Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

MRI-Based Pressure Gradient Mapping in Patient-Specific Models of Coarctation of the Aorta.

medRxiv : the preprint server for health sciences·2026
Same author

Impact of guideline definitions on right ventricular diameter in echocardiography: an automated analysis in controls and patients with pulmonary hypertension.

Echo research and practice·2026
Same author

SDFStent: Real-time interactive virtual stenting via SDF deformation fields.

ArXiv·2026
Same author

Per-vessel myocardial blood flow improvement after coronary artery bypass graft surgery quantified by CT myocardial perfusion imaging.

Journal of cardiovascular computed tomography·2026
Same author

Standardized End Point Definitions for Clinical Trials in Thoracic Aortic Repair: A Consensus Report From the ARCH-Academic Research Consortium.

Circulation·2026
Same author

A Continuum of Atrial Peristalsis Initiates the Bicuspid to Quadricuspid Valve Transition.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Dec 29, 2025

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

4.3K

Fluid-structure interaction simulations of patient-specific aortic dissection.

Kathrin Bäumler1, Vijay Vedula2, Anna M Sailer3

  • 13D and Quantitative Imaging Laboratory, Department of Radiology, Stanford University, Stanford, CA, 94305, USA. baeumler@stanford.edu.

Biomechanics and Modeling in Mechanobiology
|January 30, 2020
PubMed
Summary

Computational fluid dynamic simulations of aortic dissection are improved by a new framework. This model accounts for the dissection flap's mobility, which significantly impacts blood flow and pressure dynamics.

Keywords:
4D flow MRIAortic dissectionComputational hemodynamicsFluid–structure interactionPrestressTissue support

More Related Videos

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
06:18

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Published on: December 6, 2024

922
In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging
11:16

In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging

Published on: February 25, 2022

3.7K

Related Experiment Videos

Last Updated: Dec 29, 2025

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
13:07

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

Published on: January 15, 2022

4.3K
Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
06:18

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Published on: December 6, 2024

922
In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging
11:16

In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging

Published on: February 25, 2022

3.7K

Area of Science:

  • Biomedical Engineering
  • Computational Mechanics
  • Cardiovascular Science

Background:

  • Aortic dissection involves a mobile membrane separating true and false lumens, complicating accurate computational fluid dynamic (CFD) simulations.
  • Existing CFD models struggle to capture the dynamic interplay between vessel wall deformation, blood flow, and pressure in patient-specific aortic dissection cases.

Purpose of the Study:

  • To develop and validate a comprehensive numerical framework for patient-specific CFD simulations of aortic dissection.
  • To investigate the influence of dissection flap mobility and material properties on hemodynamics within the aorta.

Main Methods:

  • A patient-specific model was created using computed tomography angiography (CTA) data.
  • A two-way fluid-structure interaction (FSI) model incorporated prestress, external tissue support, arterial tethering, and distinct elastic moduli for the dissection flap and aortic wall.
  • Physiologically realistic boundary conditions were derived from 4D flow MRI and blood pressure measurements.

Main Results:

  • The numerical framework accurately captured the cyclical deformation of the dissection membrane and showed good agreement with 4D flow MRI data.
  • Decreasing flap stiffness significantly increased flap displacement, reduced time-averaged wall shear stress (TAWSS) surface area, decreased pressure differences between lumens, and lowered true lumen flow rate.

Conclusions:

  • The mobility of the dissection flap is a critical factor influencing local hemodynamics in aortic dissection.
  • Patient-specific CFD simulations must account for dissection flap mobility for accurate hemodynamic assessment.
  • Further research into flap stiffness measurement is needed to advance CFD applications in aortic dissection treatment.