural Checklists
Get Radiology Tree app to read full this article<
Global Rating Scales
Get Radiology Tree app to read full this article<
Surveys
Get Radiology Tree app to read full this article<
Pre- and Post-tests
Get Radiology Tree app to read full this article<
Time-action Analysis
Get Radiology Tree app to read full this article<
Error Analysis
Get Radiology Tree app to read full this article<
Simulator Metrics
Get Radiology Tree app to read full this article<
Conclusion
Get Radiology Tree app to read full this article<
Get Radiology Tree app to read full this article<
References
1. Issenberg S.B.: The scope of simulation-based healthcare education. Simul Healthc 2006; 1: pp. 203-208.
2. Desser T.S.: Simulation-based training: the next revolution in radiology education?. J Am Coll Radiol 2007; 4: pp. 816-824.
3. Rochlen L.R., Housey M., Gannon I., et. al.: A survey of simulation utilization in anesthesiology residency programs in the United States. A A Case Rep 2016; 6: pp. 335-342.
4. Sanders A., Douglas Wilson R.: Simulation training in obstetrics and gynaecology residency programs in Canada. J Obstet Gynaecol Can 2015; 37: pp. 1025-1032.
5. Okuda Y., Bond W., Bonfante G., et. al.: National growth in simulation training within emergency medicine residency programs, 2003–2008. Acad Emerg Med 2008; 15: pp. 1113-1116.
6. Gould D., Patel A., Becker G., et. al.: SIR/RSNA/CIRSE Joint Medical Simulation Task Force strategic plan: executive summary. Cardiovasc Intervent Radiol 2007; 30: pp. 551-554.
7. U.S. Food and Drug Administration : Center for Devices and Radiological Health, Medical Devices Advisory Committee, Circulatory System Devices Panel meeting. Available at http://www.fda.gov/ohrms/dockets/ac/04/transcripts/4033t1.htm
8. Rosen K.R., McBride J.M., Drake R.L.: The use of simulation in medical education to enhance students’ understanding of basic sciences. Med Teach 2009; 31: pp. 842-846.
9. Dondelinger R., Ghysels M., Brisbois D., et. al.: Relevant radiological anatomy of the pig as a training model in interventional radiology. Eur Radiol 1998; 8: pp. 1254-1273.
10. Mentice : VIST-LAB with VIST G5—simulation training. Available at http://www.mentice.com/vist-lab-with-vist-g5
11. Johnson S.J., Guediri S.M., Kilkenny C., et. al.: Development and validation of a virtual reality simulator: human factors input to interventional radiology training. Hum Factors 2011; 53: pp. 612-625.
12. Narra P., Kuban J., Grandpre L.E., et. al.: Videoscopic phantom-based angiographic simulation: effect of brief angiographic simulator practice on vessel cannulation times. J Vasc Interv Radiol 2009; 20: pp. 1215-1223.
13. Chaer R.A., Derubertis B.G., Lin S.C., et. al.: Simulation improves resident performance in catheter-based intervention: results of a randomized, controlled study. Ann Surg 2006; 244: pp. 343-352.
14. Bagai A., O’Brien S., Al Lawati H., et. al.: Mentored simulation training improves procedural skills in cardiac catheterization: a randomized, controlled pilot study. Circ Cardiovasc Interv 2012; 5: pp. 672-679.
15. Jensen U.J., Jensen J., Olivecrona G., et. al.: The role of a simulator-based course in coronary angiography on performance in real life cath lab. BMC Med Educ 2014; 14: pp. 49.
16. Patel A.A., Gould D.A.: Simulators in interventional radiology training and evaluation: a paradigm shift is on the horizon. J Vasc Interv Radiol 2006; 17: pp. S163-S173.
17. Klass D., Tam M.D., Cockburn J., et. al.: Training on a vascular interventional simulator: an observational study. Eur Radiol 2008; 18: pp. 2874-2878.
18. Coates P.J., Zealley I.A., Chakraverty S.: Endovascular simulator is of benefit in the acquisition of basic skills by novice operators. J Vasc Interv Radiol 2010; 21: pp. 130-134.
19. Hseino H., Nugent E., Lee M.J., et. al.: Skills transfer after proficiency-based simulation training in superficial femoral artery angioplasty. Simul Healthc 2012; 7: pp. 274-281.
20. Dayal R., Faries P.L., Lin S.C., et. al.: Computer simulation as a component of catheter-based training. J Vasc Surg 2004; 40: pp. 1112-1117.
21. Aggarwal R., Black S.A., Hance J.R., et. al.: Virtual reality simulation training can improve inexperienced surgeons’ endovascular skills. Eur J Vasc Endovasc Surg 2006; 31: pp. 588-593.
22. Glaiberman C.B., 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: pp. 1366-1371.
23. Lee J.T., Qiu M., Teshome M., et. al.: The utility of endovascular simulation to improve technical performance and stimulate continued interest of preclinical medical students in vascular surgery. J Surg Educ 2009; 66: pp. 367-373.
24. Powell D.K., Jamison D.K., Silberzweig J.E.: An endovascular simulation exercise among radiology residents: comparison of simulation performance with and without practice. Clin Imaging 2015; 39: pp. 1080-1085.
25. Willaert W., Aggarwal R., Harvey K., et. al.: Efficient implementation of patient-specific simulated rehearsal for the carotid artery stenting procedure: part-task rehearsal. Eur J Vasc Endovasc Surg 2011; 42: pp. 158-166.
26. Willaert W.I., Aggarwal R., Van Herzeele I., et. al.: Patient-specific endovascular simulation influences interventionalists performing carotid artery stenting procedures. Eur J Vasc Endovasc Surg 2011; 41: pp. 492-500.
27. Willaert W.I., Aggarwal R., Daruwalla F., et. al.: Simulated procedure rehearsal is more effective than a preoperative generic warm-up for endovascular procedures. Ann Surg 2012; 255: pp. 1184-1189.
28. 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: pp. 455-461.
29. Monsky W.L., Levine D., Mehta T.S., et. al.: Using a sonographic simulator to assess residents before overnight call. AJR Am J Roentgenol 2002; 178: pp. 35-39.
30. Ahmad R., Alhashmi G., Ajlan A., et. al.: Impact of high-fidelity transvaginal ultrasound simulation for radiology on residents’ performance and satisfaction. Acad Radiol 2015; 22: pp. 234-239.
31. Mendiratta-Lala M., Williams T., de Quadros N., et. al.: The use of a simulation center to improve resident proficiency in performing ultrasound-guided procedures. Acad Radiol 2010; 17: pp. 535-540.
32. Andreatta P., Chen Y., Marsh M., et. al.: Simulation-based training improves applied clinical placement of ultrasound-guided PICCs. Support Care Cancer 2011; 19: pp. 539-543.
33. Faulkner A.R., Bourgeois A.C., Bradley Y.C., et. al.: Simulation-based educational curriculum for fluoroscopically guided lumbar puncture improves operator confidence and reduces patient dose. Acad Radiol 2015; 22: pp. 668-673.
34. Mendiratta-Lala M., Williams T.R., Mendiratta V., et. al.: Simulation center training as a means to improve resident performance in percutaneous noncontinuous CT-guided fluoroscopic procedures with dose reduction. AJR Am J Roentgenol 2015; 204: pp. W376-W383.
35. Bartlett M.J., Bynevelt M.: Acute contrast reaction management by radiologists: a local audit study. Australas Radiol 2003; 47: pp. 363-367.
36. Chew F.S.: Section editor’s notebook: sedation simulation. AJR Am J Roentgenol 2013; 201: pp. 940.
37. Medina L.S., Racadio J.M., Schwid H.A.: Computers in radiology. The sedation, analgesia, and contrast media computerized simulator: a new approach to train and evaluate radiologists’ responses to critical incidents. Pediatr Radiol 2000; 30: pp. 299-305.
38. Sarwani N., Tappouni R., Flemming D.: Use of a simulation laboratory to train radiology residents in the management of acute radiologic emergencies. AJR Am J Roentgenol 2012; 199: pp. 244-251.
39. Pfeifer K., Staib L., Arango J., et. al.: High-fidelity contrast reaction simulation training: performance comparison of faculty, fellows, and residents. J Am Coll Radiol 2016; 13: pp. 81-87.
40. Tubbs R.J., Murphy B., Mainiero M.B., et. al.: High-fidelity medical simulation as an assessment tool for radiology residents’ acute contrast reaction management skills. J Am Coll Radiol 2009; 6: pp. 582-587.
41. Wang C.L., Schopp J.G., Petscavage J.M., et. al.: Prospective randomized comparison of standard didactic lecture versus high-fidelity simulation for radiology resident contrast reaction management training. AJR Am J Roentgenol 2011; 196: pp. 1288-1295.
42. Picard M., Curry N., Collins H., et. al.: Comparison of high-fidelity simulation versus didactic instruction as a reinforcement intervention in a comprehensive curriculum for radiology trainees in learning contrast reaction management: does it matter how we refresh?. Acad Radiol 2015; 22: pp. 1268-1276.
43. Wang C.L., Schopp J.G., Kani K., et. al.: Prospective randomized study of contrast reaction management curricula: computer-based interactive simulation versus high-fidelity hands-on simulation. Eur J Radiol 2013; 82: pp. 2247-2252.
44. Tofil N.M., White M.L., Grant M., et. al.: Severe contrast reaction emergencies high-fidelity simulation training for radiology residents and technologists in a children’s hospital. Acad Radiol 2010; 17: pp. 934-940.
45. Niell B.L., Kattapuram T., Halpern E.F., et. al.: Prospective analysis of an interprofessional team training program using high-fidelity simulation of contrast reactions. AJR Am J Roentgenol 2015; 204: pp. W670-W676.
46. Walker S.T., Sevdalis N., McKay A., et. al.: Unannounced in situ simulations: integrating training and clinical practice. BMJ Qual Saf 2013; 22: pp. 453-458.
47. Sica G.T., Barron D.M., Blum R., et. al.: Computerized realistic simulation: a teaching module for crisis management in radiology. AJR Am J Roentgenol 1999; 172: pp. 301-304.
48. Larkin C., Valand R., Syrysko P., et. al.: “Night shift”: a task simulation to improve on-call prioritisation, self-management. Commun Route Plan Skills 2014; pp. 59-62.
49. Dawson S.: Procedural simulation: a primer. Radiology 2006; 241: pp. 17-25.
50. Neequaye S.K., Aggarwal R., Van Herzeele I., et. al.: Endovascular skills training and assessment. J Vasc Surg 2007; 46: pp. 1055-1064.
51. ORCAMP : Orzone. Available at https://www.orzone.com/simulators
52. Rudarakanchana N., Van Herzeele I., Bicknell C.D., et. al.: Endovascular repair of ruptured abdominal aortic aneurysm: technical and team training in an immersive virtual reality environment. Cardiovasc Intervent Radiol 2014; 37: pp. 920-927.
53. Dawson D.L., Meyer J., Lee E.S., et. al.: Training with simulation improves residents’ endovascular procedure skills. J Vasc Surg 2007; 45: pp. 149-154.
54. Berry M., Lystig T., Reznick R., et. al.: Assessment of a virtual interventional simulator trainer. J Endovasc Ther 2006; 13: pp. 237-243.
55. Hsu J.H., Younan D., Pandalai S., et. al.: Use of computer simulation for determining endovascular skill levels in a carotid stenting model. J Vasc Surg 2004; 40: pp. 1118-1125.
56. ANGIO Mentor : ANGIO MENTOR. Available at http://simbionix.com/simulators/angio-mentor/
57. Shames M.L., DallaRosa J.V., Brannick M.T.: Validation of a novel virtual basic skills simulation model. J Vasc Surg 2015; 61: pp. 99S.
58. Petscavage J.M., Wang C.L., Schopp J.G., et. al.: Cost analysis and feasibility of high-fidelity simulation based radiology contrast reaction curriculum. Acad Radiol 2011; 18: pp. 107-112.
59. Phantom B.: General pathology transvaginal ultrasound training model. Available at http://www.bluephantom.com/product/General-Pathology-Transvaginal-Ultrasound-Training-Model.aspx?cid=406
60. Phantom B.: Gen II ultrasound central line training model—Brand NEW. Available at https://www.bluephantom.com/product/Gen-II-Ultrasound-Central-Line-Training-Model_Brand-NEW.aspx?cid=414
61. Phantom B.: Gen II PICC with IV & arterial line vascular access ultrasound trainer. Available at https://www.bluephantom.com/product/Gen-II-PICC-with-IV-AND-Arterial-Line-Vascular-Access-Ultrasound-Trainer.aspx?cid=407
62. Miller G.E.: The assessment of clinical skills/competence/performance. Acad Med 1990; 65: pp. S63-S67.
63. Ahmed K., Keeling A.N., Fakhry M., et. al.: Role of virtual reality simulation in teaching and assessing technical skills in endovascular intervention. J Vasc Interv Radiol 2010; 21: pp. 55-66.
64. Boulet J.R., Murray D.J.: Simulation-based assessment in anesthesiology. Anesthesiology 2010; 112: pp. 1041-1052.
65. Van Herzeele I., Aggarwal R., Malik I., et. al.: Validation of video-based skill assessment in carotid artery stenting. Eur J Vasc Endovasc Surg 2009; 38: pp. 1-9.
66. Seagull F.J., Rooney D.M.: Filling a void: developing a standard subjective assessment tool for surgical simulation through focused review of current practices. Surgery 2014; 156: pp. 718-722.
67. Boulet J.R., Murray D.: Review article: assessment in anesthesiology education. Can J Anaesth 2012; 59: pp. 182-192.
68. Bakker N.H., Tanase D., Reekers J.A., et. al.: Evaluation of vascular and interventional procedures with time–action analysis: a pilot study. J Vasc Interv Radiol 2002; 13: pp. 483-488.
69. Duncan J.R., Glaiberman C.B.: Analysis of simulated angiographic procedures: part 1—capture and presentation of audio and video recordings. J Vasc Interv Radiol 2006; 17: pp. 1979-1989.
70. Duncan J.R., Kline B., Glaiberman C.B.: Analysis of simulated angiographic procedures. Part 2: extracting efficiency data from audio and video recordings. J Vasc Interv Radiol 2007; 18: pp. 535-544.
71. Johnson S.J., Hunt C.M., Woolnough H.M., et. al.: Virtual reality, ultrasound-guided liver biopsy simulator: development and performance discrimination. Br J Radiol 2012; 85: pp. 555-561.
72. Luboz V., Zhang Y., Johnson S., et. al.: ImaGiNe Seldinger: first simulator for Seldinger technique and angiography training. Comput Methods Programs Biomed 2013; 111: pp. 419-434.
73. Mentice : Carotid intervention procedural training dodule. Available at http://www.mentice.com/carotid-intervention
74. MedSim : UltraSim. Available at http://www.medsim.com/ultrasim_73_4064402069.pdf
75. Laerdal : SimMan. Available at http://www.laerdal.com/ca/doc/86/SimMan