Evidence map›Paper›PMID 33797689›Full record

ArticleInternational journal of computer assisted radiology and surgery2021

Laparoscopic augmented reality registration for oncological resection site repair.

Fabian Joeres, Tonia Mielke, Christian Hansen

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Fabian JoeresDepartment of Simulation and Graphics, Research Campus STIMULATE, Otto-von-Guericke-University, Magdeburg, Germany.ORCID http://orcid.org/0000-0001-8105-9263
Tonia MielkeDepartment of Simulation and Graphics, Research Campus STIMULATE, Otto-von-Guericke-University, Magdeburg, Germany.ORCID http://orcid.org/0000-0002-2363-2460
Christian HansenDepartment of Simulation and Graphics, Research Campus STIMULATE, Otto-von-Guericke-University, Magdeburg, Germany. christian.hansen@ovgu.de.ORCID http://orcid.org/0000-0002-5734-7529

Funding

Federal State of Saxony-Anhalt (Germany), European Union ZS/2016/10/81684
6 · The paper itself

Abstract

purposeResection site repair during laparoscopic oncological surgery (e.g. laparoscopic partial nephrectomy) poses some unique challenges and opportunities for augmented reality (AR) navigation support. This work introduces an AR registration workflow that addresses the time pressure that is present during resection site repair.

methodsWe propose a two-step registration process: the AR content is registered as accurately as possible prior to the tumour resection (the primary registration). This accurate registration is used to apply artificial fiducials to the physical organ and the virtual model. After the resection, these fiducials can be used for rapid re-registration (the secondary registration). We tested this pipeline in a simulated-use study with [Formula: see text] participants. We compared the registration accuracy and speed for our method and for landmark-based registration as a reference.

resultsAcquisition of and, thereby, registration with the artificial fiducials were significantly faster than the initial use of anatomical landmarks. Our method also had a trend to be more accurate in cases in which the primary registration was successful. The accuracy loss between the elaborate primary registration and the rapid secondary registration could be quantified with a mean target registration error increase of 2.35 mm.

conclusionThis work introduces a registration pipeline for AR navigation support during laparoscopic resection site repair and provides a successful proof-of-concept evaluation thereof. Our results indicate that the concept is better suited than landmark-based registration during this phase, but further work is required to demonstrate clinical suitability and applicability.

Indexed as

Augmented RealityLaparoscopySurgery, Computer-AssistedHumansImaging, Three-DimensionalNephrectomyAugmented realityLaparoscopic surgeryPartial nephrectomyRegistration

Identifiers

PMID33797689
PMCPMC8354909

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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.