Advertisement

Synthetic Replica for Training in Microsurgical Anastomosis: An Important Frontier in Neurosurgical Education

  • Rudy J. Rahme
  • Chandan Krishna
  • Mithun G. Sattur
  • Rami James N. Aoun
  • Matthew E. Welz
  • Aman Gupta
  • Bernard R. Bendok
Chapter
Part of the Comprehensive Healthcare Simulation book series (CHS)

Abstract

Medical education has evolved through the years, moving away from the Halstedian apprenticeship model. The medical governing bodies involved in medical graduate education have established a set of rulings and recommendations focused on improving patient safety and curbing resident fatigue including limiting work hours to 80 h a week. In addition to duty hour regulations, decreasing volumes and dilution of surgical cases among an increasing number of tertiary care centers have raised concern about the ability of residents to achieve appropriate levels of competency by the time of graduation. Therefore, simulation has seen an increased role in education in the last decade.

Microsurgical anastomosis is one of the most complex and technically challenging surgical skills. While the need for microanastomosis has decreased due to a multitude of factors, it is still a required skill set in various specialties including neurosurgery, otolaryngology, vascular, and plastic surgery. Multiple simulation models have been devised to allow for better training and improving resident dexterity in microanastomosis. These include cadavers, both animal and human, live animal models, and synthetic models. Each model has its benefits and disadvantages. While cadavers are arguably the most realistic, they are expensive and require proper labs and disposal methods. Live animal models also require proper training and adherence to institutional protocols. They also raise animal welfare ethical questions. Synthetic models with silicone vessels while less realistic offer the best currently available alternative. They are widely available, can be cheap to acquire, and do not require special setups.

In addition to the models, assessment tools are essential for the success of simulation in education. Multiple assessment scales have been used, but only a few have been validated. The Northwestern Objective Microanastomosis Assessment Tool (NOMAT) was developed and validated specifically for microanastomosis for neurosurgical education and has been used by various neurosurgical societies in various national and international meetings.

While there is no current optimal model and assessment scale for microsurgical anastomosis simulation, huge strides forward have been made in the last decade to allow for the adoption of simulation as an acceptable and adequate educational tool.

Keywords

Simulation Microsurgical Anastomosis NOMAT Duty hours Organized neurosurgery Validity Assessment scale 

References

  1. 1.
    Carter BN. The fruition of Halsted’s concept of surgical training. Surgery. 1952;32(3):518–27.PubMedGoogle Scholar
  2. 2.
    Fabricant PD, Dy CJ, Dare DM, Bostrom MP. A narrative review of surgical resident duty hour limits: where do we go from here? J Grad Med Educ. 2013;5(1):19–24.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Accreditation Council for Graduate Medical Education. Report of the ACGME work group on resident duty hours: Accreditation Council for Graduate Medical Education. Chicago: Accreditation Council for Graduate Medical Education;2002.Google Scholar
  4. 4.
    Accreditation Council for Graduate Medical Education: Accreditation Council for Graduate Medical Education. Statement of justification/impact for the final approval of common standards related to resident duty hours. Chicago: Accreditation Council for Graduate Medical Education;2002.Google Scholar
  5. 5.
    Ericsson KA, Krampe RT, Tesch-Römer C. The role of deliberate practice in the Acquisition of Expert Performance. Psychol Rev. 1993;100(3):363–406.CrossRefGoogle Scholar
  6. 6.
    Aoun SG, El Ahmadieh TY, El Tecle NE, et al. A pilot study to assess the construct and face validity of the Northwestern Objective Microanastomosis Assessment Tool. J Neurosurg. 2015;123(1):103–9.CrossRefPubMedGoogle Scholar
  7. 7.
    Balasundaram I, Aggarwal R, Darzi LA. Development of a training curriculum for microsurgery. Br J Oral Maxillofac Surg. 2010;48(8):598–606.CrossRefPubMedGoogle Scholar
  8. 8.
    Harrop J, Lobel DA, Bendok B, Sharan A, Rezai AR. Developing a neurosurgical simulation-based educational curriculum: an overview. Neurosurgery. 2013;73(Suppl 1):25–9.CrossRefPubMedGoogle Scholar
  9. 9.
    Zammar SG, Hamade YJ, Aoun RJ, et al. The cognitive and technical skills impact of the Congress of Neurological Surgeons simulation curriculum on neurosurgical trainees at the 2013 Neurological Society of India meeting. World Neurosurg. 2015;83(4):419–23.CrossRefPubMedGoogle Scholar
  10. 10.
    Fargen KM, Arthur AS, Bendok BR, et al. Experience with a simulator-based angiography course for neurosurgical residents: beyond a pilot program. Neurosurgery. 2013;73(Suppl 1):46–50.CrossRefPubMedGoogle Scholar
  11. 11.
    Harrop J, Rezai AR, Hoh DJ, Ghobrial GM, Sharan A. Neurosurgical training with a novel cervical spine simulator: posterior foraminotomy and laminectomy. Neurosurgery. 2013;73(Suppl 1):94–9.CrossRefPubMedGoogle Scholar
  12. 12.
    Ghobrial GM, Balsara K, Maulucci CM, et al. Simulation training curricula for neurosurgical residents: cervical foraminotomy and durotomy repair modules. World Neurosurg. 2015;84(3):751–755 e751–7.Google Scholar
  13. 13.
    Lobel DA, Elder JB, Schirmer CM, Bowyer MW, Rezai AR. A novel craniotomy simulator provides a validated method to enhance education in the management of traumatic brain injury. Neurosurgery. 2013;73(Suppl 1):57–65.CrossRefPubMedGoogle Scholar
  14. 14.
    Duvivier RJ, van Dalen J, Muijtjens AM, Moulaert VR, van der Vleuten CP, Scherpbier AJ. The role of deliberate practice in the acquisition of clinical skills. BMC Med Educ. 2011;11:101.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Pines AR, Alghoul MS, Hamade YJ, et al. Assessment of the interrater reliability of the congress of neurological surgeons microanastomosis assessment scale. Oper Neurosurg. 2016;Publish Ahead of Print.Google Scholar
  16. 16.
    McCaslin AF, Aoun SG, Batjer HH, Bendok BR. Enhancing the utility of surgical simulation: from proficiency to automaticity. World Neurosurg. 2011;76(6):482–4.CrossRefPubMedGoogle Scholar
  17. 17.
    Prabhu A, Smith W, Yurko Y, Acker C, Stefanidis D. Increased stress levels may explain the incomplete transfer of simulator-acquired skill to the operating room. Surgery. 2010;147(5):640–5.CrossRefPubMedGoogle Scholar
  18. 18.
    Stefanidis D, Scerbo MW, Montero PN, Acker CE, Smith WD. Simulator training to automaticity leads to improved skill transfer compared with traditional proficiency-based training: a randomized controlled trial. Ann Surg. 2012;255(1):30–7.CrossRefPubMedGoogle Scholar
  19. 19.
    Singh H, Kalani M, Acosta-Torres S, El Ahmadieh TY, Loya J, Ganju A. History of simulation in medicine: from Resusci Annie to the Ann Myers Medical Center. Neurosurgery. 2013;73(Suppl 1):9–14.CrossRefPubMedGoogle Scholar
  20. 20.
    Davis PK, Winnefeld JA, Bankes SC, Kahan JP. Analytic War Gaming with the RAND Strategy Assessment System (RSAS). 1987. http://www.rand.org/pubs/research_briefs/RB7801.html.
  21. 21.
    Barrows HS. An overview of the uses of standardized patients for teaching and evaluating clinical skills. AAMC Acad Med. 1993;68(6):443–51; discussion 451-443.Google Scholar
  22. 22.
    Swanson DB, van der Vleuten CP. Assessment of clinical skills with standardized patients: state of the art revisited. Teach Learn Med. 2013;25(Suppl 1):S17–25.CrossRefPubMedGoogle Scholar
  23. 23.
    Mashiko T, Otani K, Kawano R, et al. Development of three-dimensional hollow elastic model for cerebral aneurysm clipping simulation enabling rapid and low cost prototyping. World Neurosurg. 2015;83(3):351–61.CrossRefPubMedGoogle Scholar
  24. 24.
    Oishi M, Fukuda M, Hiraishi T, Yajima N, Sato Y, Fujii Y. Interactive virtual simulation using a 3D computer graphics model for microvascular decompression surgery. J Neurosurg. 2012;117(3):555–65.CrossRefPubMedGoogle Scholar
  25. 25.
    Delorme S, Laroche D, DiRaddo R, Del Maestro RF. NeuroTouch: a physics-based virtual simulator for cranial microneurosurgery training. Neurosurgery. 2012;71(1 Suppl Operative):32–42.PubMedGoogle Scholar
  26. 26.
    Nguyen N, Eagleson R, Boulton M, Realism d RS. Criterion validity, and training capability of simulated diagnostic cerebral angiography. Stud Health Technol Inform. 2014;196:297–303.PubMedGoogle Scholar
  27. 27.
    Spiotta AM, Rasmussen PA, Masaryk TJ, Benzel EC, Schlenk R. Simulated diagnostic cerebral angiography in neurosurgical training: a pilot program. J Neurointerv Surg. 2013;5(4):376–81.CrossRefPubMedGoogle Scholar
  28. 28.
    Luciano CJ, Banerjee PP, Sorenson JM, et al. Percutaneous spinal fixation simulation with virtual reality and haptics. Neurosurgery. 2013;72(Suppl 1):89–96.CrossRefPubMedGoogle Scholar
  29. 29.
    Crosby NL, Clapson JB, Buncke HJ, Newlin L. Advanced non-animal microsurgical exercises. Microsurgery. 1995;16(9):655–8.CrossRefPubMedGoogle Scholar
  30. 30.
    Lascar I, Totir D, Cinca A, et al. Training program and learning curve in experimental microsurgery during the residency in plastic surgery. Microsurgery. 2007;27(4):263–7.CrossRefPubMedGoogle Scholar
  31. 31.
    Blackwell KE, Brown MT, Gonzalez D. Overcoming the learning curve in microvascular head and neck reconstruction. Arch Otolaryngol Head Neck Surg. 1997;123(12):1332–5.CrossRefPubMedGoogle Scholar
  32. 32.
    Hui KC, Zhang F, Shaw WW, et al. Learning curve of microvascular venous anastomosis: a never ending struggle? Microsurgery. 2000;20(1):22–4.CrossRefPubMedGoogle Scholar
  33. 33.
    Szalay D, MacRae H, Regehr G, Reznick R. Using operative outcome to assess technical skill. Am J Surg. 2000;180(3):234–7.CrossRefPubMedGoogle Scholar
  34. 34.
    Buis DR, Buis CR, Feller RE, Mandl ES, Peerdeman SM. A basic model for practice of intracranial microsurgery. Surg Neurol. 2009;71(2):254–6.CrossRefPubMedGoogle Scholar
  35. 35.
    Matsumura N, Hayashi N, Hamada H, Shibata T, Horie Y, Endo S. A newly designed training tool for microvascular anastomosis techniques: microvascular practice card. Surg Neurol. 2009;71(5):616–20.CrossRefPubMedGoogle Scholar
  36. 36.
    Kim BJ, Kim ST, Jeong YG, Lee WH, Lee KS, Paeng SH. An efficient microvascular anastomosis training model based on chicken wings and simple instruments. J Cerebrovasc Endovasc Neurosurg. 2013;15(1):20–5.CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Abla AA, Uschold T, Preul MC, Zabramski JM. Comparative use of turkey and chicken wing brachial artery models for microvascular anastomosis training. J Neurosurg. 2011;115(6):1231–5.CrossRefPubMedGoogle Scholar
  38. 38.
    Olabe J, Olabe J, Roda JM, Sancho V. Human cadaver brain infusion skull model for neurosurgical training. Surg Neurol Int. 2011;2:54.CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Olabe J, Olabe J, Sancho V. Human cadaver brain infusion model for neurosurgical training. Surg Neurol. 2009;72(6):700–2.CrossRefPubMedGoogle Scholar
  40. 40.
    Belykh E, Lei T, Safavi-Abbasi S, et al. Low-flow and high-flow neurosurgical bypass and anastomosis training models using human and bovine placental vessels: a histological analysis and validation study. J Neurosurg. 2016;125(4):915–28.CrossRefPubMedGoogle Scholar
  41. 41.
    Hicdonmez T, Hamamcioglu MK, Tiryaki M, Cukur Z, Cobanoglu S. Microneurosurgical training model in fresh cadaveric cow brain: a laboratory study simulating the approach to the circle of Willis. Surg Neurol. 2006;66(1):100–4. discussion 104CrossRefPubMedGoogle Scholar
  42. 42.
    Colpan ME, Slavin KV, Amin-Hanjani S, Calderon-Arnuphi M, Charbel FT. Microvascular anastomosis training model based on a Turkey neck with perfused arteries. Neurosurgery. 2008;62(5 Suppl 2):ONS407–410; discussion ONS410–401.Google Scholar
  43. 43.
    Hino A. Training in microvascular surgery using a chicken wing artery. Neurosurgery. 2003;52(6):1495–7; discussion 1497–8.Google Scholar
  44. 44.
    Schoffl H, Hager D, Hinterdorfer C, et al. Pulsatile perfused porcine coronary arteries for microvascular training. Ann Plast Surg. 2006;57(2):213–6.CrossRefPubMedGoogle Scholar
  45. 45.
    Inoue T, Tsutsumi K, Saito K, Adachi S, Tanaka S, Kunii N. Training of A3-A3 side-to-side anastomosis in a deep corridor using a box with 6.5-cm depth: technical note. Surg Neurol. 2006;66(6):638–41.CrossRefPubMedGoogle Scholar
  46. 46.
    Dumestre D, Yeung JK, Temple-Oberle C. Evidence-based microsurgical skills acquisition series part 2: validated assessment instruments – a systematic review. J Surg Educ. 2015;72(1):80–9.CrossRefPubMedGoogle Scholar
  47. 47.
    Garrett HE Jr. A human cadaveric circulation model. J Vasc Surg. 2001;33(5):1128–30.CrossRefPubMedGoogle Scholar
  48. 48.
    Aboud E, Aboud G, Al-Mefty O, et al. “Live cadavers” for training in the management of intraoperative aneurysmal rupture. J Neurosurg. 2015;123(5):1339–46.CrossRefPubMedGoogle Scholar
  49. 49.
    Inoue T, Tsutsumi K, Adachi S, Tanaka S, Saito K, Kunii N. Effectiveness of suturing training with 10-0 nylon under fixed and maximum magnification (x 20) using desk type microscope. Surg Neurol. 2006;66(2):183–7.CrossRefPubMedGoogle Scholar
  50. 50.
    Olabe J, Olabe J. Microsurgical training on an in vitro chicken wing infusion model. Surg Neurol. 2009;72(6):695–9.CrossRefPubMedGoogle Scholar
  51. 51.
    Hwang G, Oh CW, Park SQ, Sheen SH, Bang JS, Kang HS. Comparison of different microanastomosis training models : model accuracy and practicality. J Korean Neurosurg Soc. 2010;47(4):287–90.CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Kawashima M, Rhoton AL Jr, Tanriover N, Ulm AJ, Yasuda A, Fujii K. Microsurgical anatomy of cerebral revascularization. Part I: anterior circulation. J Neurosurg. 2005;102(1):116–31.CrossRefPubMedGoogle Scholar
  53. 53.
    Ilie V, Ilie V, Ghetu N, Popescu S, Grosu O, Pieptu D. Assessment of the microsurgical skills: 30 minutes versus 2 weeks patency. Microsurgery. 2007;27(5):451–4.CrossRefPubMedGoogle Scholar
  54. 54.
    Onoda S, Kimata Y, Matsumoto K. Iliolumbar vein as a training model for microsurgical end-to-side anastomosis. J Craniofac Surg. 2016;27(3):767–8.CrossRefPubMedGoogle Scholar
  55. 55.
    Rayan B, Rayan GM. Microsurgery training card: a practical, economic tool for basic techniques. J Reconstr Microsurg. 2006;22(4):273–5; discussion 276.Google Scholar
  56. 56.
    Dumestre D, Yeung JK, Temple-Oberle C. Evidence-based microsurgical skill-acquisition series part 1: validated microsurgical models – a systematic review. J Surg Educ. 2014;71(3):329–38.CrossRefPubMedGoogle Scholar
  57. 57.
    Taffinder N, Smith SG, Huber J, Russell RC, Darzi A. The effect of a second-generation 3D endoscope on the laparoscopic precision of novices and experienced surgeons. Surg Endosc. 1999;13(11):1087–92.CrossRefPubMedGoogle Scholar
  58. 58.
    Datta V, Chang A, Mackay S, Darzi A. The relationship between motion analysis and surgical technical assessments. Am J Surg. 2002;184(1):70–3.CrossRefPubMedGoogle Scholar
  59. 59.
    Datta V, Mackay S, Mandalia M, Darzi A. The use of electromagnetic motion tracking analysis to objectively measure open surgical skill in the laboratory-based model. J Am Coll Surg. 2001;193(5):479–85.CrossRefPubMedGoogle Scholar
  60. 60.
    Grober ED, Hamstra SJ, Wanzel KR, et al. Validation of novel and objective measures of microsurgical skill: hand-motion analysis and stereoscopic visual acuity. Microsurgery. 2003;23(4):317–22.CrossRefPubMedGoogle Scholar
  61. 61.
    Ezra DG, Aggarwal R, Michaelides M, et al. Skills acquisition and assessment after a microsurgical skills course for ophthalmology residents. Ophthalmology. 2009;116(2):257–62.CrossRefPubMedGoogle Scholar
  62. 62.
    Saleh GM, Voyatzis G, Hance J, Ratnasothy J, Darzi A. Evaluating surgical dexterity during corneal suturing. Arch Ophthalmol. 2006;124(9):1263–6.CrossRefPubMedGoogle Scholar
  63. 63.
    Moulton CA, Dubrowski A, Macrae H, Graham B, Grober E, Reznick R. Teaching surgical skills: what kind of practice makes perfect? A randomized, controlled trial. Ann Surg. 2006;244(3):400–9.PubMedPubMedCentralGoogle Scholar
  64. 64.
    Nugent E, Joyce C, Perez-Abadia G, et al. Factors influencing microsurgical skill acquisition during a dedicated training course. Microsurgery. 2012;32(8):649–56.CrossRefPubMedGoogle Scholar
  65. 65.
    Temple CL, Ross DC. A new, validated instrument to evaluate competency in microsurgery: the University of Western Ontario Microsurgical Skills Acquisition/Assessment instrument [outcomes article]. Plast Reconstr Surg. 2011;127(1):215–22.CrossRefPubMedGoogle Scholar
  66. 66.
    Chan W, Niranjan N, Ramakrishnan V. Structured assessment of microsurgery skills in the clinical setting. J Plast Reconstr Aesthet Surg. 2010;63(8):1329–34.CrossRefPubMedGoogle Scholar
  67. 67.
    El Ahmadieh TY, Aoun SG, El Tecle NE, et al. A didactic and hands-on module enhances resident microsurgical knowledge and technical skill. Neurosurgery. 2013;73(Suppl 1):51–6.CrossRefPubMedGoogle Scholar
  68. 68.
    Belykh E, Byvaltsev V. Off-the-job microsurgical training on dry models: Siberian experience. World Neurosurg. 2014;82(1–2):20–4.CrossRefPubMedGoogle Scholar
  69. 69.
    Zammar SG, El Tecle NE, El Ahmadieh TY, et al. Impact of a vascular neurosurgery simulation-based course on cognitive knowledge and technical skills in European neurosurgical trainees. World Neurosurg. 2015;84(2):197–201.CrossRefPubMedGoogle Scholar
  70. 70.
    Ganju A, Aoun SG, Daou MR, et al. The role of simulation in neurosurgical education: a survey of 99 United States neurosurgery program directors. World Neurosurg. 2013;80(5):e1–8.CrossRefPubMedGoogle Scholar
  71. 71.
    Selden NR, Anderson VC, McCartney S, Origitano TC, Burchiel KJ, Barbaro NM. Society of Neurological Surgeons boot camp courses: knowledge retention and relevance of hands-on learning after 6 months of postgraduate year 1 training. J Neurosurg. 2013;119(3):796–802.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Rudy J. Rahme
    • 1
  • Chandan Krishna
    • 2
    • 4
    • 5
  • Mithun G. Sattur
    • 2
    • 4
    • 5
  • Rami James N. Aoun
    • 2
    • 4
    • 5
  • Matthew E. Welz
    • 2
    • 4
    • 5
  • Aman Gupta
    • 2
    • 4
    • 5
  • Bernard R. Bendok
    • 3
    • 4
    • 5
  1. 1.Department of NeurosurgeryNorthwestern Feinberg School and Medicine and McGaw Medical CenterChicagoUSA
  2. 2.Department of NeurosurgeryMayo ClinicPhoenixUSA
  3. 3.Department of Neurological Surgery, Otolaryngology, and RadiologyMayo ClinicPhoenixUSA
  4. 4.Precision Neurotherapeutics LabMayo ClinicPhoenixUSA
  5. 5.Neurosurgery Simulation and Innovation LabMayo ClinicPhoenixUSA

Personalised recommendations