Evidence map›Paper›PMID 32016687›Full record

Article3D printing in medicine2020

Simulation of semilunar valve function: computer-aided design, 3D printing and flow assessment with MR.

Nabil Hussein, Pascal Voyer-Nguyen, Sharon Portnoy, Brandon Peel, Eric Schrauben, Christopher Macgowan, Shi-Joon Yoo

Abstract read
In one paragraph

Article in 3D printing in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Bioinspired functional materials for biomedical applications.Frontiers in bioengineering and biotechnology · 2026
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  4. Article
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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

7 authors.

Nabil HusseinDivision of Cardiology, Department of Paediatrics and Division of Cardiovascular Surgery, Department of Surgery, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Pascal Voyer-NguyenCenter for Image-Guided Innovation and Therapeutic Intervention (CIGITI), Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Sharon PortnoyMedical Biophysics & Medical Imaging, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Brandon PeelCenter for Image-Guided Innovation and Therapeutic Intervention (CIGITI), Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Eric SchraubenMedical Biophysics & Medical Imaging, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Christopher MacgowanMedical Biophysics & Medical Imaging, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Shi-Joon YooDepartment of Diagnostic Imaging and Division of Cardiology, Department of Paediatrics Hospital for Sick Children, University of Toronto, 555 University Avenue, Toronto, Ontario, M5G1X8, Canada. shi-joon.yoo@sickkids.ca.ORCID http://orcid.org/0000-0002-9952-8504

Funding

Peter and Fabiola Butler NA
6 · The paper itself

Abstract

backgroundThe structure of the valve leaflets and sinuses are crucial in supporting the proper function of the semilunar valve and ensuring leaflet durability. Therefore, an enhanced understanding of the structural characteristics of the semilunar valves is fundamental to the evaluation and staging of semilunar valve pathology, as well as the development of prosthetic or bioprosthetic valves. This paper illustrates the process of combining computer-aided design (CAD), 3D printing and flow assessment with 4-dimensional flow magnetic resonance imaging (MRI) to provide detailed assessment of the structural and hemodynamic characteristics of the normal semilunar valve.

methodsPreviously published geometric data on the aortic valve was used to model the 'normal' tricuspid aortic valve with a CAD software package and 3D printed. An MRI compatible flow pump with the capacity to mimic physiological flows was connected to the phantom. A peak flow rate of 100 mL/s and heart rate of 60 beats per minute were used. MRI measurements included cine imaging, 2D and 4D phase-contrast imaging to assess valve motion, flow velocity and complex flow patterns.

resultsCine MRI data showed normal valve function and competency throughout the cardiac cycle in the 3D-printed phantom. Quantitative analysis of 4D Flow data showed net flow through 2D planes proximal and distal to the valve were very consistent (26.03 mL/s and 26.09 mL/s, respectively). Measurements of net flow value agreed closely with the flow waveform provided to the pump (27.74 mL/s), confirming 4D flow acquisition in relation to the pump output. Peak flow values proximal and distal to the valve were 78.4 mL/s and 63.3 mL/s, respectively. Particle traces of flow from 4D-phase contrast MRI data demonstrated flow through the valve into the ascending aorta and vortices within the aortic sinuses, which are expected during ventricular diastole.

conclusionIn this proof of concept study, we have demonstrated the ability to generate physiological 3D-printed aortic valve phantoms and evaluate their function with cine- and 4D Flow MRI. This technology can work synergistically with promising tissue engineering research to develop optimal aortic valve replacements, which closely reproduces the complex function of the normal aortic valve.

Indexed as

3D-printing4D-flow MRIAortic valveComputer-aided design

Identifiers

PMID32016687
PMCPMC6998846

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LicenceCC BY
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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.