Evidence map›Paper›PMID 41801604›Full record

ArticleJournal of robotic surgery2026

Accuracy and reliability of an augmented reality prototype for robot-assisted partial nephrectomy: a preclinical study with 3D-printed kidney phantoms (UroCCR 168).

F Rubat Baleuri, M Pattou, G Margue, G Nguyen, A Pitout, A Khaddad, K Chandelon, J Desternes, N Bourdel, J-C Bernhard and 1 more

Abstract read
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In one paragraph

Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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

11 authors.

F Rubat BaleuriUrology Department, Bordeaux University Hospital, Bordeaux, 33000, France. federico.rubat@gmail.com.ORCID http://orcid.org/0009-0006-9724-8353
M PattouUrology Department, Bordeaux University Hospital, Bordeaux, 33000, France.
G MargueUrology Department, Bordeaux University Hospital, Bordeaux, 33000, France.
G Nguyen, SurgAR, Clermont-Ferrand, 63000, France.
A PitoutUrology Department, Bordeaux University Hospital, Bordeaux, 33000, France.
A KhaddadUrology Department, Bordeaux University Hospital, Bordeaux, 33000, France.
K Chandelon, SurgAR, Clermont-Ferrand, 63000, France.
J Desternes, SurgAR, Clermont-Ferrand, 63000, France.
N Bourdel, SurgAR, Clermont-Ferrand, 63000, France.
J-C BernhardUrology Department, Bordeaux University Hospital, Bordeaux, 33000, France.
A Bartoli, SurgAR, Clermont-Ferrand, 63000, France.

Funding

Agence Nationale de la Recherche ANR-21-RHUS-0015
6 · The paper itself

Abstract

Augmented Reality (AR) systems can enhance intraoperative anatomical understanding during Robot-Assisted Partial Nephrectomy by overlaying preoperative 3D models onto the surgical view. Their usefulness, however, depends on the spatial accuracy of these overlays, which requires objective validation. This preclinical study quantitatively evaluated the spatial accuracy of a new AR software prototype using a validation workflow based on 3D-printed kidney phantoms and a Structure-from-Motion (SfM) reconstruction as ground truth. CT scans were segmented to create virtual kidney models that were 3D printed and filmed with the da Vinci Si camera. The AR prototype was applied to the recordings, and manual 3D registration was performed using the TilePro interface. Keyframes from manual and tracking-based registrations were analysed to compute the Target Registration Error (TRE), defined as the mean Euclidean distance between corresponding vertices of the AR and SfM models. Three operators repeated the workflow, and manual registration time was recorded to assess variability and feasibility. Mean TRE across experiments was below 5 mm, indicating clinically acceptable accuracy. TRE values for individual keyframes remained consistently under 10 mm, with limited inter-operator variability (ICC(3,k) = 0.80). Manual and tracking TREs were comparable and strongly correlated (β = 0.89; p < 0.001). Tracking-related precision changes varied among operators, and mean manual registration time was 173.6 ± 76.4 s. Accuracy was unaffected by keyframe count, kidney variability, or registration duration. This methodology offers an objective, reproducible framework for assessing AR registration in preclinical settings. The prototype showed reliable spatial performance, supporting progression toward in vivo validation.

Indexed as

Augmented RealityKidneyNephrectomyPhantoms, ImagingPrinting, Three-DimensionalRobotic Surgical ProceduresHumansImaging, Three-DimensionalModels, AnatomicReproducibility of ResultsSoftwareTomography, X-Ray Computed3D registrationAugmented realityRobot-Assisted partial nephrectomyStructure-from-MotionSurgical navigationTarget registration errorValidation methodology

Identifiers

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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.