Virtual hepatic surgery scenarios using manipulated real liver models

Computer Engineering and Informatics Department, University of Patras, Patras, Greece
Hepatobiliary and Pancreatic Unit, University Hospital of Patras, Patras, Greece
Biomedical Engineering Laboratory, National Technical University of Athens, Athens, Greece
DOI
10.7287/peerj.preprints.1090v1
Subject Areas
Gastroenterology and Hepatology, Surgery and Surgical Specialties, Science and Medical Education
Keywords
hepatic surgery, hepatic surgery, liver segmentation, medical education, medical informatics
Copyright
© 2015 Zygomalas et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Zygomalas A, Megalooikonomou V, Koutsouris D, Karavias D, Karagiannidis I, Amanatidis T, Maroulis I, Giokas K, Karavias D. 2015. Virtual hepatic surgery scenarios using manipulated real liver models. PeerJ PrePrints 3:e1090v1

Abstract

Background. High quality patient specific 3D liver models can be nowadays exported using computer liver segmentation algorithms. Specific 3D image editing tools can be used to manipulate the liver models and create virtual surgical cases. Objective. The aim of our study was to create virtual hepatic surgery scenarios using a novel liver segmentation and preoperative planning application and evaluating it as an educational tool. Method. A liver segmentation and preoperative planning application was developed on MATLAB® 2013a. Special image editing tools were designed to allow manipulation of the exported 3D liver models. Three pathological and two liver imaging datasets from healthy patients were used for the validation. The 3D liver models which have been created after liver segmentation were then manipulated by; 1) changing tumors’ volumes, 2) adding tumors and 3) designing liver injuries. Addition fictitious clinical information were implemented. Residents were asked to study the virtual cases and propose resection plans. Their scenarios were evaluated and discussed with specialized liver surgeons. The Kirkpatrick’s four levels model of learning evaluation was used. Results. Up to 30 different virtual liver surgical cases were created. The number of virtual scenarios that could be designed is theoretically unlimited. The residents quickly and effectively learned to evaluate critical anatomical and pathological structures and propose liver resection plans considering liver surgery principles. Conclusions. Virtual hepatic surgery scenarios allowed for a rapid education without the need to wait for similar real cases. The proposed liver segmentation and hepatectomy simulation application can be used for educational purposes.

Author Comment

This is an abstract which has been accepted for the 2nd International Conference on Medical Education Informatics.