Evidence map›Paper›PMID 29670533›Full record

ReviewFrontiers in physiology2018

Thrombosis in Cerebral Aneurysms and the Computational Modeling Thereof: A Review.

Malebogo N Ngoepe, Alejandro F Frangi, James V Byrne, Yiannis Ventikos

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in physiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
3.1field-weighted citation impact, top 9% 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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 60 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Modeling Fibrin Accumulation on Flow-Diverting Devices for Intracranial Aneurysms.International journal for numerical methods in biomedical engineering · 2024
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Computational Fluid Dynamics for the Prediction of Endograft Thrombosis in the Superficial Femoral Artery.Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists · 2023
    Article
  17. Article
  18. Article
  19. Article
  20. Review
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 4 institutions in 2 countries.

Malebogo N NgoepeDepartment of Mechanical Engineering, University of Cape Town, Cape Town, South Africa.
Alejandro F FrangiCenter for Computational Imaging and Simulation Technologies in Biomedicine, University of Sheffield, Sheffield, United Kingdom.
James V ByrneDepartment of Neuroradiology, John Radcliffe Hospital, Oxford, United Kingdom.
Yiannis VentikosUCL Mechanical Engineering, University College London, London, United Kingdom.
Council for Scientific and Industrial Research · ZAJohn Radcliffe Hospital · GBUniversity College London · GBUniversity of Sheffield · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thrombosis is a condition closely related to cerebral aneurysms and controlled thrombosis is the main purpose of endovascular embolization treatment. The mechanisms governing thrombus initiation and evolution in cerebral aneurysms have not been fully elucidated and this presents challenges for interventional planning. Significant effort has been directed towards developing computational methods aimed at streamlining the interventional planning process for unruptured cerebral aneurysm treatment. Included in these methods are computational models of thrombus development following endovascular device placement. The main challenge with developing computational models for thrombosis in disease cases is that there exists a wide body of literature that addresses various aspects of the clotting process, but it may not be obvious what information is of direct consequence for what modeling purpose (e.g., for understanding the effect of endovascular therapies). The aim of this review is to present the information so it will be of benefit to the community attempting to model cerebral aneurysm thrombosis for interventional planning purposes, in a simplified yet appropriate manner. The paper begins by explaining current understanding of physiological coagulation and highlights the documented distinctions between the physiological process and cerebral aneurysm thrombosis. Clinical observations of thrombosis following endovascular device placement are then presented. This is followed by a section detailing the demands placed on computational models developed for interventional planning. Finally, existing computational models of thrombosis are presented. This last section begins with description and discussion of physiological computational clotting models, as they are of immense value in understanding how to construct a general computational model of clotting. This is then followed by a review of computational models of clotting in cerebral aneurysms, specifically. Even though some progress has been made towards computational predictions of thrombosis following device placement in cerebral aneurysms, many gaps still remain. Answering the key questions will require the combined efforts of the clinical, experimental and computational communities.

Indexed as

cerebral aneurysmcomputational modelingflow diverterinterventional planningthrombosis

Identifiers

PMID29670533
PMCPMC5893827
OpenAlexW2794854394

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.