Evidence map›Paper›PMID 21892370›Full record

ArticleThe open medical informatics journal2011

Micro soft tissues visualization based on x-ray phase-contrast imaging.

Lu Zhang, Shuqian Luo

Open access · hybridAbstract read
In one paragraph

Article in The open medical informatics journal, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. [Diffraction-enhanced imaging and in-line phase contrast imaging with synchrotron radiation for human intra-hepatic bile duct dilation ex vivo].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2015
    Article
  5. Article
  6. 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

2 authors at 1 institution in 1 country.

Lu ZhangSchool of Biomedical Engineering, Capital Medical University, Beijing, China.
Shuqian Luo
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current imaging methods have a limited ability to visualize microstructures of biological soft tissues. Small lesions cannot be detected at the early stage of the disease. Phase contrast imaging (PCI) is a novel non-invasive imaging technique that can provide high contrast images of soft tissues by the use of X-ray phase shift. It is a new choice in terms of non-invasively revealing soft tissue details. In this study, the lung and hepatic fibrosis models of mice and rats were used to investigate the ability of PCI in microstructures observation of soft tissues. Our results demonstrated that different liver fibrosis stages could be distinguished non-invasively by PCI. The three-dimensional morphology of a segment of blood vessel was constructed. Noteworthy, the blood clot inside the vessel was visualized in three dimensions which provided a precise description of vessel stenosis. Furthermore, the whole lung airways including the alveoli were obtained. We had specifically highlighted its use in the visualization and assessment of the alveoli. To our knowledge, this was the first time for non-invasive alveoli imaging using PCI. This finding may offer a new perspective on the diagnosis of respiratory disease. All the results confirmed that PCI will be a valuable tool in biological soft tissues imaging.

Indexed as

alveoli.diffraction enhanced imaging (DEI)hepatic fibrosisin-line X-ray phase contrast imaging (IL-XPCI)microvesselPhase contrast imaging (PCI)

Identifiers

PMID21892370
PMCPMC3151592
OpenAlexW2030901624

What OpenQuestion holds

Textmetadata
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.