Evidence map›Paper›PMID 32040812›Full record

ArticleJournal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract2021

Augmented Reality during Open Liver Surgery Using a Markerless Non-rigid Registration System.

Nicolas Golse, Antoine Petit, Maïté Lewin, Eric Vibert, Stéphane Cotin

Abstract read
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In one paragraph

Article in Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
4.7field-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

29 citing papers in PubMed, 2 syntheses or guidelines pooled it, 83 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
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  7. Towards a zero-shot low-latency navigation for open surgery augmented reality applications.International journal of computer assisted radiology and surgery · 2025
    Article
  8. Non-rigid image-volume registration for human livers in laparoscopic surgery.Quantitative imaging in medicine and surgery · 2025
    Article
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  18. Registration Sanity Check for AR-guided Surgical Interventions: Experience From Head and Face Surgery.IEEE journal of translational engineering in health and medicine · 2024
    Article
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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

5 authors at 2 institutions in 1 country.

Nicolas Golse *Department of Surgery, Paul-Brousse Hospital, Assistance Publique Hôpitaux de Paris, Centre Hépato-Biliaire, 12 Avenue Paul Vaillant Couturier, 94804, Villejuif Cedex, France. nicolasgolse@me.com.ORCID 0000-0002-5261-1538
Antoine Petit *Inria, Strasbourg, France.
Maïté LewinDepartment of Radiology, Paul-Brousse Hospital, Assistance Publique Hôpitaux de Paris, Centre Hépato-Biliaire, 94800, Villejuif, France.
Eric Vibert *Department of Surgery, Paul-Brousse Hospital, Assistance Publique Hôpitaux de Paris, Centre Hépato-Biliaire, 12 Avenue Paul Vaillant Couturier, 94804, Villejuif Cedex, France.
Stéphane CotinInria, Strasbourg, France.
Université Paris-Sud · FRAssistance Publique – Hôpitaux de Paris · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIntraoperative navigation during liver resection remains difficult and requires high radiologic skills because liver anatomy is complex and patient-specific. Augmented reality (AR) during open liver surgery could be helpful to guide hepatectomies and optimize resection margins but faces many challenges when large parenchymal deformations take place. We aimed to experiment a new vision-based AR to assess its clinical feasibility and anatomical accuracy. PATIENTS AND

methodsBased on preoperative CT scan 3-D segmentations, we applied a non-rigid registration method, integrating a physics-based elastic model of the liver, computed in real time using an efficient finite element method. To fit the actual deformations, the model was driven by data provided by a single RGB-D camera. Five livers were considered in this experiment. In vivo AR was performed during hepatectomy (n = 4), with manual handling of the livers resulting in large realistic deformations. Ex vivo experiment (n = 1) consisted in repeated CT scans of explanted whole organ carrying internal metallic landmarks, in fixed deformations, and allowed us to analyze our estimated deformations and quantify spatial errors.

resultsIn vivo AR tests were successfully achieved in all patients with a fast and agile setup installation (< 10 min) and real-time overlay of the virtual anatomy onto the surgical field displayed on an external screen. In addition, an ex vivo quantification demonstrated a 7.9 mm root mean square error for the registration of internal landmarks.

conclusionThese first experiments of a markerless AR provided promising results, requiring very little equipment and setup time, yet providing real-time AR with satisfactory 3D accuracy. These results must be confirmed in a larger prospective study to definitively assess the impact of such minimally invasive technology on pathological margins and oncological outcomes.

Indexed as

Augmented RealitySurgery, Computer-AssistedHumansImaging, Three-DimensionalLiverProspective StudiesAugmented realityLiver resectionNon-rigid registrationRGB-D camera

Identifiers

PMID32040812
OpenAlexW3006341343

What OpenQuestion holds

Textmetadata
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.