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Results Of A Pilot Program Using Novel, 3-Dimensional Simulation Models Of Different Anatomical Locations For Training Of Vascular Exposure And Reconstruction
May Dvir, MD
1, Indrani Sen, MBBS
2, Sebastian Cifuentes Munoz, MD
3, Balázs Gasz, MD, PhD
4, Bernardo C. Mendes, MD
1, Jill J. Colglazier, MD
1, Todd E. Rasmussen, MD
1.
1Division of Vascular and Endovascular Surgery, Mayo Clinic, Rochester, MN, USA,
2Vascular and Endovascular Surgery, Mayo Clinic Health System, Eau Claire, WI, USA,
3Mayo Clinic Division of Trauma, Critical Care, and General Surgery, Rochester, MN, USA,
4Institute for Translational Medicine, University of Pécs, Pecs, Hungary.
Objective: Simulation is a necessary aspect of teaching open vascular exposure, control, and reconstruction. Current technologies lack 3-dimensional (3D) depth, real anatomic topography associated with different body regions and do not provide assessment of technical adequacy of vascular reconstruction. We conducted a pilot testing of Your-Anastomosis (Pecs, Hungary). A novel 3D-printed simulation-model based on patient computed tomographic imaging and surface scanning of surgical sites, providing real topography and sewing angles as well as flow dynamic and visual assessment of each simulated reconstruction.
Methods: The 3D-printed simulation-models were used in two sessions supervised by a senior vascular surgeon. Once each simulated anastomosis was completed, the vessel specimen was removed from the model and sent for analysis. Analysis results were provided to the trainee and the training program.
Results: Two sessions were completed, the first with 17 general surgery (GS) interns and 6 medical students (MS) on upper extremity arteriovenous-fistula and carotid patch angioplasty (CPA) models. The second session had vascular surgery residents (three PGY-1, one PGY-3, one PGY-4) and one MS on femoral and CPA models. Once each anastomosis was completed, the vessel specimen was removed from the model and sent for analysis. A digital 3D-model of the anastomosis was created to generate a computational fluid-dynamics assessment. The software utilized an AI-based program that analyzed technical aspects of the anastomosis as wall-shear stress, energy-loss and oscillatory shear index. An objective normalized score (range: lowest 1.3 to highest 8.7, based on previous analyzed anastomoses) was generated. At the end of each session, trainees subjectively reported their experience. Session I received an overall score of 3.8±0.8, and session II received a score of 4.8±0.8. The trainees' subjective experience was excellent.
Conclusion: In its first assessment in a U.S. center, this technology was shown to be feasible and provided a variety of realistic anastomotic experiences of different anatomic locations. This experience confirms and extends a previous report on this technology, showing its ability to generate detailed flow dynamic and visual assessment as objective feedback to GS and vascular trainees. This experience provides the foundation for expanded use and study of the technology
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