Evidence map›Paper›PMID 35562806›Full record

ArticleTrials2022

Patient-individualized resection planning in liver surgery using 3D print and virtual reality (i-LiVR)-a study protocol for a prospective randomized controlled trial.

Tobias Huber, Laura Isabel Hanke, Christian Boedecker, Lukas Vradelis, Janine Baumgart, Stefan Heinrich, Fabian Bartsch, Jens Mittler, Alicia Schulze, Christian Hansen and 2 more

Open access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in Trials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Couinaud segment-aware deep learning on point clouds for major liver resection planning.International journal of computer assisted radiology and surgery · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. The future of surgical simulation.Annals of translational medicine · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Tobias HuberDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany. tobias.huber@unimedizin-mainz.de.ORCID http://orcid.org/0000-0003-3219-501X
Laura Isabel HankeDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Christian BoedeckerDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Lukas VradelisDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Janine BaumgartDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Stefan HeinrichDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Fabian BartschDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Jens MittlerDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Alicia SchulzeInstitute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center Mainz, Mainz, Germany.
Christian HansenInstitute of Simulation and Graphics, Faculty of Informatics, University Magdeburg, Magdeburg, Germany.
Florentine HüttlDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Hauke LangDepartment of General, Visceral and Transplant Surgery, University Medical Center Mainz, Mainz, Germany.
Johannes Gutenberg University Mainz · DEUniversity Hospital Magdeburg · DE

Funding

Deutsche Forschungsgemeinschaft 490729183 HU2420/2-1
6 · The paper itself

Abstract

backgroundA multitude of different diseases-benign and malign-can require surgery of the liver. The liver is an especially challenging organ for resection planning due to its unique and interindividually variable anatomy. This demands a high amount of mental imagination from the surgeon in order to plan accordingly - a skill, which takes years of training to acquire and which is difficult to teach. Since the volume of the functional remnant liver is of great importance, parenchyma sparing resections are favoured. 3D reconstructions of computed tomography imaging enable a more precise understanding of anatomy and facilitate resection planning. The modality of presentation of these 3D models ranges from 2D monitors to 3D prints and virtual reality applications.

methodsThe presented trial compares three different modes of demonstration of a 3D reconstruction of CT scans of the liver, which are 3D print, a demonstration on a regular computer screen or using a head-mounted virtual reality headset, with the current gold standard of viewing the CT scan on a computer screen. The group size was calculated with n=25 each. Patients with major liver resections in a laparoscopic or open fashion are eligible for inclusion. Main endpoint is the comparison of the quotient between planned resection volume and actual resection volume between these groups. Secondary endpoints include usability for the surgical team as well as patient specifics and perioperative outcome measures and teaching issues. DISCUSSION: The described study will give insight in systematic planning of liver resections and the comparison of different demonstration modalities of 3D reconstruction of preoperative CT scans and the preference of technology. Especially teaching of these demanding operations is underrepresented in prior investigations.

trial registrationProspective trials registration at the German Clinical Trials register with the registration number DRKS00027865 . Registration Date: January 24, 2022.

Indexed as

Imaging, Three-DimensionalVirtual RealityHepatectomyHumansLiverProspective StudiesRandomized Controlled Trials as Topic3D printHead-mounted displayLiver resection planningLiver surgerySurgical trainingVirtual reality

Identifiers

PMID35562806
PMCPMC9100295
OpenAlexW4280494013

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.