Evidence map›Paper›PMID 40514606›Full record

ArticleAnnals of biomedical engineering2025

Hemodynamic Characterization of Peripheral Arterio-Venous Malformations Using Rapid Contrast-Enhanced MR Imaging: An In Vitro and In Vivo Study.

Camilla Giulia Calastra, Marika Bono, Aloma Blanch Granada, Aleksandra Tuleja, Sarah Maike Bernhard, Vanessa Diaz-Zuccarini, Stavroula Balabani, Dominik Obrist, Hendrik von Tengg-Kobligk, Bernd Jung

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Camilla Giulia CalastraDepartment of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland. camilla.calastra@yahoo.com.ORCID http://orcid.org/0009-0003-7051-7056
Marika BonoARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
Aloma Blanch GranadaDepartment of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.ORCID http://orcid.org/0000-0002-1699-5693
Aleksandra TulejaDivision of Angiology, Swiss Cardiovascular Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0002-7108-418X
Sarah Maike BernhardDivision of Angiology, Swiss Cardiovascular Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0002-2750-5928
Vanessa Diaz-ZuccariniDepartment of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.ORCID http://orcid.org/0000-0003-3183-7463
Stavroula BalabaniDepartment of Mechanical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.ORCID http://orcid.org/0000-0002-6287-1106
Dominik ObristARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0002-6062-9076
Hendrik von Tengg-Kobligk *Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0000-0003-3207-3223
Bernd Jung *Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID http://orcid.org/0009-0002-3659-0930

Funding

Sinergia CRSII5_193694.
6 · The paper itself

Abstract

purposePeripheral arterio-venous malformations (pAVMs) are vascular defects often requiring extensive medical treatment. To improve disease management, hemodynamic markers based on 2D Digital Subtraction Angiography (DSA) data were previously defined to classify pAVMs. However, DSA offers only 2D information, involves ionizing radiation, and requires intra-arterial intervention. We hypothesized that pAVMs could be classified with the same approach with 3D dynamic contrast-enhanced MR-based data. To this end, the present work aims to develop a computational classification system for pAVMs using 3D dynamic contrast-enhanced MR-based data.

methodsA pAVM phantom was imaged using both DSA and MRI to validate the methodology, which was then applied to 10 MR-based in vivo datasets. A semi-automated vessel detection algorithm, based on the standard deviation of each voxel or pixel in time, was used. Classification was performed by identifying the time of arrival (CA

resultsNormalized CA

conclusionsMR image quality and temporal resolution are sufficient to allow a classification of pAVMs. This classification method has the potential to become a diagnostic tool for the surgical navigation of pAVMs for clinicians.

Indexed as

Arteriovenous MalformationsHemodynamicsMagnetic Resonance ImagingAdultAngiography, Digital SubtractionContrast MediaFemaleHumansMalePhantoms, ImagingContrast MediaCE-trMRAMR imagingValidationVascular malformationsYakes AVMs classification

Identifiers

PMID40514606
PMCPMC12390877

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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.