Generic surgical process model for minimally invasive liver treatment methods

Journal Article (2022)
Author(s)

Maryam Gholinejad (TU Delft - Medical Instruments & Bio-Inspired Technology)

Egidius Pelanis (Oslo University Hospital, Universitetet i Oslo)

Davit Aghayan (Oslo University Hospital, Yerevan State Medical University After M. Heratsi)

Åsmund Avdem Fretland (Oslo University Hospital)

Bjørn Edwin (Oslo University Hospital, Universitetet i Oslo)

Turkan Terkivatan (Erasmus MC)

Ole Jakob Elle (Oslo University Hospital)

Arjo J. Loeve (TU Delft - Medical Instruments & Bio-Inspired Technology)

Jenny Dankelman (TU Delft - Medical Instruments & Bio-Inspired Technology)

Research Group
Medical Instruments & Bio-Inspired Technology
DOI related publication
https://doi.org/10.1038/s41598-022-19891-1
More Info
expand_more
Publication Year
2022
Language
English
Research Group
Medical Instruments & Bio-Inspired Technology
Issue number
1
Volume number
12
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Surgical process modelling is an innovative approach that aims to simplify the challenges involved in improving surgeries through quantitative analysis of a well-established model of surgical activities. In this paper, surgical process model strategies are applied for the analysis of different Minimally Invasive Liver Treatments (MILTs), including ablation and surgical resection of the liver lesions. Moreover, a generic surgical process model for these differences in MILTs is introduced. The generic surgical process model was established at three different granularity levels. The generic process model, encompassing thirteen phases, was verified against videos of MILT procedures and interviews with surgeons. The established model covers all the surgical and interventional activities and the connections between them and provides a foundation for extensive quantitative analysis and simulations of MILT procedures for improving computer-assisted surgery systems, surgeon training and evaluation, surgeon guidance and planning systems and evaluation of new technologies.