Evidence map›Paper›PMID 26691327›Full record

ArticleBMC physiology2015

An investigation of the efficacy and mechanism of contrast-enhanced X-ray computed tomography utilizing iodine for large specimens through experimental and simulation approaches.

Zhiheng Li, Julia A Clarke, Richard A Ketcham, Matthew W Colbert, Fei Yan

Open access · hybridAbstract read
In one paragraph

Article in BMC physiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

19 citing papers in PubMed, 46 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 3D Muscle Architecture of the Pectoral Muscles of European Starling (Integrative organismal biology (Oxford, England) · 2019
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

5 authors at 2 institutions in 1 country.

Zhiheng LiDepartment of Geological Sciences, University of Texas at Austin, Austin, TX, USA. zhiheng_li@utexas.edu.
Julia A ClarkeDepartment of Geological Sciences, University of Texas at Austin, Austin, TX, USA. Julia_Clarke@jsg.utexas.edu.
Richard A KetchamDepartment of Geological Sciences, University of Texas at Austin, Austin, TX, USA. ketcham@jsg.utexas.edu.
Matthew W ColbertDepartment of Geological Sciences, University of Texas at Austin, Austin, TX, USA. colbert@jsg.utexas.edu.
Fei YanDepartment of Civil and Environmental Engineering, Rice University, Houston, TX, USA. feionline@gmail.com.
The University of Texas at Austin · USRice University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIodine-based solutions have long been known to be effective in aiding the differentiation among soft tissues in both fundamental anatomical research and for clinical diagnoses. Recently the combination of this particular contrasting agent with micro-computed tomography (micro-CT) has resulted in an array of high-quality image data, in which anatomical structures not visible in conventional CT can be identified and quantified. However, there has been only limited data available to inform detailed protocols for staining large specimens. Further, modeling of the staining mechanism has focused on simple diffusion processes.

resultsA low concentration of iodine-based buffered formalin solution with a long staining period was used to visualize soft-tissue structures in a large goose head. The staining effect was analyzed by serially measuring the micro-CT profiles across coronal sections throughout the staining period. Regular replacement of the staining solution combined with a longer staining period significantly improved contrast within tissues. A simplified one-dimensional Diffusion-Sorption model with a three-zone domain was used to simulate the diffusion process by calculating the concentration profile of iodine across the adductor region, which fits well with the experiment data. Observations of changes in the concentration of the staining agent and simulation results suggest that the sorption of iodine by tissues significantly affects the effective diffusion coefficient for the contrasting agent.

conclusionsThe Diffusion-Sorption model better explains previously reported difficulties in staining large samples comprised of tissues with high partition coefficients (K d ). Differences in partition coefficient (K d ), bulk density (ρ b ), and porosity (θ) could further explain the observed variation in staining rate and maximal staining effect among different tissues. Recommended protocols for staining large specimens are detailed.

Indexed as

Contrast MediaIodineAnimalsBrainGeeseImaging, Three-DimensionalTomography, X-Ray ComputedContrast MediaIodine

Identifiers

PMID26691327
PMCPMC4687389
OpenAlexW2221051871

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.