Evidence map›Paper›PMID 32210520›Full record

ArticleJournal of fluids and structures2020

A reduced-order flow model for vocal fold vibration: from idealized to subject-specific models.

Ye Chen, Zheng Li, Siyuan Chang, Bernard Rousseau, Haoxiang Luo

Abstract read
In one paragraph

Article in Journal of fluids and structures, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

5 authors.

Ye ChenDepartment of Mechanical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235-1592.
Zheng LiDepartment of Mechanical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235-1592.
Siyuan ChangDepartment of Mechanical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235-1592.
Bernard RousseauDepartment of Communication Science and Disorders, University of Pittsburgh.
Haoxiang LuoDepartment of Mechanical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235-1592.

Funding

Development of a Patient-Specific Surgical Planning Tool for Type I LaryngoplastyR01DC016236 · NIDCD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI COYLE, JAMES L · 2018 to 2022
$2.4M
NIDCD NIH HHS R01 DC016236
6 · The paper itself

Abstract

We present a reduced-order model for fluid-structure interaction (FSI) simulation of vocal fold vibration during phonation. This model couples the three-dimensional (3D) tissue mechanics and a one-dimensional (1D) flow model that is derived from the momentum and mass conservation equations for the glottal airflow. The effects of glottal entrance and pressure loss in the glottis are incorporated in the flow model. We consider both idealized vocal fold geometries and subject-specific anatomical geometries segmented from the MRI images of rabbits. For the idealized vocal fold geometries, we compare the simulation results from the 1D/3D hybrid FSI model with those from the full 3D FSI simulation based on an immersed-boundary method. For the subject-specific geometries, we incorporate previously estimated tissue properties for individual samples and compare the results with those from the high-speed imaging experiment of in vivo phonation. In both setups, the comparison shows good agreement in the vibration frequency, amplitude, phase delay, and deformation pattern of the vocal fold, which suggests potential application of the present approach for future patient-specific modeling.

Indexed as

fluid–structure interactionphonationreduced-order modelsubject-specific modelvocal fold

Identifiers

PMID32210520
PMCPMC7093056

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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.