Simulation Training in Minimally Invasive Lung Resections: Developing a Reproducible, High-Fidelity Porcine Model

Simulation Training in Minimally Invasive Lung Resections: Developing a Reproducible, High-Fidelity Porcine Model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Simulation Training in Minimally Invasive Lung Resections: Developing a Reproducible, High-Fidelity Porcine Model J Whooley, C O’Conghaile, S Horne, DA O’Keefe, C Condron, GJ Fitzmaurice, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7010617/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Robotic-assisted lung resection has gained prominence within the era of minimally invasive surgery as it holds the potential to offer improved peri-operative pain and duration of stay without compromising oncological outcomes. The surgeon learning curve remains a challenge and simulation forms a crucial part of surgical training. Virtual reality simulation is currently the standard modality used by trainees when simulating console operating, which lacks the ability to replicate real tissue handling. We describe a high-fidelity, reproducible, low-cost porcine lung model from adult Landrace pigs, with porcine peri-cardiac fat used to simulate pulmonary tumours. This model was evaluated in a training session for higher-level cardiothoracic trainees performing robotic-assisted lung resections under the guidance of expert robotic surgeons with feedback recorded via an evaluation tool. Trainees rated the model high on its fidelity to human lung simulation, tissue handling and overall usefulness (median score 4/5). Trainees reported that this model was very useful for simulating realistic lung parenchymal manipulation, wedge resections and hilar dissection, while suggestions for improvement included adding simulated blood flow. This is a low-cost, high-fidelity simulation model for robotic-assisted lung resection with high acceptability to surgical trainees, which could be readily adopted by other training centres. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Surgery continues to be the primary treatment for lung cancer, providing the best chance for long-term, disease-free survival and potential cure. The standard major pulmonary resections include sub-lobar resection, lobectomy, bilobectomy, and pneumonectomy. Sub-lobar resections encompass both non-anatomical wedge resections for peripheral tumors and anatomical segmentectomies. While lobectomy remains the gold standard for lung cancer resection, sub-lobar resection has become a valuable alternative for patients with compromised pulmonary function or significant comorbidities. These surgical procedures can be performed by either an open (thoracotomy) or minimally invasive approach. Minimally invasive thoracic surgery is preferred if suitable for patients, as it has been shown to reduce post-operative pain, leading to improved length of stay and recovery [ 1 ]. The first robotic lobectomies were reported in 2003, and despite an initial slow uptake in robotic-assisted surgery in comparison to other surgical specialties, between 2013 and 2018 the number of robotic-assisted lobectomies performed in the United States increased by 243% according to the Society of Thoracic Surgeons (STS) database [ 2 – 4 ]. With over 80% of lobectomies being performed via a minimally invasive approach, there is an increasing emphasis on incorporating robotic techniques into present-day thoracic training [ 5 ]. There are potential barriers to incorporating robotic training into modern thoracic training, including concerns regarding handing over control of the robotic console to junior trainees and potential time constraints [ 6 ]. Lobectomy is a particularly challenging operation to teach, due to pressures around the manipulation of major blood vessels such as the pulmonary arteries and veins, achieving a negative margin and complications such as a prolonged airleak. Consequently, simulation training in robotic surgery has become a widely accepted and essential component of surgical education, playing a key role in improving performance in the operating room. However, one of the main challenges of robotic simulation is its inability to fully replicate the authenticity of actual surgical procedures, which is crucial for ensuring that acquired skills transfer effectively to real-world settings. While virtual reality programs are beneficial for gaining familiarity with the robotic system and understanding foundational concepts, they fall short in replicating realistic tissue interaction. This limitation can potentially leave surgeons underprepared when transitioning from simulation to live surgery. [ 7 ]. Methods Our goal was to develop a high-fidelity, reproducible, and cost-effective porcine pulmonary simulation model to support robotic surgical training. This initiative was guided by a collaborative steering group comprising researchers and practitioners, including simulation technicians, clinical educators specializing in simulation, a consultant robotic thoracic surgeon, and a thoracic surgery trainee. Design-based research principles [ 8 ] were applied, with the model undergoing multiple refinements through an iterative process guided by direct feedback from surgeons. The primary goals were to ensure reproducibility and achieve high functional fidelity. [ 9 ]. The final model was pilot-tested by three robotic thoracic surgeons and a group of five Irish thoracic surgical trainees, after which the team reached a consensus on its suitability for use in robotic training. A porcine heart, lungs and trachea block with adipose tissue were used to create the model (Fig. 1 ). These blocks were procured from our agricultural partners using adult Landrace pigs. The extra organs were useful to simulate discernable human supine orientation. Tumours were created from excess adipose tissue on the porcine model as previously described for an in-house renal model [ 10 ]. The adipose tissue was resected from the superior aspect of the heart and shaped by hand into the desired shape, texture and size (ranging from 2 to 4 cm in diameter). Approaching mediolaterally, round tipped scissors were used to create a small channel by opening and advancing about 6-8cm in length (Fig. 2 ). After removing the scissors, a gloved finger was used to widen the channel under the visceral pleura and a rounded ball of adipose tissue was placed into the aperture to achieve the desired placement and positioning of the tumour. A few drops of 3 M™ Vetbond™ Tissue Adhesive™ was used to secure the tumor in place. This we repeated until the desired number of tumors were created. The model was positioned inside a box trainer acting as a simulated hemi-thorax. The da Vinci Xi ® robotic arms were docked into appropriate ports and thoracic surgical trainees then performed Robotic Assisted Thoracic Surgery via the robotic console (Figs. 3 , 4 , 5 , 6 ). All participants were familiar with the procedure of Robotic assisted lung resection having completed the online training programme [ 11 ]. Following completion of the session, trainees completed an evaluation via an anonymous 10-question questionnaire [Figure 7] enquiring about perceptions of the simulator and its potential utility. Results All five thoracic surgery trainees provided feedback. Using a scale from 1 (very poor) to 5 (perfect), they gave a median rating of 4 for how accurately the model replicated a human lung in terms of vessel manipulation and dissection. All trainees reported that the model was similar to previous models that they had used on VATS lobectomy courses, with 1 trainee reporting that this model was better with regards to tissue handling. All trainees felt that the simulation session was very useful and were keen to integrate the session into the annual thoracic surgery training schedule. Two trainees felt that the model could be improved by adding fluid into the model’s blood vessels, to improve visual feedback when encircling the pulmonary artery and vein. [Figure 8.] Table 1 Summarizing our Questionnaire’s results. What is your experience with Robotic Thoracic Surgery? (N = 5) a. No experience (N = 1) b. Previously 1st assistant (N = 1) c. Currently 1st assistant (N = 1) d. Currently using robotic console to perform certain aspects of procedures (N = 1) e. Currently using robotic console to perform sublobar lung resections (N = 0) f. Have performed a robotic lobectomy (N = 1) Did you find today’s robotic course useful? (N = 5) Yes, I think that Robotic simulation with a porcine model should be incorporated within our Thoracic training as an annual course. (N = 5) Do you have any prior experience with lung resection simulation previously? (N = 5) Yes, simulation with porcine model (N = 5) How did today’s porcine lung model compare? (N = 5) - Better simulation experience (N = 1) - Similar simulation experience (N = 4) How well did you feel that this model replicated hilar vessel manipulation and dissection? (N = 5) 1. Poor (N = 0) 2. Fair (N = 0) 3. Average (N = 1) 4. Good (N = 3) 5. Excellent (N = 1) What do you feel are the strengths of this model? - Enables a realistic experience to simulate tissue handling and dissection. - This tissue model provides a very high-fidelity simulation experience. - Excellent tissue quality that simulates tissue handling (ie. going around hilar structures) very well. - A very realistic simulation experience. - Useful for both simulating localization of nodules in lung parenchyma for wedge resection (stapler utilization) but also for simulating hilar dissections required for lobectomy. What do you feel are the limitations with this model? - Lack of bleeding when vessels are cut/lack of pressure in vessels. (N = 2) - Anatomical planes were difficult to delineate. - Variable lobar anatomy in comparison with human lungs. Do you feel there are any areas for improvement with this model? - Alteration of chest wall model to more accurately simulate the orientation of a human thoracic cavity. - Introduce pressurized saline into blood vessels to improve hilar vessel dissection simulation experience. Did you get sufficient Robot console time today? Yes (N = 5) Do you have any further suggestions for future iterations of this course in the future? - A Porcine pulmonary anatomy presentation could be delivered prior to wet-lab sessions. Discussion This straightforward and replicable model offers several benefits. Most notably, it is cost-effective, with a total expense of around €55 ( $ 60) per unit, including both staffing and equipment costs. This is in keeping with a previously published ex-vivo porcine model ( $ 65), both of which are markedly cheaper when compared with a previously published hydrogel model ( $ 500) [ 12 , 13 ]. This low-cost enables training centres to facilitate repeated high-fidelity training sessions with high reproducibility, and opens the door for broader utilisation of this model within the thoracic surgical training pathway with an expansion of indications such as a thymic model. Multiple lesions can be incorporated into a single model, enabling shared use among trainees, repeated practice by the same individual, or alternation between procedures such as lobectomy and wedge resection. The model demonstrated high user acceptability, and its feasibility was confirmed by the successful completion of all planned procedures. According to trainee feedback, dissection and handling of the hilar structures, as well as manipulation of the lung parenchyma, closely resembled the tactile experience of working with human lung tissue. This model does have some limitations. While the model itself is inexpensive, its use depended on access to a da Vinci Xi® training robot, which may not be available in all centres. Nonetheless, the model can also be adapted for use in simulating open or video-assisted thoracoscopic (VATS) lung resections. Although it was well received by surgical trainees, the model was evaluated with a small sample size, and further validation with a larger cohort is necessary. The model as it is described does not simulate bleeding, although this is something that can be achieved by cannulating the pulmonary artery and pulmonary vein and attaching to a giving set, as described in our previous kidney model [ 10 ]. By simulating pulmonary artery and vein pressure, this could enhance the trainee simulation experience by providing more realistic dissection of hilar structures, introducing a more authentic experience when performing the hilar dissection, and would also aid in simulating the surgical stress of managing bleeding during a dissection. This could also facilitate running simulation exercises with the Robotic theatre team as a whole, such as an emergency bleeding scenario and how to appropriately manage the situation as the operator. This issue will be considered as part of the next steps for developing further iterations of this model, as it becomes integrated within the Irish thoracic surgical training pathway. One additional limitation with the porcine model is the anatomical variation to human lungs. The porcine lungs have two lobes (cranial and caudal) on the left side, and four lobes (cranial, middle, caudal and accessory) on the right side, whereas human lungs have three lobes (upper, middle and lower) on the right side and two (upper and lower) on the left side. As a result, the left sided porcine lung is more useful to simulate a lobectomy, whereas the right sided porcine lung remains useful as a model to simulate wedge resections. Future courses may also include a didactic session where trainees are briefed on potential anatomical differences between human and porcine lungs, in order to optimise their robotic simulation experience. The affordability and versatility of this model make it well-suited for repeated training sessions within a robotic thoracic surgery curriculum, enabling lobectomy and wedge resections to be practiced on biological tissue beyond the standard robotic console simulation. Objective assessments of skill development—such as movement efficiency and ergonomics—could be conducted using data gathered from the da Vinci Xi® platform to track trainee progress. Conclusion This is a high-fidelity, low-cost simulation model that can be used to reliably simulate lung resections and hilar structure dissection with high acceptability to surgical trainees; it could be readily adopted by other training centres. Declarations Author Contribution J.W and GJ.F wrote the main manuscript text, and J.W and C.OC prepared the figures. All authors reviewed the manuscript. References Sedrakyan A, van der Meulen J, Lewsey J, Treasure T. Video assisted thoracic surgery for treatment of pneumothorax and lung resections: systematic review of randomised clinical trials. BMJ 2004; 329:1008–1010 J.A. Morgan, M.E. Ginsburg, J.R. Sonett, et al. Advanced thoracoscopic procedures are facilitated by computer-aided robotic technology. Eur J Cardiothorac Surg, 23 (2003), pp. 883-887 R.C. Ashton, C.P. Connery, D.G. Swistel, et al. Robot-assisted lobectomy. J Thorac Cardiovasc Surg, 126 (2003), pp. 292-293 Servais EL, Towe CW, Brown LM, et al. The Society of Thoracic Surgeons General Thoracic Surgery Database: 2020 update on outcomes and research.  Ann Thorac Surg. 2020;110(3):768-775. doi:10.1016/j.athoracsur.2020.06.006 Towe CW, Servais EL, Brown LM, et al. The Society of Thoracic Surgeons General Thoracic Surgery Database: 2023 update on outcomes and research.  Ann Thorac Surg. 2024;117(3):489-496. doi:10.1016/j.athoracsur.2023.11.021 Turner SR, Mormando J, Park BJ, Huang J (2020) Attitudes of robotic surgery educators and learners: challenges, advantages, tips and tricks of teaching and learning robotic surgery. J Robot Surg 14(3):455–461. https://doi.org/10.1007/s11701-019-01013-1 A. Gleason, E. Servais, S. Quadri, et al. Developing basic robotic skills using virtual reality simulation and automated assessment tools: a multidisciplinary robotic virtual reality–based curriculum using the da Vinci skills simulator and tracking progress with the intuitive learning platform. J Robot Surg, 16 (2022), pp. 1313-1319 Cowling M, Birt J (2018) Pedagogy before technology: a design- based research approach to enhancing skills development in para- medic science using mixed reality. Information 9(2):29. https:// doi.org/10.3390/info9020029 Hamstra SJ, Brydges R, Hatala R, Zendejas B, Cook DA (2014) Reconsidering fidelity in simulation-based training. Acad Med 89(3):387–392. https://doi.org/10.1097/ACM.0000000000000130 Croghan, S.M., Voborsky, M., Roche, A.F. et al. Design and utilisation of a novel, high-fidelity, low-cost, hybrid-tissue simulation model to facilitate training in robot-assisted partial nephrectomy. J Robotic Surg 18, 103 (2024). https://doi.org/10.1007/s11701-024-01857-2 Online Training program https://www.intuitive.com/en-us/products-and-services/da-vinci/learning Meyerson SL, LoCascio F, Balderson SS, D’Amico TA. An inexpensive, re- producible tissue simulator for teaching thoracoscopic lobectomy. Ann Thorac Surg 2010;89:594–7. Sato T, Morikawa T. Video-assisted thoracoscopic surgery training with a polyvinyl-alcohol hydrogel modelmimicking real tissue. J Vis Surg 2017;3:65. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7010617","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":479332170,"identity":"87d4c857-419b-4dea-8a8d-152d632539e3","order_by":0,"name":"J 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12:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7010617/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7010617/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86140079,"identity":"d345d5a5-f9d0-4e3c-bc26-8ed038952caa","added_by":"auto","created_at":"2025-07-07 08:22:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2320978,"visible":true,"origin":"","legend":"\u003cp\u003eHeart, lungs and trachea block with simulated tumour marked on the specimen\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7010617/v1/f23924a69c32d7b9880214d4.png"},{"id":86140078,"identity":"95b227ca-3c9b-4088-895a-ba0a24cbeaeb","added_by":"auto","created_at":"2025-07-07 08:22:15","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":217286,"visible":true,"origin":"","legend":"\u003cp\u003eHeavy scissors creating a small channel in the lung parenchyma\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7010617/v1/bd7cc1c7812bc178ec07537e.jpeg"},{"id":86140089,"identity":"fec5f89b-89e8-4ed8-8d96-94930b07e0c3","added_by":"auto","created_at":"2025-07-07 08:22:15","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1319640,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of the box simulator with the robotic arms docked\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7010617/v1/b2aebb96ab407fcb52e4f5e5.jpeg"},{"id":86141878,"identity":"d19f1f70-2c91-4c9c-b8ec-f22b4f7e7ff5","added_by":"auto","created_at":"2025-07-07 08:30:15","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":926220,"visible":true,"origin":"","legend":"\u003cp\u003eThe heart – lung block with simulated tumours evident on a stainless steel tray positioned in the box simulator\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7010617/v1/7c06d3a179990e62eec28557.jpeg"},{"id":86140087,"identity":"5c8c1bac-b48a-422a-ab52-a02f170c3201","added_by":"auto","created_at":"2025-07-07 08:22:15","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":864503,"visible":true,"origin":"","legend":"\u003cp\u003eIntra-operative image demonstrating resection of a simulated tumour from the lung parenchyma using a Sureform Green stapler\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7010617/v1/52a9e448e39ab92be80afde1.jpeg"},{"id":86140083,"identity":"e93c266a-1452-4785-8d53-777b30e0fe7e","added_by":"auto","created_at":"2025-07-07 08:22:15","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1193100,"visible":true,"origin":"","legend":"\u003cp\u003eImage within the box simulator demonstrating resection of a simulated tumour from the lung parenchyma using a Sureform Black stapler\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7010617/v1/f87b61ac067cdd9e5e56bfd9.jpeg"},{"id":86637227,"identity":"3fd54b8d-9966-46c3-910d-03054179faf2","added_by":"auto","created_at":"2025-07-14 07:32:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7505864,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7010617/v1/37db6b50-e371-438e-acaf-5fef1284e9b1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Simulation Training in Minimally Invasive Lung Resections: Developing a Reproducible, High-Fidelity Porcine Model","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSurgery continues to be the primary treatment for lung cancer, providing the best chance for long-term, disease-free survival and potential cure. The standard major pulmonary resections include sub-lobar resection, lobectomy, bilobectomy, and pneumonectomy. Sub-lobar resections encompass both non-anatomical wedge resections for peripheral tumors and anatomical segmentectomies. While lobectomy remains the gold standard for lung cancer resection, sub-lobar resection has become a valuable alternative for patients with compromised pulmonary function or significant comorbidities.\u003c/p\u003e \u003cp\u003eThese surgical procedures can be performed by either an open (thoracotomy) or minimally invasive approach. Minimally invasive thoracic surgery is preferred if suitable for patients, as it has been shown to reduce post-operative pain, leading to improved length of stay and recovery [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The first robotic lobectomies were reported in 2003, and despite an initial slow uptake in robotic-assisted surgery in comparison to other surgical specialties, between 2013 and 2018 the number of robotic-assisted lobectomies performed in the United States increased by 243% according to the Society of Thoracic Surgeons (STS) database [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. With over 80% of lobectomies being performed via a minimally invasive approach, there is an increasing emphasis on incorporating robotic techniques into present-day thoracic training [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are potential barriers to incorporating robotic training into modern thoracic training, including concerns regarding handing over control of the robotic console to junior trainees and potential time constraints [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Lobectomy is a particularly challenging operation to teach, due to pressures around the manipulation of major blood vessels such as the pulmonary arteries and veins, achieving a negative margin and complications such as a prolonged airleak. Consequently, simulation training in robotic surgery has become a widely accepted and essential component of surgical education, playing a key role in improving performance in the operating room. However, one of the main challenges of robotic simulation is its inability to fully replicate the authenticity of actual surgical procedures, which is crucial for ensuring that acquired skills transfer effectively to real-world settings. While virtual reality programs are beneficial for gaining familiarity with the robotic system and understanding foundational concepts, they fall short in replicating realistic tissue interaction. This limitation can potentially leave surgeons underprepared when transitioning from simulation to live surgery. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eOur goal was to develop a high-fidelity, reproducible, and cost-effective porcine pulmonary simulation model to support robotic surgical training. This initiative was guided by a collaborative steering group comprising researchers and practitioners, including simulation technicians, clinical educators specializing in simulation, a consultant robotic thoracic surgeon, and a thoracic surgery trainee. Design-based research principles [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] were applied, with the model undergoing multiple refinements through an iterative process guided by direct feedback from surgeons. The primary goals were to ensure reproducibility and achieve high functional fidelity. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The final model was pilot-tested by three robotic thoracic surgeons and a group of five Irish thoracic surgical trainees, after which the team reached a consensus on its suitability for use in robotic training.\u003c/p\u003e \u003cp\u003eA porcine heart, lungs and trachea block with adipose tissue were used to create the model (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These blocks were procured from our agricultural partners using adult Landrace pigs. The extra organs were useful to simulate discernable human supine orientation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTumours were created from excess adipose tissue on the porcine model as previously described for an in-house renal model [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The adipose tissue was resected from the superior aspect of the heart and shaped by hand into the desired shape, texture and size (ranging from 2 to 4 cm in diameter). Approaching mediolaterally, round tipped scissors were used to create a small channel by opening and advancing about 6-8cm in length (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter removing the scissors, a gloved finger was used to widen the channel under the visceral pleura and a rounded ball of adipose tissue was placed into the aperture to achieve the desired placement and positioning of the tumour. A few drops of 3 M\u0026trade; Vetbond\u0026trade; Tissue Adhesive\u0026trade; was used to secure the tumor in place. This we repeated until the desired number of tumors were created.\u003c/p\u003e \u003cp\u003eThe model was positioned inside a box trainer acting as a simulated hemi-thorax. The \u003cem\u003eda Vinci Xi\u003c/em\u003e \u0026reg; robotic arms were docked into appropriate ports and thoracic surgical trainees then performed Robotic Assisted Thoracic Surgery via the robotic console (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). All participants were familiar with the procedure of Robotic assisted lung resection having completed the online training programme [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Following completion of the session, trainees completed an evaluation via an anonymous 10-question questionnaire [Figure 7] enquiring about perceptions of the simulator and its potential utility.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAll five thoracic surgery trainees provided feedback. Using a scale from 1 (very poor) to 5 (perfect), they gave a median rating of 4 for how accurately the model replicated a human lung in terms of vessel manipulation and dissection. All trainees reported that the model was similar to previous models that they had used on VATS lobectomy courses, with 1 trainee reporting that this model was better with regards to tissue handling. All trainees felt that the simulation session was very useful and were keen to integrate the session into the annual thoracic surgery training schedule. Two trainees felt that the model could be improved by adding fluid into the model\u0026rsquo;s blood vessels, to improve visual feedback when encircling the pulmonary artery and vein. [Figure 8.]\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummarizing our Questionnaire\u0026rsquo;s results.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhat is your experience with Robotic Thoracic Surgery? (N\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ea. No experience (N\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003cp\u003eb. Previously 1st assistant (N\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003cp\u003ec. Currently 1st assistant (N\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003cp\u003ed. Currently using robotic console to perform certain aspects of procedures (N\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003cp\u003ee. Currently using robotic console to perform sublobar lung resections (N\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003cp\u003ef. Have performed a robotic lobectomy (N\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDid you find today\u0026rsquo;s robotic course useful? (N\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes, I think that Robotic simulation with a porcine model should be incorporated within our Thoracic training as an annual course. (N\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDo you have any prior experience with lung resection simulation previously? (N\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes, simulation with porcine model (N\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHow did today\u0026rsquo;s porcine lung model compare? (N\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Better simulation experience (N\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003cp\u003e- Similar simulation experience (N\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHow well did you feel that this model replicated hilar vessel manipulation and dissection? (N\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. Poor (N\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003cp\u003e2. Fair (N\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003cp\u003e3. Average (N\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003cp\u003e4. Good (N\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003cp\u003e5. Excellent (N\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWhat do you feel are the strengths of this model?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Enables a realistic experience to simulate tissue handling and dissection.\u003c/p\u003e \u003cp\u003e- This tissue model provides a very high-fidelity simulation experience.\u003c/p\u003e \u003cp\u003e- Excellent tissue quality that simulates tissue handling (ie. going around hilar structures) very well.\u003c/p\u003e \u003cp\u003e- A very realistic simulation experience.\u003c/p\u003e \u003cp\u003e- Useful for both simulating localization of nodules in lung parenchyma for wedge resection (stapler utilization) but also for simulating hilar dissections required for lobectomy.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWhat do you feel are the limitations with this model?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Lack of bleeding when vessels are cut/lack of pressure in vessels. (N\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003cp\u003e- Anatomical planes were difficult to delineate.\u003c/p\u003e \u003cp\u003e- Variable lobar anatomy in comparison with human lungs.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDo you feel there are any areas for improvement with this model?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Alteration of chest wall model to more accurately simulate the orientation of a human thoracic cavity.\u003c/p\u003e \u003cp\u003e- Introduce pressurized saline into blood vessels to improve hilar vessel dissection simulation experience.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDid you get sufficient Robot console time today?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes (N\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDo you have any further suggestions for future iterations of this course in the future?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- A Porcine pulmonary anatomy presentation could be delivered prior to wet-lab sessions.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e This straightforward and replicable model offers several benefits. Most notably, it is cost-effective, with a total expense of around \u0026euro;55 (\u003cspan\u003e$\u003c/span\u003e60) per unit, including both staffing and equipment costs. This is in keeping with a previously published ex-vivo porcine model (\u003cspan\u003e$\u003c/span\u003e65), both of which are markedly cheaper when compared with a previously published hydrogel model (\u003cspan\u003e$\u003c/span\u003e500) [ \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e , \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e ]. This low-cost enables training centres to facilitate repeated high-fidelity training sessions with high reproducibility, and opens the door for broader utilisation of this model within the thoracic surgical training pathway with an expansion of indications such as a thymic model. \u003c/p\u003e \u003cp\u003eMultiple lesions can be incorporated into a single model, enabling shared use among trainees, repeated practice by the same individual, or alternation between procedures such as lobectomy and wedge resection. The model demonstrated high user acceptability, and its feasibility was confirmed by the successful completion of all planned procedures. According to trainee feedback, dissection and handling of the hilar structures, as well as manipulation of the lung parenchyma, closely resembled the tactile experience of working with human lung tissue.\u003c/p\u003e \u003cp\u003eThis model does have some limitations. While the model itself is inexpensive, its use depended on access to a da Vinci Xi\u0026reg; training robot, which may not be available in all centres. Nonetheless, the model can also be adapted for use in simulating open or video-assisted thoracoscopic (VATS) lung resections. Although it was well received by surgical trainees, the model was evaluated with a small sample size, and further validation with a larger cohort is necessary. The model as it is described does not simulate bleeding, although this is something that can be achieved by cannulating the pulmonary artery and pulmonary vein and attaching to a giving set, as described in our previous kidney model [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. By simulating pulmonary artery and vein pressure, this could enhance the trainee simulation experience by providing more realistic dissection of hilar structures, introducing a more authentic experience when performing the hilar dissection, and would also aid in simulating the surgical stress of managing bleeding during a dissection. This could also facilitate running simulation exercises with the Robotic theatre team as a whole, such as an emergency bleeding scenario and how to appropriately manage the situation as the operator. This issue will be considered as part of the next steps for developing further iterations of this model, as it becomes integrated within the Irish thoracic surgical training pathway.\u003c/p\u003e \u003cp\u003eOne additional limitation with the porcine model is the anatomical variation to human lungs. The porcine lungs have two lobes (cranial and caudal) on the left side, and four lobes (cranial, middle, caudal and accessory) on the right side, whereas human lungs have three lobes (upper, middle and lower) on the right side and two (upper and lower) on the left side. As a result, the left sided porcine lung is more useful to simulate a lobectomy, whereas the right sided porcine lung remains useful as a model to simulate wedge resections. Future courses may also include a didactic session where trainees are briefed on potential anatomical differences between human and porcine lungs, in order to optimise their robotic simulation experience.\u003c/p\u003e \u003cp\u003eThe affordability and versatility of this model make it well-suited for repeated training sessions within a robotic thoracic surgery curriculum, enabling lobectomy and wedge resections to be practiced on biological tissue beyond the standard robotic console simulation. Objective assessments of skill development\u0026mdash;such as movement efficiency and ergonomics\u0026mdash;could be conducted using data gathered from the da Vinci Xi\u0026reg; platform to track trainee progress.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis is a high-fidelity, low-cost simulation model that can be used to reliably simulate lung resections and hilar structure dissection with high acceptability to surgical trainees; it could be readily adopted by other training centres.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.W and GJ.F wrote the main manuscript text, and J.W and C.OC prepared the figures. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSedrakyan A, van der Meulen J, Lewsey J, Treasure T. Video assisted thoracic surgery for treatment of pneumothorax and lung resections: systematic review of randomised clinical trials. BMJ 2004; 329:1008\u0026ndash;1010\u003c/li\u003e\n\u003cli\u003eJ.A. Morgan, M.E. Ginsburg, J.R. Sonett, et al. Advanced thoracoscopic procedures are facilitated by computer-aided robotic technology. Eur J Cardiothorac Surg, 23 (2003), pp. 883-887\u003c/li\u003e\n\u003cli\u003eR.C. Ashton, C.P. Connery, D.G. Swistel, et al. Robot-assisted lobectomy. J Thorac Cardiovasc Surg, 126 (2003), pp. 292-293\u003c/li\u003e\n\u003cli\u003eServais EL, Towe CW, Brown LM, et al. The Society of Thoracic Surgeons General Thoracic Surgery Database: 2020 update on outcomes and research.  Ann Thorac Surg. 2020;110(3):768-775. doi:10.1016/j.athoracsur.2020.06.006\u003c/li\u003e\n\u003cli\u003eTowe CW, Servais EL, Brown LM, et al. The Society of Thoracic Surgeons General Thoracic Surgery Database: 2023 update on outcomes and research.  Ann Thorac Surg. 2024;117(3):489-496. doi:10.1016/j.athoracsur.2023.11.021\u003c/li\u003e\n\u003cli\u003eTurner SR, Mormando J, Park BJ, Huang J (2020) Attitudes of robotic surgery educators and learners: challenges, advantages, tips and tricks of teaching and learning robotic surgery. J Robot Surg 14(3):455\u0026ndash;461. https://doi.org/10.1007/s11701-019-01013-1 \u003c/li\u003e\n\u003cli\u003eA. Gleason, E. Servais, S. Quadri, et al. Developing basic robotic skills using virtual reality simulation and automated assessment tools: a multidisciplinary robotic virtual reality\u0026ndash;based curriculum using the da Vinci skills simulator and tracking progress with the intuitive learning platform. J Robot Surg, 16 (2022), pp. 1313-1319\u003c/li\u003e\n\u003cli\u003eCowling M, Birt J (2018) Pedagogy before technology: a design- based research approach to enhancing skills development in para- medic science using mixed reality. Information 9(2):29. https:// doi.org/10.3390/info9020029 \u003c/li\u003e\n\u003cli\u003eHamstra SJ, Brydges R, Hatala R, Zendejas B, Cook DA (2014) Reconsidering fidelity in simulation-based training. Acad Med 89(3):387\u0026ndash;392. https://doi.org/10.1097/ACM.0000000000000130 \u003c/li\u003e\n\u003cli\u003eCroghan, S.M., Voborsky, M., Roche, A.F. et al. Design and utilisation of a novel, high-fidelity, low-cost, hybrid-tissue simulation model to facilitate training in robot-assisted partial nephrectomy. J Robotic Surg 18, 103 (2024). https://doi.org/10.1007/s11701-024-01857-2\u003c/li\u003e\n\u003cli\u003eOnline Training program https://www.intuitive.com/en-us/products-and-services/da-vinci/learning\u003c/li\u003e\n\u003cli\u003eMeyerson SL, LoCascio F, Balderson SS, D\u0026rsquo;Amico TA. An inexpensive, re- producible tissue simulator for teaching thoracoscopic lobectomy. Ann Thorac Surg 2010;89:594\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eSato T, Morikawa T. Video-assisted thoracoscopic surgery training with a polyvinyl-alcohol hydrogel modelmimicking real tissue. J Vis Surg 2017;3:65. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7010617/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7010617/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRobotic-assisted lung resection has gained prominence within the era of minimally invasive surgery as it holds the potential to offer improved peri-operative pain and duration of stay without compromising oncological outcomes. The surgeon learning curve remains a challenge and simulation forms a crucial part of surgical training. Virtual reality simulation is currently the standard modality used by trainees when simulating console operating, which lacks the ability to replicate real tissue handling. We describe a high-fidelity, reproducible, low-cost porcine lung model from adult Landrace pigs, with porcine peri-cardiac fat used to simulate pulmonary tumours. This model was evaluated in a training session for higher-level cardiothoracic trainees performing robotic-assisted lung resections under the guidance of expert robotic surgeons with feedback recorded via an evaluation tool. Trainees rated the model high on its fidelity to human lung simulation, tissue handling and overall usefulness (median score 4/5). Trainees reported that this model was very useful for simulating realistic lung parenchymal manipulation, wedge resections and hilar dissection, while suggestions for improvement included adding simulated blood flow. This is a low-cost, high-fidelity simulation model for robotic-assisted lung resection with high acceptability to surgical trainees, which could be readily adopted by other training centres.\u003c/p\u003e","manuscriptTitle":"Simulation Training in Minimally Invasive Lung Resections: Developing a Reproducible, High-Fidelity Porcine Model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-07 08:22:10","doi":"10.21203/rs.3.rs-7010617/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1a4a2402-bfc4-40b8-9110-154ae9e81b38","owner":[],"postedDate":"July 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T07:24:00+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-07 08:22:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7010617","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7010617","identity":"rs-7010617","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}