Evidence map›Paper›PMID 38125508›Full record

ArticleHeliyon2023

A high-fidelity virtual liver model incorporating biological characteristics.

Xiaorui Zhang, Wenzheng Zhang, Wei Sun, Aiguo Song, Tong Xu

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Xiaorui ZhangSchool of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
Wenzheng ZhangSchool of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
Wei SunCollege of Automation, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
Aiguo SongCollege of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China.
Tong XuUniversity of Southern California, Los Angeles, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flexible tissue modeling plays an important role in the field of telemedicine. It is related to whether the soft tissue deformation process can be accurately, real-time and vividly simulated during surgery. However, most existing models lack the unique biological characteristics. To solve this problem, we proposed a high-fidelity virtual liver model incorporating biological characteristics, such as the viscoelastic, anisotropic and nonlinear biological characteristics. Besides, to the best of our knowledge, our study is the first to introduce the viscoplasticity of biological tissues to improve the fidelity of the liver model. This mothod was proposed to describe the viscoplastic characteristics of the diseased liver resection process, when the liver is in a state of excessive deformation and loss of elasticity, however, there are few works focusing on this problem. The 3DMax2020 and OpenGL4.6 were used to build a liver surgery simulation platform, and the PHANTOM OMNI manual controller was used to sense the feedback force during the operation. The proposed model was verified from three aspects of accuracy, fidelity and real-time performance. The experimental results show that the proposed virtual liver model can enhance visual perception ability, improve deformation accuracy and fidelity.

Indexed as

Biological characteristicsLiver soft tissue deformationTelemedicineViscoplasticity

Identifiers

PMID38125508
PMCPMC10731058

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.