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).
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.
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.
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.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Augmented reality in robotic urology: from 3D printed models to cognitive surgical systems. A systematic literature review.Journal of robotic surgery · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
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.
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Registered trials
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.