Bayesian multipoint velocity encoding for concurrent flow and turbulence mapping.

Area of Science:

• Cardiovascular imaging
• Biomedical engineering
• Fluid dynamics

Background:

• Accurate measurement of blood flow is crucial for diagnosing cardiovascular diseases and evaluating medical devices.
• Existing methods for quantifying blood flow dynamics, particularly turbulent kinetic energy, face limitations in speed, accuracy, and dynamic range.

Purpose of the Study:

• To develop and validate an efficient approach for measuring 3D velocity vector fields and turbulent kinetic energy in blood flow.
• To assess the performance of this new method compared to existing techniques using numerical simulations and in vitro measurements.
• To demonstrate the clinical potential for hemodynamic assessment of prosthetic heart valves.

Main Methods:

• Utilized multipoint phase-contrast imaging combined with Bayesian analysis for velocity mapping.
• Employed spatiotemporal undersampling to achieve clinically acceptable scan times.
• Validated the approach using numerical simulations and in vitro experiments with aortic valve phantoms.

Main Results:

• The Bayesian multipoint velocity encoding method demonstrated lower errors in velocity and turbulent kinetic energy over a larger dynamic range compared to previous methods.
• Significant differences in peak velocity and turbulent kinetic energy were observed between different prosthetic aortic valves (CoreValve vs. St. Jude Medical).
• Substantial variations in turbulent kinetic energy were detected between patients with aortic stenosis, implanted aortic valves, and healthy subjects.

Conclusions:

• The developed method enables efficient and accurate measurement of 3D blood flow dynamics, including turbulent kinetic energy.
• This technique offers a comprehensive hemodynamic assessment of heart valve performance in vivo.
• The findings highlight the potential of this approach for improved clinical diagnosis and device evaluation.