Evidence map›Paper›PMID 34611845›Full record

ArticleCardiovascular engineering and technology2022

A Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations.

Gaia Franzetti, Mirko Bonfanti, Cyrus Tanade, Chung Sim Lim, Janice Tsui, George Hamilton, Vanessa Díaz-Zuccarini, Stavroula Balabani

Open access · hybridAbstract read
In one paragraph

Article in Cardiovascular engineering and technology, 2022. 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
0.7field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Gaia Franzetti *Department of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.ORCID 0000-0001-9800-0962
Mirko Bonfanti *Department of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.ORCID 0000-0001-5548-3298
Cyrus TanadeDepartment of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
Chung Sim LimDepartment of Vascular Surgery, Royal Free Hospital NHS Foundation Trust, Pond Street, London, NW3 2QG, UK.
Janice TsuiDepartment of Vascular Surgery, Royal Free Hospital NHS Foundation Trust, Pond Street, London, NW3 2QG, UK.ORCID 0000-0001-6826-4211
George HamiltonDepartment of Vascular Surgery, Royal Free Hospital NHS Foundation Trust, Pond Street, London, NW3 2QG, UK.ORCID 0000-0003-4962-2348
Vanessa Díaz-ZuccariniDepartment of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK. v.diaz@ucl.ac.uk.ORCID 0000-0003-3183-7463
Stavroula BalabaniDepartment of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK. s.balabani@ucl.ac.uk.ORCID 0000-0002-6287-1106
Royal Free London NHS Foundation Trust · GBWellcome / EPSRC Centre for Interventional and Surgical Sciences · GBUniversity College London · GB

Funding

British Heart Foundation FS/15/22/31356Wellcome TrustWellcome Trust 203145Z/16/Z
6 · The paper itself

Abstract

purposePeripheral arteriovenous malformations (pAVMs) are congenital lesions characterised by abnormal high-flow, low-resistance vascular connections-the so-called nidus-between arteries and veins. The mainstay treatment typically involves the embolisation of the nidus, however the complexity of pAVMs often leads to uncertain outcomes. This study aims at developing a simple, yet effective computational framework to aid the clinical decision making around the treatment of pAVMs using routinely acquired clinical data.

methodsA computational model was developed to simulate the pre-, intra-, and post-intervention haemodynamics of a patient-specific pAVM. A porous medium of varying permeability was employed to simulate the sclerosant effect on the nidus haemodynamics. Results were compared against clinical data (digital subtraction angiography, DSA, images) and experimental flow-visualization results in a 3D-printed phantom of the same pAVM.

resultsThe computational model allowed the simulation of the pAVM haemodynamics and the sclerotherapy-induced changes at different interventional stages. The predicted inlet flow rates closely matched the DSA-derived data, although the post-intervention one was overestimated, probably due to vascular system adaptations not accounted for numerically. The nidus embolization was successfully captured by varying the nidus permeability and increasing its hydraulic resistance from 0.330 to 3970 mmHg s ml

conclusionThe study demonstrates that the haemodynamic effects of the embolisation procedure can be simulated from routinely acquired clinical data via a porous medium with varying permeability as evidenced by the good qualitative agreement between numerical predictions and both in vivo and in vitro data. It provides a fundamental building block towards a computational treatment-planning framework for AVM embolisation.

Indexed as

Arteriovenous MalformationsEmbolization, TherapeuticAngiography, Digital SubtractionHemodynamicsHumansArteriovenous malformationBlood flowComputational fluid dynamicsExperimental fluid dynamicsPatient-specific

Identifiers

PMID34611845
PMCPMC9114032
OpenAlexW3204171314

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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.