Evidence map›Paper›PMID 31822701›Full record

ArticleScientific reports2019

The effect of intraoperative imaging on surgical navigation for laparoscopic liver resection surgery.

Andrea Teatini, Egidijus Pelanis, Davit L Aghayan, Rahul Prasanna Kumar, Rafael Palomar, Åsmund Avdem Fretland, Bjørn Edwin, Ole Jakob Elle

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
4.9field-weighted citation impact, top 4% 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

24 citing papers in PubMed, 54 citations in OpenAlex.

  1. [Research on surgical instrument segmentation algorithm based on frequency-domain adaptive feature decomposition and visual Mamba].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Advanced Image-Guidance and Surgical-Navigation Techniques for Real-Time Visualized Surgery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  7. Observational
  8. Article
  9. Article
  10. Review
  11. Article
  12. A Review of Medical Image Registration for Different Modalities.Bioengineering (Basel, Switzerland) · 2024
    Review
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Minimizing blood loss and transfusion rate in laparoscopic liver surgery: a review.Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques · 2023
    Review
  20. 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

8 authors at 1 institution in 2 countries.

Andrea TeatiniThe Intervention Centre, Oslo University Hospital, Oslo, Norway. andre_tea@outlook.com.ORCID http://orcid.org/0000-0003-4764-5685
Egidijus PelanisThe Intervention Centre, Oslo University Hospital, Oslo, Norway.
Davit L AghayanThe Intervention Centre, Oslo University Hospital, Oslo, Norway.ORCID http://orcid.org/0000-0001-7051-3512
Rahul Prasanna KumarThe Intervention Centre, Oslo University Hospital, Oslo, Norway.
Rafael PalomarThe Intervention Centre, Oslo University Hospital, Oslo, Norway.
Åsmund Avdem FretlandThe Intervention Centre, Oslo University Hospital, Oslo, Norway.
Bjørn EdwinThe Intervention Centre, Oslo University Hospital, Oslo, Norway.
Ole Jakob ElleThe Intervention Centre, Oslo University Hospital, Oslo, Norway.
Oslo University Hospital · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional surgical navigation systems rely on preoperative imaging to provide guidance. In laparoscopic liver surgery, insufflation of the abdomen (pneumoperitoneum) can cause deformations on the liver, introducing inaccuracies in the correspondence between the preoperative images and the intraoperative reality. This study evaluates the improvements provided by intraoperative imaging for laparoscopic liver surgical navigation, when displayed as augmented reality (AR). Significant differences were found in terms of accuracy of the AR, in favor of intraoperative imaging. In addition, results showed an effect of user-induced error: image-to-patient registration based on annotations performed by clinicians caused 33% more inaccuracy as compared to image-to-patient registration algorithms that do not depend on user annotations. Hence, to achieve accurate surgical navigation for laparoscopic liver surgery, intraoperative imaging is recommendable to compensate for deformation. Moreover, user annotation errors may lead to inaccuracies in registration processes.

Indexed as

Augmented RealityAlgorithmsAnimalsHepatectomyHumansImage Processing, Computer-AssistedImaging, Three-DimensionalLaparoscopyLiverMonitoring, IntraoperativeOperating RoomsReproducibility of ResultsSurgery, Computer-AssistedSwineTomography, X-Ray Computed

Identifiers

PMID31822701
PMCPMC6904553
OpenAlexW2996409482

What OpenQuestion holds

Textmetadata
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.