Evidence map›Paper›PMID 28798525›Full record

ReviewJournal of toxicologic pathology2017

Bias in image analysis and its solution: unbiased stereology.

Danielle L Brown

Abstract readReview
In one paragraph

Review in Journal of toxicologic pathology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Dynamic Kidney Organoid Microphysiological Analysis Platform.bioRxiv : the preprint server for biology · 2024
    Article
  10. Arginine Vasotocin Directly Regulates Spermatogenesis in Adult Zebrafish (International journal of molecular sciences · 2024
    Article
  11. Article
  12. Article
  13. ACS materials Au · 2022
    Article
  14. Review
  15. The Use of Quantitative Digital Pathology to Measure Proteoglycan and Glycosaminoglycan Expression and Accumulation in Healthy and Diseased Tissues.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2021
    Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

1 author.

Danielle L BrownCharles River Laboratories, Pathology Associates, 4025 Stirrup Creek Drive, Suite 150, Durham, NC 27703, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the human eye is excellent for pattern recognition, it often lacks the sensitivity to detect subtle changes in particle density. Because of this, quantitative evaluation may be required in some studies. A common type of quantitative assessment used for routine toxicology studies is two-dimensional histomorphometry. Although this technique can provide additional information about the tissue section being examined, it does not give information about the tissue as a whole. Furthermore, it produces biased (inaccurate) data that does not take into account the size, shape, or orientation of particles. In contrast, stereology is a technique that utilizes stringent sampling methods to obtain three-dimensional information about the entire tissue that is unbiased. The purpose of this review is to illuminate the sources of bias with two-dimensional morphometry, how it can affect the data, and how that bias is minimized with stereology.

Indexed as

biasmorphometrypathologystereology

Identifiers

PMID28798525
PMCPMC5545670

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.