Evidence map›Paper›PMID 41375877›Full record

ReviewJournal of clinical medicine2025

Technological Advances in Intra-Operative Navigation: Integrating Fluorescence, Extended Reality, and Artificial Intelligence.

Edward Murphy, Ronan A Cahill

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Edward MurphyUCD Centre for Precision Surgery, 47 Eccles Street, Phibsboro, D07 Y9AW Dublin, Ireland.
Ronan A CahillUCD Centre for Precision Surgery, 47 Eccles Street, Phibsboro, D07 Y9AW Dublin, Ireland.ORCID 0000-0002-1270-4000

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surgical navigation is a rapidly advancing area of innovation that has extended from its roots as a tool based on rigid anatomical landmarks into the complex domain of soft-tissue surgery. Three complementary technologies-fluorescence-guided surgery (FGS), extended reality (XR), and artificial intelligence (AI)-are converging to provide real-time visualisation and decision support. FGS, most often currently using indocyanine green (ICG), is now widely applied for perfusion assessment, lymphatic mapping, and biliary anatomy delineation, with growing evidence of improved surgical safety and efficacy. Targeted fluorophores are under development to enable disease-specific imaging, while XR platforms can overlay three-dimensional reconstructions onto the operative field to enhance spatial orientation. AI offers the potential to standardise interpretation, reduce variability, and analyse complex intra-operative datasets to guide surgical decisions. Despite these advances, significant barriers remain before broad clinical deployment, including technical limitations, limited high-quality evidence, training demands and regulatory and ethical challenges. The near future of surgical navigation lies in integrating FGS, XR, and AI into a cohesive system that enhances precision, safety, and outcomes and remains adaptable to future imaging and therapeutic innovations.

Indexed as

artificial intelligenceaugmented realityfluorescence-guided surgeryindocyanine greensurgical navigation

Identifiers

PMID41375877
PMCPMC12693097

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.