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

Thin-Walled Hollow Shafts01:15

Thin-Walled Hollow Shafts

217
In analyzing a thin-walled hollow shaft subjected to torsional loading, a segment with width dx is isolated for examination. Despite its equilibrium state, this segment faces torsional shearing forces at its ends. These forces are quantitatively described by the product of the longitudinal shearing stress on the segment's minor surface and the area of this surface, leading to the concept of shear flow. This shear flow is consistent throughout the structure, indicating a uniform distribution...
217
Shearing Stress01:19

Shearing Stress

754
Shearing stress, denoted by the Greek letter tau (τ), is stress caused by forces acting transversely on an object. These forces create internal ones within the entity in the plane where the external forces are applied. The resultant of these internal forces is the shear in the section.
The average shearing stress can be calculated by dividing the shear by the area of the cross-section.
754
Unsymmetric Loading of Thin-Walled Members: Problem Solving01:07

Unsymmetric Loading of Thin-Walled Members: Problem Solving

134
The shear center of a channel section with uniform thickness, height, and width, is determined by computing the shear force in the member and calculating the moments of inertia of the sections.
To compute the shear forces, find the shear flow at a specific distance from the endpoint using the vertical shear and the moment of inertia values. The total shear force on the flange is calculated by integrating the shear flow from one end of the flange to the other.
Next, calculate the moments of...
134

You might also read

Related Articles

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

Sort by
Same author

7 Tesla MR Imaging for Evaluation of Epilepsy.

Neuroimaging clinics of North America·2026
Same author

Clinical 7T MRI for Epilepsy: A Retrospective Review of 50 Cases.

AJNR. American journal of neuroradiology·2025
Same author

Optimising <sup>68</sup>Ga-SSTR PET radiomic feature extraction towards improved feature stability and predictive classification models for small neuroendocrine tumours.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2025
Same author

Validation of a TOPAS cone beam computed tomography (CBCT) Monte Carlo model towards personalised CBCT dosimetry in interventional radiology (IR).

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2025
Same author

Deep-Learning Accelerated Vessel Wall Imaging Using T1-SPACE at Ultra-High-Field Strength MRI.

AJNR. American journal of neuroradiology·2025
Same author

Evaluating the accuracy of SPECT/CT LSF estimations in SIRT therapies using Monte Carlo simulations with virtual 4D anthropomorphic phantoms.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2025

Related Experiment Video

Updated: Jul 27, 2025

Monitoring the Wall Mechanics During Stent Deployment in a Vessel
08:28

Monitoring the Wall Mechanics During Stent Deployment in a Vessel

Published on: May 8, 2012

9.3K

Development and Evaluation of a Multifrequency Ultrafast Doppler Spectral Analysis (MFUDSA) Algorithm for Wall Shear

Andrew J Malone1,2, Seán Cournane3, Izabela Naydenova1

  • 1School of Physics, Clinical and Optometric Sciences, IEO Centre, Faculty of Science and Health, Technological University Dublin, D07 H6K8 Dublin, Ireland.

Diagnostics (Basel, Switzerland)
|June 10, 2023
PubMed
Summary

A new Multifrequency ultrafast Doppler spectral analysis (MFUDSA) algorithm improves wall shear stress (WSS) measurement in atherosclerotic plaque. This offers potential for earlier cardiovascular disease diagnosis compared to existing methods.

Keywords:
Doppler ultrasoundbiomedical signal processingcardiovascular diseaseflow phantomquantitative ultrasoundsignal processing algorithmsultrasonographywall shear stress

More Related Videos

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

4.0K
A Cost-effective and Reliable Method to Predict Mechanical Stress in Single-use and Standard Pumps
07:34

A Cost-effective and Reliable Method to Predict Mechanical Stress in Single-use and Standard Pumps

Published on: August 5, 2015

9.5K

Related Experiment Videos

Last Updated: Jul 27, 2025

Monitoring the Wall Mechanics During Stent Deployment in a Vessel
08:28

Monitoring the Wall Mechanics During Stent Deployment in a Vessel

Published on: May 8, 2012

9.3K
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

4.0K
A Cost-effective and Reliable Method to Predict Mechanical Stress in Single-use and Standard Pumps
07:34

A Cost-effective and Reliable Method to Predict Mechanical Stress in Single-use and Standard Pumps

Published on: August 5, 2015

9.5K

Area of Science:

  • Biomedical Engineering
  • Cardiovascular Imaging
  • Medical Diagnostics

Background:

  • Cardiovascular diseases are a leading cause of death globally.
  • Current diagnostic methods primarily focus on vessel anatomy, potentially missing early disease indicators.
  • Wall shear stress (WSS) is an emerging biomarker for early atherosclerotic disease detection.

Purpose of the Study:

  • To introduce and validate a novel algorithm, Multifrequency ultrafast Doppler spectral analysis (MFUDSA), for quantifying WSS in atherosclerotic plaque.
  • To compare the performance of MFUDSA against existing WSS assessment techniques.
  • To evaluate the potential of MFUDSA for earlier cardiovascular disease diagnosis.

Main Methods:

  • Development and optimization of the MFUDSA algorithm using simulations and in-vitro flow phantom experiments.
  • Comparison of MFUDSA with standard pulsed-wave Doppler, Ultrafast Doppler, Parabolic Doppler, and plane-wave Doppler.
  • Assessment of signal-to-noise ratio (SNR) and velocity resolution improvements.

Main Results:

  • MFUDSA demonstrated a 4-8 fold increase in SNR and a 1.10-1.35 fold increase in velocity resolution compared to 1D Fourier analysis.
  • MFUDSA significantly differentiated WSS values between moderate (p = 0.003) and severe (p = 0.001) disease progression.
  • The algorithm showed superior performance in WSS assessment.

Conclusions:

  • MFUDSA is a promising novel algorithm for accurate WSS quantification in atherosclerotic plaque.
  • The enhanced performance of MFUDSA suggests its potential for earlier and more precise cardiovascular disease diagnosis.
  • This technique may offer advantages over current anatomical imaging methods for risk stratification.