Evidence map›Paper›PMID 38696084›Full record

ArticleUpdates in surgery2024

Augmented reality improving intraoperative navigation in minimally invasive liver surgery: an interplay between 3D reconstruction and indocyanine green.

Francesca Ratti, Matteo Serenari, Diletta Corallino, Luca Aldrighetti

Abstract read
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In one paragraph

Article in Updates in surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
5.7field-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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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  3. Review
  4. 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

4 authors at 2 institutions in 1 country.

Francesca RattiHepatobiliary Surgery Division, IRCCS San Raffaele Scientific Institute, Milan, Italy. ratti.francesca@hsr.it.ORCID http://orcid.org/0000-0002-8108-9064
Matteo SerenariHepatobiliary and Transplant Unit, IRCCS, Azienda Ospedaliero-Universitaria di Bologna, Sant'Orsola-Malpighi Hospital, Bologna, Italy.
Diletta CorallinoHepatobiliary Surgery Division, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Luca AldrighettiHepatobiliary Surgery Division, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Vita-Salute San Raffaele University · ITIRCCS Azienda Ospedliero-Universitaria di Bologna Policlinico di Sant'Orsola · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technology have helped surgeons to increase MILS feasibility, so that currently liver surgery evolution is strongly based on technological advances and the same trend is expected even further soon. Aim of the present technical report is to provide insights regarding the possible interplay between 3D reconstructions based on augmented reality and intraoperative navigation by indocyanine green fluorescence. Augmented reality methods based on reconstructions created through artificial intelligence interact synergistically. The better the understanding of the anatomy and characteristics of the lesion, the more accurate the preoperative planning may be scheduled. On the other hand, the better the intraoperative navigation, the more reproducible the preoperative planning becomes.

Indexed as

Augmented RealityHepatectomyImaging, Three-DimensionalIndocyanine GreenSurgery, Computer-AssistedColoring AgentsHumansLiverLiver NeoplasmsMinimally Invasive Surgical ProceduresColoring AgentsIndocyanine Green3D reconstructionAugmented realityIndocyanine greenLiver surgery

Identifiers

PMID38696084
OpenAlexW4396580087

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.