Evidence map›Paper›PMID 35128089›Full record

ArticleHeliyon2022

Spatial analysis of histology in 3D: quantification and visualization of organ and tumor level tissue environment.

Pekka Ruusuvuori, Masi Valkonen, Kimmo Kartasalo, Mira Valkonen, Tapio Visakorpi, Matti Nykter, Leena Latonen

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
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  5. Article
  6. Article
  7. Article
  8. Article
  9. Comapping Cellular Content and Extracellular Matrix with Hemodynamics in Intact Arterial Tissues Using Scanning Immunofluorescent Multiphoton Microscopy.Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada · 2024
    Article
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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

7 authors at 3 institutions in 1 country.

Pekka RuusuvuoriInstitute of Biomedicine, University of Turku, Turku, Finland.
Masi ValkonenInstitute of Biomedicine, University of Turku, Turku, Finland.
Kimmo KartasaloFaculty of Medicine and Health Technology, Tampere University, Finland.
Mira ValkonenFaculty of Medicine and Health Technology, Tampere University, Finland.
Tapio VisakorpiFaculty of Medicine and Health Technology, Tampere University, Finland.
Matti NykterFaculty of Medicine and Health Technology, Tampere University, Finland.
Leena LatonenInstitute of Biomedicine, University of Eastern Finland, Kuopio, Finland.
Tampere University · FIUniversity of Turku · FIUniversity of Eastern Finland · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Histological changes in tissue are of primary importance in pathological research and diagnosis. Automated histological analysis requires ability to computationally separate pathological alterations from normal tissue. Conventional histopathological assessments are performed from individual tissue sections, leading to the loss of three-dimensional context of the tissue. Yet, the tissue context and spatial determinants are critical in several pathologies, such as in understanding growth patterns of cancer in its local environment. Here, we develop computational methods for visualization and quantitative assessment of histopathological alterations in three dimensions. First, we reconstruct the 3D representation of the whole organ from serial sectioned tissue. Then, we proceed to analyze the histological characteristics and regions of interest in 3D. As our example cases, we use whole slide images representing hematoxylin-eosin stained whole mouse prostates in a

Indexed as

3D reconstructionHistologyImage analysisQuantitative imagingSpatial analysisTissue analysisVisualization

Identifiers

PMID35128089
PMCPMC8800033
OpenAlexW4210444321

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.