ArticleCardiovascular and interventional radiology2026
Dual-camera Augmented Reality-Based Navigation System for Precision CT-guided Biopsy and Ablation.
Article in Cardiovascular and interventional radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
- Pragmatic Augmented Reality Navigation for Precision CT-Guided Percutaneous Interventions.Cardiovascular and interventional radiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
purposeTo develop and characterize a CT-mounted dual-camera navigation system for augmented reality (AR) in CT-guided needle procedures.
methodsTwo orthogonal cameras were mounted on the CT gantry. The position of an anthropomorphic liver phantom relative to the gantry was registered to the cameras. Phantom targets and anatomy were preprocedurally segmented and overlaid on a monitor. A needle was angled and manipulated to the targets with feedback based upon the axial and sagittal camera perspectives. In one iteration, an automatic needle segmentation with vector extension helped define virtual needle trajectories. Four interventional radiologists each performed 18 needle placements in three cohorts (n = 6 each): 1. Dual-camera-based navigation ("Cam-Nav"). 2. Dual-camera-based navigation plus automatic needle trajectory definition ("Path-Nav"), and 3. CT-guided "freehand". Needle placement accuracy (closest distance from needle to target center), angle error and placement time (from planning to final needle position) were measured.
resultsMedian needle placement accuracy using Cam-Nav, Path-Nav, and freehand was 5.3 mm (interquartile range 3.8-8.3), 5.1 mm (2.3-6.1), and 16.7 mm (7.7-26.6). Angle errors were 3.3 degrees (2.3-4.5), 2.6 degrees (2.3-3.8), and 9.7 degrees (6.1-15.3). Path-Nav demonstrated no difference in accuracy and angle error compared to Cam-Nav (p = 0.35, p = 0.43) but median errors were improved. Both camera techniques demonstrated better accuracy and angle errors (all p < 0.001) and showed shorter placement times (32 s [21-45], 36 s [26-60], p = 0.29) compared to freehand (86 s [65-114], both p < 0.001).
conclusionCT-mounted dual-camera navigation showed improved needle placement accuracy over freehand and may present a reliable, cost-effective, and rapid navigation option for percutaneous needle placements. No level of evidence, experimental study.
Indexed as
Identifiers
41329373What OpenQuestion holds
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.