Evidence map›Paper›PMID 40374683›Full record

ArticleScientific reports2025

Evaluating the EVA surgical navigation system for ureteral identification in an in vivo porcine model.

Veronica Penza, Domenico Soriero, Beatrice Sperotto, Alberto Neri, Jesus Ortiz, Davide Pertile, Lorenzo Epis, Giacomo Carganico, Marco Amisano, Stefano Scabini and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 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. Review
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

12 authors.

Veronica Penza *Advanced Robotics, Istituto Italiano di Tecnologia, 16163, Genoa, Italy. veronica.penza@iit.it.
Domenico Soriero *Chirurgia Oncologica Ospedaliera, IRCCS Ospedale Policlinico San Martino, 16132, Genoa, Italy.
Beatrice SperottoUniversity of Genoa, Genoa, Italy.
Alberto NeriAdvanced Robotics, Istituto Italiano di Tecnologia, 16163, Genoa, Italy.
Jesus OrtizAdvanced Robotics, Istituto Italiano di Tecnologia, 16163, Genoa, Italy.
Davide PertileChirurgia Oncologica Ospedaliera, IRCCS Ospedale Policlinico San Martino, 16132, Genoa, Italy.
Lorenzo EpisUniversity of Genoa, Genoa, Italy.
Giacomo CarganicoUniversity of Genoa, Genoa, Italy.
Marco AmisanoChirurgia Oncologica Ospedaliera, IRCCS Ospedale Policlinico San Martino, 16132, Genoa, Italy.
Stefano ScabiniChirurgia Oncologica Ospedaliera, IRCCS Ospedale Policlinico San Martino, 16132, Genoa, Italy.
Darwin G CaldwellAdvanced Robotics, Istituto Italiano di Tecnologia, 16163, Genoa, Italy.
Leonardo S MattosAdvanced Robotics, Istituto Italiano di Tecnologia, 16163, Genoa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surgical safety has emerged as a significant public health concern. Ureteral injury (UI) is one of the most common forms of iatrogenic urological issues, lacking non-invasive prevention strategies. In this context, computer-assisted technologies offer a promising solution for enhancing intra-operative safety. This paper presents an in-vivo study focused on evaluating the feasibility of using an augmented reality (AR) surgical navigation system (EVA) for intra-operative ureteral identification on an animal model. An experienced surgeon performed a technical assessment of the system. The clinical evaluation was conducted by four general surgeons tasked with identifying the left or right ureter, both with and without EVA. The technical assessment highlighted that EVA is easily integrable with operating room instruments, achieving a calibration accuracy of [Formula: see text], and the virtual ureter effectively overlapping with the real ureter. The questionnaires indicated that surgeons appreciated EVA, with a [Formula: see text]. The perceived mental demand, task complexity, and distractions were lower when using the EVA system. Future work will focus on increasing the number of subjects and exploring the efficacy of the system on other clinical tasks.

Indexed as

Augmented RealitySurgery, Computer-AssistedUreterAnimalsHumansModels, AnimalSwine

Identifiers

PMID40374683
PMCPMC12081927

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.