Download PDF
J Reconstr Microsurg 2023; 39(04): 254-263
DOI: 10.1055/s-0041-1740957
Original Article

Simulating the IMA Recipient Site for DIEP Flap Surgery: A New Model for Dynamic Microsurgery Simulation with Real-Time Respiration and a Pilot Study

Natalia I. Ziolkowski
1   Department of Surgery, University of Toronto, Toronto, Ontario, Canada
,
Kimberly Z. Sun
2   Department of Surgery, Section of Plastics, Joseph Brant Memorial Hospital, Burlington, Ontario, Canada
,
Catherine McMillan
3   Department of Surgery, Division of Plastic & Reconstructive Surgery, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
,
Agnes Ryzynski
4   Sunnybrook Canadian Simulation Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
,
Laura Snell
3   Department of Surgery, Division of Plastic & Reconstructive Surgery, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
,
Joan E. Lipa
3   Department of Surgery, Division of Plastic & Reconstructive Surgery, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
› Author Affiliations
› Further Information
    Permissions and Reprints

Abstract

Background Breast reconstruction (BR) using autologous free flaps has been shown to have numerous psychosocial and quality-of-life benefits. Unfortunately, the microsurgical learning curve is quite steep due to some unique operative challenges. Currently, there is no realistic simulation model that captures real-life respiratory excursion and the depth of internal mammary vessels within the compact recipient site. The purpose of this study was to delineate intraoperative measurements of depth and motion, describe the resulting simulation model, and conduct a pilot study evaluating the simulator as an educational resource.

Methods This is a single-center, ethics-approved study. For the intraoperative measurements, all consecutive patients undergoing free flap BR using internal mammary vessels as recipients were recruited. Patient and intraoperative factors as well as intraoperative measurements were recorded. A dynamic model was developed based on intraoperative parameters. For the pilot study, plastic and reconstructive surgery trainees were recruited to complete a hand-sewn internal mammary artery (IMA) anastomosis using the new simulator and completed objective questionnaires pre- and postsimulation. Subjective feedback was recorded and themes determined.

Results Fifteen operative sites were analyzed. Flap pocket was found to be between 4 and 5 cm in depth with vertical excursion of 3.7 ± 1.0mm and a respiratory rate of 9 to 14 breaths/minute. Previous radiation, rib space, body mass index (BMI), blood pressure, heart rate, tidal volume, and respiratory rate showed no correlation to vessel depth/excursion. Laterality, rib space, BMI, radiation, vitals, and tidal volume had no correlation with vessel movement. Twenty-two trainees were included in the pilot. An increase in confidence and mixed results for anxiety was reported.

Conclusion This study reports a novel microsurgical simulation model that provides a realistic deep inferior epigastric perforator free flap BR IMA anastomosis experience. It replicates movement of vessels in situ with real-time respiratory excursion and similar physical structures of the internal mammary system. This model shows promising results for increased use in microsurgical education.

Keywords

anastomosis - internal mammary artery - simulation


Publication History

Received: 07 May 2021

Accepted: 10 November 2021

Article published online:
27 April 2022

© 2022. Thieme. All rights reserved.

Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 

  • References

  • 1 Healy C, Ramakrishnan V. Autologous microvascular breast reconstruction. Arch Plast Surg 2013; 40 (01) 3-10
    Article in Thieme ConnectPubMedGoogle Scholar
  • 2 Atisha D, Alderman AK, Lowery JC, Kuhn LE, Davis J, Wilkins EG. Prospective analysis of long-term psychosocial outcomes in breast reconstruction: two-year postoperative results from the Michigan Breast Reconstruction Outcomes Study. Ann Surg 2008; 247 (06) 1019-1028
    CrossrefPubMedGoogle Scholar
  • 3 Atisha DM, Tessiatore KM, Rushing CN, Dayicioglu D, Pusic A, Hwang S. A national snapshot of patient-reported outcomes comparing types of abdominal flaps for breast reconstruction. Plast Reconstr Surg 2019; 143 (03) 667-677
    CrossrefPubMedGoogle Scholar
  • 4 Chevray PM. Update on breast reconstruction using free TRAM, DIEP, and SIEA flaps. Semin Plast Surg 2004; 18 (02) 97-104
    Article in Thieme ConnectPubMedGoogle Scholar
  • 5 Nahabedian M. The internal mammary artery and vein as recipient vessels for microvascular breast reconstruction. Ann Plast Surg 2012; 68 (05) 537-538
    CrossrefPubMedGoogle Scholar
  • 6 Wallace CG, Shokrollahi K. Thoracodorsal or internal mammary recipient vessels for microvascular breast reconstruction?. Ann Plast Surg 2012; 68 (05) 536
    CrossrefPubMedGoogle Scholar
  • 7 Murray ACA, Rozen WM, Alonso-Burgos A, Ashton MW, Garcia-Tutor E, Whitaker IS. The anatomy and variations of the internal thoracic (internal mammary) artery and implications in autologous breast reconstruction: clinical anatomical study and literature review. Surg Radiol Anat 2012; 34 (02) 159-165
    CrossrefPubMedGoogle Scholar
  • 8 Singh M, Ziolkowski N, Ramachandran S, Myers SR, Ghanem AM. Development of a five-day basic microsurgery simulation training course: a cost analysis. Arch Plast Surg 2014; 41 (03) 213-217
    Article in Thieme ConnectPubMedGoogle Scholar
  • 9 Loh CYY, Wang AYL, Tiong VTY. et al. Animal models in plastic and reconstructive surgery simulation-a review. J Surg Res 2018; 221: 232-245
    CrossrefPubMedGoogle Scholar
  • 10 Pafitanis G, Ghanem AM, Myers S. Experimental Pork Belly: a simulation training model for intramuscular perforator dissection. Plast Reconstr Surg Glob Open 1674; 2018 (06) 1-6
    PubMedGoogle Scholar
  • 11 Pafitanis G, Cooper L, Hadjiandreou M, Ghanem A, Myers S. Microvascular anastomotic coupler application learning curve: a curriculum supporting further deliberate practice in ex-vivo simulation models. J Plast Reconstr Aesthet Surg 2019; 72 (02) 203-210
    CrossrefPubMedGoogle Scholar
  • 12 Pafitanis G, Hadjiandreou M, Miller R. et al. The use of mobile computing devices in microsurgery. Arch Plast Surg 2019; 46 (02) 102-107
    Article in Thieme ConnectPubMedGoogle Scholar
  • 13 Leung CCM, Ghanem AM, Tos P, Ionac M, Froschauer S, Myers SR. Towards a global understanding and standardisation of education and training in microsurgery. Arch Plast Surg 2013; 40 (04) 304-311
    Article in Thieme ConnectPubMedGoogle Scholar
  • 14 Evgeniou E, Walker H, Gujral S. The role of simulation in microsurgical training. J Surg Educ 2018; 75 (01) 171-181
    CrossrefPubMedGoogle Scholar
  • 15 Al-Bustani S, Halvorson EG. Status of microsurgical simulation training in plastic surgery: a survey of United States Program Directors. Ann Plast Surg 2016; 76 (06) 713-716
    CrossrefPubMedGoogle Scholar
  • 16 Zeng W, Gunderson KA, Sanchez RJ. et al. The Blue-Blood Porcine Chest Wall: a novel microsurgery training simulator for internal mammary vessel dissection and anastomosis. J Reconstr Microsurg 2021; 37 (04) 353-356
    Article in Thieme ConnectPubMedGoogle Scholar
  • 17 Nicholas RS, Madada-Nyakauru RN, Irri RA, Myers SR, Ghanem AM. Research priorities in light of current trends in microsurgical training: revalidation, simulation, cross-training, and standardisation. Arch Plast Surg 2014; 41 (03) 218-224
    Article in Thieme ConnectPubMedGoogle Scholar
  • 18 Ramachandran S, Ong YS, Chin AYH, Song IC, Ogden B, Tan BK. Stepwise training for reconstructive microsurgery: the journey to becoming a confident microsurgeon in Singapore. Arch Plast Surg 2014; 41 (03) 209-212
    Article in Thieme ConnectPubMedGoogle Scholar
  • 19 Nugent E, Joyce C, Perez-Abadia G. et al. Factors influencing microsurgical skill acquisition during a dedicated training course. Microsurgery 2012; 32 (08) 649-656
    CrossrefPubMedGoogle Scholar
  • 20 Rodriguez JR, Yañez R, Cifuentes I, Varas J, Dagnino B. Microsurgery workout: a novel simulation training curriculum based on nonliving models. Plast Reconstr Surg 2016; 138 (04) 739e-747e
    CrossrefPubMedGoogle Scholar
  • 21 Myers SR, Froschauer S, Akelina Y, Tos P, Kim JT, Ghanem AM. Microsurgery training for the twenty-first century. Arch Plast Surg 2013; 40 (04) 302-303
    Article in Thieme ConnectPubMedGoogle Scholar
  • 22 Masud D, Haram N, Moustaki M, Chow W, Saour S, Mohanna PN. Microsurgery simulation training system and set up: an essential system to complement every training programme. J Plast Reconstr Aesthet Surg 2017; 70 (07) 893-900
    CrossrefPubMedGoogle Scholar
  • 23 Marteau TM, Bekker H. The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). Br J Clin Psychol 1992; 31 (03) 301-306
    CrossrefPubMedGoogle Scholar
  • 24 Bhatti NI. Assessment of surgical skills and competency. Otolaryngol Clin North Am 2017; 50 (05) 959-965
    CrossrefPubMedGoogle Scholar
  • 25 Atlan M, Lellouch AG, Legagneux J, Chaouat M, Masquelet AC, Letourneur D. A new synthetic model for microvascular anastomosis training? A randomized comparative study between silicone and polyvinyl alcohol gelatin tubes. J Surg Educ 2018; 75 (01) 182-187
    CrossrefPubMedGoogle Scholar
  • 26 Ji C, Li R, Liang W, Chen Y, Zhang J. Plasticine model: an useful surgical training in plastic surgery. Aesthetic Plast Surg 2016; 40 (01) 174-181
    CrossrefPubMedGoogle Scholar
  • 27 Boczar D, Sisti A, Restrepo DJ. et al. The multifactorial contribution of publications in plastic surgery journals in microsurgery education. Ann Plast Surg 2020; 84 (02) 130-134
    CrossrefPubMedGoogle Scholar
  • 28 Shulzhenko NO, Zeng W, Albano NJ. et al. Multispecialty microsurgical course utilizing the blue-blood chicken thigh model significantly improves resident comfort, confidence, and attitudes in multiple domains. J Reconstr Microsurg 2020; 36 (02) 142-150
    Article in Thieme ConnectPubMedGoogle Scholar
  • 29 Perez-Abadia G, Janko M, Pindur L. et al. Frankfurt microsurgery course: the first 175 trainees. Eur J Trauma Emerg Surg 2017; 43 (03) 377-386
    CrossrefPubMedGoogle Scholar
  • 30 Ortiz R, Sood RF, Wilkens S, Gottlieb R, Chen NC, Eberlin KR. Longitudinal microsurgery laboratory training during hand surgery fellowship. J Reconstr Microsurg 2019; 35 (09) 640-645
    Article in Thieme ConnectPubMedGoogle Scholar
  • 31 Pavlidis I, Zavlin D, Khatri AR, Wesley A, Panagopoulos G, Echo A. Absence of stressful conditions accelerates dexterous skill acquisition in surgery. Sci Rep 2019; 9 (01) 1747
    CrossrefPubMedGoogle Scholar