Evidence map›Paper›PMID 33715047›Full record

ArticleInternational journal of computer assisted radiology and surgery2021

Complex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic images.

Annika Niemann, Samuel Voß, Riikka Tulamo, Simon Weigand, Bernhard Preim, Philipp Berg, Sylvia Saalfeld

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. 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
  2. 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, D-39106, Magdeburg, Germany. annika.niemann@ovgu.de.ORCID http://orcid.org/0000-0001-8774-814X
Samuel VoßLaboratory of Fluid Dynamics and Technical Flows, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Riikka TulamoDepartment of Vascular Surgery, and Neurosurgery Research Group, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
Simon WeigandDepartment of General, Visceral and Transplantation Surgery, Hospital of the University of Munich, Campus Grosshadern, Munich, Germany.
Bernhard PreimFaculty of Computer Science, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, D-39106, Magdeburg, Germany.
Philipp BergLaboratory of Fluid Dynamics and Technical Flows, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Sylvia SaalfeldFaculty of Computer Science, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, D-39106, Magdeburg, Germany.

Funding

Deutsche Forschungsgemeinschaft SA 3461/2-1SA 3461/2-1Deutsche ForschungsgemeinschaftDeutsche Forschungsgemeinschaft BE 6230/2-1BE 6230/2-1Forschungscampus STIMULATE 13GW0095A13GW0095A
6 · The paper itself

Abstract

purposeFor the evaluation and rupture risk assessment of intracranial aneurysms, clinical, morphological and hemodynamic parameters are analyzed. The reliability of intracranial hemodynamic simulations strongly depends on the underlying models. Due to the missing information about the intracranial vessel wall, the patient-specific wall thickness is often neglected as well as the specific physiological and pathological properties of the vessel wall.

methodsIn this work, we present a model for structural simulations with patient-specific wall thickness including different tissue types based on postmortem histologic image data. Images of histologic 2D slices from intracranial aneurysms were manually segmented in nine tissue classes. After virtual inflation, they were combined into 3D models. This approach yields multiple 3D models of the inner and outer wall and different tissue parts as a prerequisite for subsequent simulations.

resultWe presented a pipeline to generate 3D models of aneurysms with respect to the different tissue textures occurring in the wall. First experiments show that including the variance of the tissue in the structural simulation affect the simulation result. Especially at the interfaces between neighboring tissue classes, the larger influence of stiffer components on the stability equilibrium became obvious.

conclusionThe presented approach enables the creation of a geometric model with differentiated wall tissue. This information can be used for different applications, like hemodynamic simulations, to increase the modeling accuracy.

Indexed as

CadaverComputer SimulationElastic ModulusFinite Element AnalysisHemodynamicsHumansImaging, Three-DimensionalIntracranial AneurysmReproducibility of ResultsRisk AssessmentAneurysm wallHistologic imagesIntracranial aneurysmsStructural simulation

Identifiers

PMID33715047
PMCPMC8052238

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.