A Magnetic Resonance Imaging-based Computational Protocol for Analysis of Plaque Morphology and Hemodynamics in...

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Cardiovascular Research

Background:

• Current internal carotid artery (ICA) stenosis assessment relies on imaging (DUS, CTA) that doesn't capture stroke risk factors like plaque vulnerability or hemodynamics.
• Estimating plaque composition and hemodynamic forces offers a more comprehensive stroke risk evaluation than percentage stenosis alone.

Purpose of the Study:

• To present a non-invasive, patient-specific protocol for characterizing plaque composition and hemodynamic loads in ICA stenosis.
• To integrate quantitative multi-contrast atherosclerosis characterization (qMatch) MRI with patient-specific computational fluid dynamics (CFD) for detailed analysis.

Main Methods:

• Utilizing qMatch MRI for detailed plaque composition analysis.
• Creating CFD models from phase contrast (PC) MRI and CTA/TOF-MRI for anatomical data and flow waveforms.
• Developing 3D geometric models of the carotid bifurcation, prescribing flow waveforms, and applying a Windkessel model for ICA hemodynamics.
• Solving Navier-Stokes equations to obtain high-resolution velocity and pressure data for hemodynamic assessment.

Main Results:

• The integrated MRI-CFD approach enables identification of hemodynamic differences across ICA stenosis.
• Plaque composition and hemodynamic loads can be quantitatively analyzed in a patient-specific manner.
• This method provides a detailed understanding of the embolic potential of carotid plaques.

Conclusions:

• This protocol offers a non-invasive method for advanced characterization of ICA stenosis.
• Combining qMatch MRI and CFD provides a more complete assessment of stroke risk by evaluating plaque vulnerability and hemodynamics.
• This approach has the potential to improve patient management and stroke prevention strategies.