Evidence map›Paper›PMID 33258091›Full record

ArticleAnnals of biomedical engineering2021

Analyzing Liver Surface Indentation for In Vivo Refinement of Tumor Location in Minimally Invasive Surgery.

Yingqiao Yang, Kai-Leung Yung, Tin Wai Robert Hung, Kai-Ming Yu

Open access · hybridAbstract read
In one paragraph

Article in Annals of biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 48% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 1 institution in 1 country.

Yingqiao YangDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, R606, 1 Yuk Road, Hung Hom, Kowloon, Hong Kong. jasper.y.yang@connect.polyu.hk.ORCID http://orcid.org/0000-0001-6457-9101
Kai-Leung YungDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, R606, 1 Yuk Road, Hung Hom, Kowloon, Hong Kong.
Tin Wai Robert HungDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, R606, 1 Yuk Road, Hung Hom, Kowloon, Hong Kong.
Kai-Ming YuDepartment of Industrial and Systems Engineering, The Hong Kong Polytechnic University, R606, 1 Yuk Road, Hung Hom, Kowloon, Hong Kong.
Hong Kong Polytechnic University · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Manual palpation to update the position of subsurface tumor(s) is a normal practice in open surgery, but is not possible through the small incisions of minimally invasive surgery (MIS). This paper proposes a method that has the potential to use a simple constant-force indenter and the existing laparoscopic camera for tumor location refinement in MIS. The indenter floats with organ movement to generate a static surface deformation on the soft tissue, resolving problems of previous studies that require complicated measurement of force and displacement during indentation. By analyzing the deformation profile, we can intraoperatively update the tumor's location in real-time. Indentation experiments were conducted on healthy and "diseased" porcine liver specimens to obtain the deformation surrounding the indenter site. An inverse finite element (FE) algorithm was developed to determine the optimal material parameters of the healthy liver tissue. With these parameters, a computational model of tumorous tissue was constructed to quantitatively evaluate the effects of the tumor location on the induced deformation. By relating the experimental data from the "diseased" liver specimen to the computational results, we estimated the radial distance between the tumor and the indenter, as well as the angular position of the tumor relative to the indenter.

Indexed as

Minimally Invasive Surgical ProceduresModels, BiologicalAlgorithmsAnimalsFinite Element AnalysisLiverLiver NeoplasmsSwineInverse finite element analysisRobotic-assisted minimally invasive surgerySoft tissue modelingSurgical indentationTumor locating

Identifiers

PMID33258091
PMCPMC8058013
OpenAlexW3108040682

What OpenQuestion holds

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LicenceCC BY
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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.