Evidence map›Paper›PMID 39253492›Full record

ArticlebioRxiv : the preprint server for biology2024

Computational modeling of left ventricular flow using PC-CMR-derived four-dimensional wall motion.

Seyed Babak Peighambari, Tanmay Mukherjee, Emilio A Mendiola, Amr Darwish, Lucas H Timmins, Roderic I Pettigrew, Dipan J Shah, Reza Avazmohammadi

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Seyed Babak PeighambariDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.ORCID 0009-0001-1398-0111
Tanmay MukherjeeDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0002-0191-3878
Emilio A MendiolaDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Amr DarwishHouston Methodist DeBakey Heart & Vascular Center, Houston, TX, United States.
Lucas H TimminsDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Roderic I PettigrewDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Dipan J ShahHouston Methodist DeBakey Heart & Vascular Center, Houston, TX, United States.
Reza AvazmohammadiDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0001-9787-1117

Funding

The effect of systemic hypertension on prognosis of myocardial infarction: Understanding, prediction and therapy evaluationR00HL138288 · NHLBI · TEXAS ENGINEERING EXPERIMENT STATION · PI AVAZMOHAMMADI, REZA · 2020 to 2022
$727k
NHLBI NIH HHS R00 HL138288
6 · The paper itself

Abstract

Intracardiac hemodynamics plays a crucial role in the onset and development of cardiac and valvular diseases. Simulations of blood flow in the left ventricle (LV) have provided valuable insight into assessing LV hemodynamics. While fully coupled fluid-solid modelings of the LV remain challenging due to the complex passive-active behavior of the LV wall myocardium, the integration of imaging-driven quantification of structural motion with computational fluid dynamics (CFD) modeling in the LV holds the promise of feasible and clinically translatable characterization of patient-specific LV hemodynamics. In this study, we propose to integrate two magnetic resonance imaging (MRI) modalities with the moving-boundary CFD method to characterize intracardiac LV hemodynamics. Our method uses the standard cine cardiac magnetic resonance (CMR) images to estimate four-dimensional myocardial motion, eliminating the need for involved myocardial material modeling to capture LV wall behavior. In conjunction with CMR, phase contrast-MRI (PC-MRI) was used to measure temporal blood inflow rates at the mitral orifice, serving as an additional boundary condition. Flow patterns, including velocity streamlines, vortex rings, and kinetic energy, were characterized and compared to the available data. Moreover, relationships between LV wall kinematic markers and flow characteristics were determined without myocardial material modeling and using a non-rigid image registration (NRIR) method. The fidelity of the simulation was quantitatively evaluated by validating the flow rate at the aortic outflow tract against respective PC-MRI measures. The proposed methodology offers a novel and feasible toolset that works with standard PC-CMR protocols to improve the clinical assessment of LV characteristics in prognostic studies and surgical planning.

Indexed as

Cardiac computational fluid dynamics modelingCardiac magnetic resonance imagingLeft ventricle hemodynamicsphase-contrast imaging

Identifiers

PMID39253492
PMCPMC11383313

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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.