Evidence map›Paper›PMID 37457926›Full record

ArticleInternational journal of bioprinting2023

Multifunctional high-simulation 3D-printed hydrogel model manufacturing engineering for surgical training.

Xiaodong Xu, Shijie Yu, Liang Ma, Jinlei Mao, Hao Chen, Zhihao Zhu, Li Wang, Hui Lin, Jing Zhang, Zhifei Wang

Abstract read
In one paragraph

Article in International journal of bioprinting, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

7 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Review
  6. Observational
  7. Article
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

10 authors.

Xiaodong XuCollege of Materials Science and Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310014, China.
Shijie YuCollege of Materials Science and Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310014, China.
Liang MaCollege of Materials Science and Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310014, China.
Jinlei MaoDepartment of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang 310014, China.
Hao ChenDepartment of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang 310014, China.
Zhihao ZhuDepartment of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang 310014, China.
Li WangDepartment of Ultrasound Medicine, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang 310014, China.
Hui LinCollege of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310058, China.
Jing ZhangCollege of Materials Science and Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310014, China.
Zhifei WangDepartment of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery, Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang 310014, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advanced bionic organ models with vivid biological structures and wetness and softness are essential for medical-surgical training. Still, there are many challenges in the preparation process, such as matching mechanical properties, good feedback on surgical instruments, reproducibility of specific surgical scenarios, and distinguishability between structural levels. In this paper, we achieved tissuemimicking dual-network (DN) hydrogels with customizable stiffness by adjusting the composition of the hydrogel matrix and the immersion time of the ionic solution to match different biological soft tissues precisely. Combined with advanced threedimensional (3D) printing fabrication techniques, various performance-tunable bionic hydrogel organ models with structural complexity and fidelity, including kidney, liver, pancreas, and vascular tissues, were perfectly fabricated. The simulation and applicability of the model were also simulated for the forced change of the suture needle in the puncture and suture of a single tissue and between different tissues, the cutting of substantive organs by ultrasonic scalpel, the coagulation and hemostasis of blood vessels, the visualization of the internal structure under ultrasound, and the microwave ablation of liver tumors. By constructing advanced biomimetic organ models based on hydrogel with specific and tunable properties, the development of surgical training, medical device testing, and medical education reform will be significantly promoted.

Indexed as

3D printing fabricationBionic organ modelsDual-network hydrogelsSurgical trainingTunable properties

Identifiers

PMID37457926
PMCPMC10339442

What OpenQuestion holds

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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.