Evidence map›Paper›PMID 31705419›Full record

ArticleInternational journal of computer assisted radiology and surgery2020

Interactive exploration of a 3D intracranial aneurysm wall model extracted from histologic slices.

Annika Niemann, Simon Weigand, Thomas Hoffmann, Martin Skalej, Riikka Tulamo, Bernhard Preim, Sylvia Saalfeld

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Multimodal exploration of the intracranial aneurysm wall.International journal of computer assisted radiology and surgery · 2023
    Article
  3. Article
  4. Review
  5. Complex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic images.International journal of computer assisted radiology and surgery · 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

7 authors.

Annika NiemannFaculty of Computer Science, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany. annika.niemann@ovgu.de.ORCID http://orcid.org/0000-0001-8774-814X
Simon WeigandLudwig-Maximilians-Universität Klinikum, Munich, Germany.
Thomas HoffmannResearch Campus STIMULATE, Magdeburg, Germany.
Martin SkalejUniversity Hospital Magdeburg, Magdeburg, Germany.
Riikka TulamoHelsinki University Hospital, University of Helsinki, Helsinki, Finland.
Bernhard PreimFaculty of Computer Science, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany.
Sylvia SaalfeldFaculty of Computer Science, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany.

Funding

Bundesministerium für Bildung und Forschung 13GW0095AGerman Research Foundation SA 3461/2-1
6 · The paper itself

Abstract

purposeCurrently no detailed in vivo imaging of the intracranial vessel wall exists. Ex vivo histologic images can provide information about the intracranial aneurysm (IA) wall composition that is useful for the understanding of IA development and rupture risk. For a 3D analysis, the 2D histologic slices must be incorporated in a 3D model which can be used for a spatial evaluation of the IA's morphology, including analysis of the IA neck.

methodsIn 2D images of histologic slices, different wall layers were manually segmented and a 3D model was generated. The nuclei were automatically detected and classified as round or elongated, and a neural network-based wall type classification was performed. The information was combined in a software prototype visualization providing a unique view of the wall characteristics of an IA and allowing interactive exploration. Furthermore, the heterogeneity (as variance of the wall thickness) of the wall was evaluated.

resultA 3D model correctly representing the histologic data was reconstructed. The visualization integrating wall information was perceived as useful by a medical expert. The classification produces a plausible result.

conclusionThe usage of histologic images allows to create a 3D model with new information about the aneurysm wall. The model provides information about the wall thickness, its heterogeneity and, when performed on cadaveric samples, includes information about the transition between IA neck and sac.

Indexed as

CadaverHumansImaging, Three-DimensionalIntracranial AneurysmAneurysm wallHistologic imagesIntracranial aneurysms

Identifiers

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Registered trials

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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.