Evidence map›Paper›PMID 35918564›Full record

ArticleVisual computing for industry, biomedicine, and art2022

Open-source algorithm and software for computed tomography-based virtual pancreatoscopy and other applications.

Haofan Huang, Xiaxia Yu, Mu Tian, Weizhen He, Shawn Xiang Li, Zhengrong Liang, Yi Gao

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Visual computing for industry, biomedicine, and art, 2022. 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 46% 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, 2 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 3 institutions in 2 countries.

Haofan Huang *School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.
Xiaxia Yu *School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.
Mu Tian *School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.
Weizhen HeSchool of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.
Shawn Xiang LiSchool of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.
Zhengrong LiangLaboratory for Imaging Research and Informatics, State University of New York, Stony Brook, NY, 11794, USA. jerome.liang@sunysb.edu.
Yi GaoSchool of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China. gaoyi@szu.edu.cn.ORCID http://orcid.org/0000-0003-0094-8136
Shenzhen University Health Science Center · CNShenzhen University · CNState University of New York · US

Funding

Advancing Virtual Colonoscopy for Early Cancer ScreeningR01CA206171 · NCI · STATE UNIVERSITY NEW YORK STONY BROOK · PI LIANG, JEROME Z · 2016 to 2020
$2.0M
Education Department of Guangdong Province 2017KZDXM072Key-Area Research and Development Program of Guangdong Province 2021B0101420005Key Technology Development Program of Shenzhen JSGG20210713091811036National Natural Science Foundation of China 61601302NCI NIH HHS R01 CA206171Shenzhen Key Laboratory Foundation ZDSYS20200811143757022Shenzhen Municipal Government's "Peacock Plan" KQTD2016053112051497SZU Top Ranking Project 860/00000210
6 · The paper itself

Abstract

Pancreatoscopy plays a significant role in the diagnosis and treatment of pancreatic diseases. However, the risk of pancreatoscopy is remarkably greater than that of other endoscopic procedures, such as gastroscopy and bronchoscopy, owing to its severe invasiveness. In comparison, virtual pancreatoscopy (VP) has shown notable advantages. However, because of the low resolution of current computed tomography (CT) technology and the small diameter of the pancreatic duct, VP has limited clinical use. In this study, an optimal path algorithm and super-resolution technique are investigated for the development of an open-source software platform for VP based on 3D Slicer. The proposed segmentation of the pancreatic duct from the abdominal CT images reached an average Dice coefficient of 0.85 with a standard deviation of 0.04. Owing to the excellent segmentation performance, a fly-through visualization of both the inside and outside of the duct was successfully reconstructed, thereby demonstrating the feasibility of VP. In addition, a quantitative analysis of the wall thickness and topology of the duct provides more insight into pancreatic diseases than a fly-through visualization. The entire VP system developed in this study is available at https://github.com/gaoyi/VirtualEndoscopy.git .

Indexed as

3D SlicerPancreatic cancerPancreatic duct segmentationVirtual pancreatoscopy

Identifiers

PMID35918564
PMCPMC9346031
OpenAlexW4289516972

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.