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Physical patient simulators for surgical training: a review

Shao, Marine; Parraman, Carinna; Huson, David

Authors

Marine Shao

David Huson David.Huson@uwe.ac.uk
Associate Professor of Ceramics, 3D Technologies and Digital Fabrication



Abstract

The purpose of this article is to review the fabrication process of physical patient simulators for surgical training and describes current research areas. Medical image acquisition and analysis are tools to reproduce human anatomy in 3D models. Data acquisition techniques include CT scans, MRI, and ultrasound. Postprocessing of this data is necessary to obtain a file for 3D printing. Two available fabrication methods are direct 3D printing of an organ model and 3D printing a mould to cast an organ replica. Direct 3D printing presents several limitations. Therefore, casting techniques with silicones and hydrogels are better suited for the fabrication of softer tissue models. Surgeons qualitatively evaluate the simulators and their ability to train students. It is also possible to make a quantitative evaluation to compare the properties of the simulators to the physical properties of organs. Different methods exist to measure the physical properties of soft tissues, mainly to find the Young modulus of the soft tissue. The tests can be in vivo, in situ or in vitro. Researchers perform tests on human tissues or animal tissues. The use of surgical simulators has shown satisfactory results in surgical training. Nonetheless, limitations remain, simulators lack realism and are not available for some pathologies. Future work in this area could be of benefit to
surgical training.

Presentation Conference Type Conference Paper (Published)
Conference Name London Imaging Meeting 2020: Future Colour Imaging
Start Date Sep 30, 2020
End Date Oct 1, 2020
Acceptance Date Jan 31, 2020
Online Publication Date Sep 29, 2021
Publication Date Sep 29, 2021
Deposit Date May 27, 2021
Pages 124-128
Series ISSN 2694-118X
Book Title London Imaging Meeting
DOI https://doi.org/10.2352/issn.2694-118X.2020.LIM-05
Public URL https://uwe-repository.worktribe.com/output/6241280
Related Public URLs https://www.imaging.org/site/IST/IST/Conferences/LIM/LIM_Home.aspx