Evidence map›Paper›PMID 29968183›Full record

ReviewMolecular imaging and biology2018

X-ray-Based 3D Virtual Histology-Adding the Next Dimension to Histological Analysis.

J Albers, S Pacilé, M A Markus, M Wiart, G Vande Velde, G Tromba, C Dullin

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular imaging and biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. Review
  2. Article
  3. Quantitative Stain Mapping in X-Ray Virtual Histology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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
    Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Three-dimensional analysis of human pancreatic cancer specimens by phase-contrast based X-ray tomography - the next dimension of diagnosis.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023
    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

7 authors.

J AlbersInstitute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany.
S PaciléDepartment of Engineering and Architecture, University of Trieste, Trieste, Italy.
M A MarkusTranslational Molecular Imaging, Max-Planck-Institute for Experimental Medicine, Göttingen, Germany.
M WiartUniv Lyon, CarMeN Laboratory, INSERM, INRA, INSA Lyon, Université Claude Bernard Lyon 1, 69500, Bron, France.
G Vande VeldeDepartment of Imaging and Pathology, Faculty of Medicine, KU Leuven-University of Leuven, Leuven, Belgium.
G TrombaElettra Sincrotrone Trieste, Trieste, Italy.
C DullinInstitute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany. Christian.dullin@med.uni-goettingen.de.ORCID http://orcid.org/0000-0003-4297-8077

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Histology and immunohistochemistry of thin tissue sections have been the standard diagnostic procedure in many diseases for decades. This method is highly specific for particular tissue regions or cells, but mechanical sectioning of the specimens is required, which destroys the sample in the process and can lead to non-uniform tissue deformations. In addition, regions of interest cannot be located beforehand and the analysis is intrinsically two-dimensional. Micro X-ray computed tomography (μCT) on the other hand can provide 3D images at high resolution and allows for quantification of tissue structures, as well as the localization of small regions of interest. These advantages advocate the use of μCT for virtual histology tool with or without subsequent classical histology. This review summarizes the most recent examples of virtual histology and provides currently known possibilities of improving contrast and resolution of μCT. Following a background in μCT imaging, ex vivo staining procedures for contrast enhancement are presented as well as label-free virtual histology approaches and the technologies, which could rapidly advance it, such as phase-contrast CT. Novel approaches such as zoom tomography and nanoparticulate contrast agents will also be considered. The current evidence suggests that virtual histology may present a valuable addition to the workflow of histological analysis, potentially reducing the workload in pathology, refining tissue classification, and supporting the detection of small malignancies.

Indexed as

HistologyImaging, Three-DimensionalUser-Computer InterfaceAnimalsHumansNanoparticlesStaining and LabelingX-RaysHistologyPhase contrastSoft-tissue stainingSynchrotronX-ray imagingμCT

Identifiers

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.