Evidence map›Paper›PMID 37703675›Full record

ArticleMedical image analysis2023

The value of Augmented Reality in surgery - A usability study on laparoscopic liver surgery.

João Ramalhinho, Soojeong Yoo, Thomas Dowrick, Bongjin Koo, Murali Somasundaram, Kurinchi Gurusamy, David J Hawkes, Brian Davidson, Ann Blandford, Matthew J Clarkson

Abstract read
In one paragraph

Article in Medical image analysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Warm-started reinforcement learning for iterative 3D/2D liver registration.International journal of computer assisted radiology and surgery · 2026
    Article
  6. Review
  7. Digs: diffusion-guided Gaussian Splatting for dynamic occlusion surgical scene reconstruction.International journal of computer assisted radiology and surgery · 2026
    Article
  8. Article
  9. Liver mask-guided SAM-enhanced dual-decoder network for landmark segmentation in AR-guided surgery.International journal of computer assisted radiology and surgery · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Non-rigid image-volume registration for human livers in laparoscopic surgery.Quantitative imaging in medicine and surgery · 2025
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. 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

10 authors.

João RamalhinhoWellcome ESPRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom. Electronic address: joao.ramalhinho.15@ucl.ac.uk.
Soojeong YooWellcome ESPRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom; UCL Interaction Centre, University College London, London, United Kingdom.
Thomas DowrickWellcome ESPRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom.
Bongjin KooWellcome ESPRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom.
Murali SomasundaramDivision of Surgery and Interventional Sciences, University College London, London, United Kingdom.
Kurinchi GurusamyDivision of Surgery and Interventional Sciences, University College London, London, United Kingdom.
David J HawkesWellcome ESPRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom.
Brian DavidsonDivision of Surgery and Interventional Sciences, University College London, London, United Kingdom.
Ann BlandfordWellcome ESPRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom; UCL Interaction Centre, University College London, London, United Kingdom.
Matthew J ClarksonWellcome ESPRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Augmented Reality (AR) is considered to be a promising technology for the guidance of laparoscopic liver surgery. By overlaying pre-operative 3D information of the liver and internal blood vessels on the laparoscopic view, surgeons can better understand the location of critical structures. In an effort to enable AR, several authors have focused on the development of methods to obtain an accurate alignment between the laparoscopic video image and the pre-operative 3D data of the liver, without assessing the benefit that the resulting overlay can provide during surgery. In this paper, we present a study that aims to assess quantitatively and qualitatively the value of an AR overlay in laparoscopic surgery during a simulated surgical task on a phantom setup. We design a study where participants are asked to physically localise pre-operative tumours in a liver phantom using three image guidance conditions - a baseline condition without any image guidance, a condition where the 3D surfaces of the liver are aligned to the video and displayed on a black background, and a condition where video see-through AR is displayed on the laparoscopic video. Using data collected from a cohort of 24 participants which include 12 surgeons, we observe that compared to the baseline, AR decreases the median localisation error of surgeons on non-peripheral targets from 25.8 mm to 9.2 mm. Using subjective feedback, we also identify that AR introduces usability improvements in the surgical task and increases the perceived confidence of the users. Between the two tested displays, the majority of participants preferred to use the AR overlay instead of navigated view of the 3D surfaces on a separate screen. We conclude that AR has the potential to improve performance and decision making in laparoscopic surgery, and that improvements in overlay alignment accuracy and depth perception should be pursued in the future.

Indexed as

Augmented RealityLaparoscopySurgery, Computer-AssistedHumansImaging, Three-DimensionalLiverAugmented realityImage-guided surgeryLaparoscopic surgeryUsability

Identifiers

PMID37703675
PMCPMC10958137

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.