Evidence map›Paper›PMID 29769600›Full record

ArticleScientific reports2018

X-ray based virtual histology allows guided sectioning of heavy ion stained murine lungs for histological analysis.

Jonas Albers, M Andrea Markus, Frauke Alves, Christian Dullin

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
6.5field-weighted citation impact, top 3% 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

34 citing papers in PubMed, 52 citations in OpenAlex.

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  13. The potential of x-ray virtual histology in the diagnosis of skin tumors.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024
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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

4 authors at 3 institutions in 2 countries.

Jonas AlbersInstitute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany. jonas.albers@med.uni-goettingen.de.ORCID 0000-0002-2957-8282
M Andrea MarkusTranslational Molecular Imaging, Max-Planck-Institute for Experimental Medicine, Göttingen, Germany.
Frauke AlvesInstitute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany.
Christian DullinInstitute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany.ORCID 0000-0003-4297-8077
Universitätsmedizin Göttingen · DEElettra-Sincrotrone Trieste S.C.p.A. · ITMax Planck Institute of Experimental Medicine · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Examination of histological or immunohistochemically stained 2D sections of embedded tissue is one of the most frequently used tools in biomedical research and clinical routine. Since to date, targeted sectioning of specific regions of interest (ROI) in the sample is not possible, we aimed at developing a guided sectioning approach based on x-ray 3D virtual histology for heavy ion stained murine lung samples. For this purpose, we increased the contrast to noise ratio of a standard benchtop microCT by 5-10-fold using free-propagation phase contrast imaging and thus substantially improved image quality. We then show that microCT 3D datasets deliver more precise anatomical information and quantification of the sample than traditional histological sections, which display deformations of the tissue. To quantify these deformations caused by sectioning we developed the "Displacement Index (DI)", which combines block-matching with the calculation of the local mutual information. We show that the DI substantially decreases when a femtosecond laser microtome is used for sections as opposed to a traditional microtome. In conclusion, our microCT based virtual histology approach can be used as a supplement and a guidance tool for traditional histology, providing 3D measurement capabilities and offering the ability to perform sectioning directly at an ROI.

Indexed as

Heavy IonsAnimalsFemaleHistological TechniquesImaging, Three-DimensionalLungMiceStaining and LabelingX-Ray Microtomography

Identifiers

PMID29769600
PMCPMC5955938
OpenAlexW2803575853

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.