Evidence map›Paper›PMID 39720761›Full record

ArticleHealthcare technology letters2024

Intraoperative patient-specific volumetric reconstruction and 3D visualization for laparoscopic liver surgery.

Luca Boretto, Egidijus Pelanis, Alois Regensburger, Kaloian Petkov, Rafael Palomar, Åsmund Avdem Fretland, Bjørn Edwin, Ole Jakob Elle

Abstract read
In one paragraph

Article in Healthcare technology letters, 2024. 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
–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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Navigated hepatic tumor resection using intraoperative ultrasound imaging.International journal of computer assisted radiology and surgery · 2026
    Article
  5. Article
  6. 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.

Luca BorettoSiemens Healthcare AS Oslo Norway.ORCID https://orcid.org/0009-0005-8360-1817
Egidijus PelanisThe Intervention Centre Oslo University Hospital Rikshospitalet Oslo Norway.
Alois RegensburgerSiemens Healthineers AG Forchheim Germany.
Kaloian PetkovSiemens Medical Solutions USA, Inc. Princeton New Jersey USA.
Rafael PalomarThe Intervention Centre Oslo University Hospital Rikshospitalet Oslo Norway.
Åsmund Avdem FretlandThe Intervention Centre Oslo University Hospital Rikshospitalet Oslo Norway.
Bjørn EdwinThe Intervention Centre Oslo University Hospital Rikshospitalet Oslo Norway.
Ole Jakob ElleDepartment of Informatics Faculty of Mathematics and Natural Sciences University of Oslo Oslo Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the benefits of minimally invasive surgery, interventions such as laparoscopic liver surgery present unique challenges, like the significant anatomical differences between preoperative images and intraoperative scenes due to pneumoperitoneum, patient pose, and organ manipulation by surgical instruments. To address these challenges, a method for intraoperative three-dimensional reconstruction of the surgical scene, including vessels and tumors, without altering the surgical workflow, is proposed. The technique combines neural radiance field reconstructions from tracked laparoscopic videos with ultrasound three-dimensional compounding. The accuracy of our reconstructions on a clinical laparoscopic liver ablation dataset, consisting of laparoscope and patient reference posed from optical tracking, laparoscopic and ultrasound videos, as well as preoperative and intraoperative computed tomographies, is evaluated. The authors propose a solution to compensate for liver deformations due to pressure applied during ultrasound acquisitions, improving the overall accuracy of the three-dimensional reconstructions compared to the ground truth intraoperative computed tomography with pneumoperitoneum. A unified neural radiance field from the ultrasound and laparoscope data, which allows real-time view synthesis providing surgeons with comprehensive intraoperative visual information for laparoscopic liver surgery, is trained.

Indexed as

augmented realitybiomedical imagingcomputer visionlivermedical image processingobject trackingoptical trackingultrasonic imagingvirtual reality

Identifiers

PMID39720761
PMCPMC11665787

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Registered trials

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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.