ArticleSurgical endoscopy2026
Development and validation of 3D-printed anatomically accurate liver model for endoscopic ultrasound-based endo-hepatology training (with video).
Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEx vivo endoscopic ultrasound (EUS) training relies on animal tissue, which is anatomically variable, perishable, and requires dedicated endoscopes. As EUS-based liver assessment (EUS-LA)-including parenchymal imaging, shear-wave elastography (SWE), attenuation imaging, and EUS-guided liver biopsy (EUS-LB)-expands, an anatomically accurate, tissue-free training platform could be a valuable educational tool. We developed a synthetic training tool that integrated a gelatin liver and silicone foregut and assessed its validity.
methodsCT data from a healthy female were extracted to three-dimensionally print a liver replica. The replica was used to create a negative mold to cast a gelatin matrix around color-coded vasculature, then integrated with silicone esophagus/stomach/duodenum model to recreate normal foregut/liver anatomy. Sixteen endoscopists (12 experts from five centers in two countries; 4 novices) performed standardized EUS-LA across four tasks. Content validity (12 experts) was summarized with a content-validity index (CVI); inter-rater agreement used Gwet's AC1 with 95% confidence intervals (CI); face validity and global satisfaction were assessed in all 16.
resultsComposite CVI was 0.85 (AC1 0.68, 95% CI 0.54-0.83; p < 0.0001). CVI realism was 0.87, with perfect endorsement for liver parenchyma (1.00; AC1 0.90) and high endorsement for quantitative imaging (0.95; AC1 0.88); vascular realism was lower (0.73), with expert agreement no better than chance (AC1 0.41; p = 0.17). CVI relevance was 0.90 and representativeness 0.77. The complete workflow, including the EUS-LB maneuver, vessel avoidance, and SWE/attenuation acquisition, was completed by 100% of evaluable participants. All endorsed use before ex vivo training, and 93.8% would recommend the model; global satisfaction was 4.25 (IQR 4-5).
conclusionsThe anatomically accurate, synthetic training model showed strong content and face validity and supported the complete diagnostic endo-hepatology workflow in a reproducible manner. Vascular realism is the principal target for refinement.
Indexed as
Identifiers
42618822What 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.