ArticleJournal of visualized surgery2025
Training in minimally invasive thoracic surgery on 3D-model: back to the future of education.
Article in Journal of visualized surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- ERS Congress 2025: highlights from the Thoracic Surgery and Lung Transplantation Assembly.ERJ open research · 2026Article
- Soft Conductive Textile Sensors: Characterization Methodology and Behavioral Analysis.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Minimally invasive surgery (MIS) is the standard approach for early-stage lung cancer, offering benefits such as reduced recovery time, shorter hospital stays, and minimized postoperative pain. However, these techniques require advanced motor skills and a deep understanding of thoracic anatomy. Recent technological advancements, specialized surgical instruments, and energy devices, have further improved MIS capabilities. Despite these advancements, the steep learning curve of video-assisted thoracic surgery (VATS) and robotic-assisted thoracic surgery (RATS) highlights the need for structured simulation-based education to ensure patient safety and optimize skill acquisition. Simulation training provides a risk-free environment for developing technical proficiency before operating on real patients. Virtual simulators, such as LapSim and V-Trainer, are widely used to familiarize trainees with endoscopic instruments and procedural techniques. However, real analog models remain essential for refining motor skills, depth perception, and tactile feedback, which are crucial for complex thoracic procedures. Traditional training methods using wet labs or cadaveric models pose limitations in cost, availability, and ethical concerns. The integration of high-realistic physical anatomical models, including 3D printed anatomical components, represents a promising alternative, offering high-fidelity surgical simulations that mimic real-life operative conditions. At the University of Pisa's EndoCAS Interdipartimental Center for Computer Assisted Surgery, a structured training program incorporating lung phantoms in a 3D-printed thoracic cage, virtual simulation, and stepwise lobectomy simulations have been developed to enhance thoracic surgery education. This study presents our experience with a hybrid simulation approach, based on the combination of virtual and physical simulation, in lobectomy training, emphasizing its role in bridging theoretical learning with hands-on surgical practice, ultimately improving technical skills and clinical confidence among thoracic surgery residents.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.