ArticleBMC surgery2024
Developing a phantom for simulating robotic-assisted complete mesocolic excision using 3D printing and medical imaging.
Article in BMC surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 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
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Hands-on Distance Simulation of Technical Skills: A Systematic Review.Simulation in healthcare : journal of the Society for Simulation in Healthcare · 2026Pooled it
- Efficacy of the "critical view/open book" concept for implementing standardized right hemicolectomy with complete mesocolic excision-results from a series of minimally invasive surgical training courses.Surgical endoscopy · 2026Article
- Development of an electrosurgery-compatible simulation task for quantitatively assessing oral cancer resection skills: initial validity evidence.BMC medical education · 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
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRobotic-assisted complete mesocolic excision is an advanced procedure mainly because of the great variability in anatomy. Phantoms can be used for simulation-based training and assessment of competency when learning new surgical procedures. However, no phantoms for robotic complete mesocolic excision have previously been described. This study aimed to develop an anatomically true-to-life phantom, which can be used for training with a robotic system situated in the clinical setting and can be used for the assessment of surgical competency.
methodsEstablished pathology and surgical assessment tools for complete mesocolic excision and specimens were used for the phantom development. Each assessment item was translated into an engineering development task and evaluated for relevance. Anatomical realism was obtained by extracting relevant organs from preoperative patient scans and 3D printing casting moulds for each organ. Each element of the phantom was evaluated by two experienced complete mesocolic excision surgeons without influencing each other's answers and their feedback was used in an iterative process of prototype development and testing.
resultsIt was possible to integrate 35 out of 48 procedure-specific items from the surgical assessment tool and all elements from the pathological evaluation tool. By adding fluorophores to the mesocolic tissue, we developed an easy way to assess the integrity of the mesocolon using ultraviolet light. The phantom was built using silicone, is easy to store, and can be used in robotic systems designated for patient procedures as it does not contain animal-derived parts.
conclusionsThe newly developed phantom could be used for training and competency assessment for robotic-assisted complete mesocolic excision surgery in a simulated setting.
Indexed as
Identifiers
What 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.