Evidence map›Paper›PMID 33051774›Full record

ReviewHistochemistry and cell biology2021

Stereology as the 3D tool to quantitate lung architecture.

Lars Knudsen, Christina Brandenberger, Matthias Ochs

Abstract readReview
In one paragraph

Review in Histochemistry and cell biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. January In focus in HCB.Histochemistry and cell biology · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. A short primer on lung stereology.Respiratory research · 2021
    Review
  10. Review
  11. Review
  12. Introduction: 3D imaging in lung biology.Histochemistry and cell biology · 2021
    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

3 authors.

Lars KnudsenInstitute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany.
Christina BrandenbergerInstitute of Functional and Applied Anatomy, Hannover Medical School, Hannover, Germany.
Matthias OchsInstitute of Functional Anatomy, Charité-Universitätsmedizin Berlin, Philippstr. 11, 10115, Berlin, Germany. matthias.ochs@charite.de.ORCID http://orcid.org/0000-0002-0936-6979

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stereology is the method of choice for the quantitative assessment of biological objects in microscopy. It takes into account the fact that, in traditional microscopy such as conventional light and transmission electron microscopy, although one has to rely on measurements on nearly two-dimensional sections from fixed and embedded tissue samples, the quantitative data obtained by these measurements should characterize the real three-dimensional properties of the biological objects and not just their "flatland" appearance on the sections. Thus, three-dimensionality is a built-in property of stereological sampling and measurement tools. Stereology is, therefore, perfectly suited to be combined with 3D imaging techniques which cover a wide range of complementary sample sizes and resolutions, e.g. micro-computed tomography, confocal microscopy and volume electron microscopy. Here, we review those stereological principles that are of particular relevance for 3D imaging and provide an overview of applications of 3D imaging-based stereology to the lung in health and disease. The symbiosis of stereology and 3D imaging thus provides the unique opportunity for unbiased and comprehensive quantitative characterization of the three-dimensional architecture of the lung from macro to nano scale.

Indexed as

Imaging, Three-DimensionalAnimalsHumansLungMicroscopy, ElectronLaser scanning microscopyLungMicro-computed tomographyStereologyVolume electron microscopy

Identifiers

PMID33051774
PMCPMC7910236

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.