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Quantification of flow using ultrasound and microbubbles: a disruption replenishment model based on physical
John M Hudson1, Raffi Karshafian, Peter N Burns
1Department of Medical Biophysics, University of Toronto, Toronto, Canada; and Sunnybrook Health Sciences Centre, Toronto, Canada. hudsonjm@gmail.com
Ultrasound in Medicine & Biology
|October 14, 2009
Summary
A new analytic model improves contrast-enhanced ultrasound (CEUS) quantification of microcirculation blood flow. This model accounts for physical principles, enhancing accuracy over traditional methods for better clinical applications.
Area of Science:
- Ultrasound physics
- Biomedical imaging
- Hemodynamics
Background:
- Contrast-enhanced ultrasound (CEUS) quantifies microcirculation flow and vascular volume noninvasively.
- Current quantification relies on time-intensity curves analyzed with simplified mathematical functions (e.g., mono-exponential).
- Traditional methods neglect underlying physics and measurement device influences, limiting accuracy.
Purpose of the Study:
- To introduce a general analytic disruption replenishment model for CEUS quantification.
- To account for hemodynamic properties, ultrasound field distribution, and microbubble behavior.
- To compare the proposed model's performance against the established mono-exponential model.
Main Methods:
- Developed a general analytic disruption replenishment model incorporating hemodynamic properties (velocity, vascular cross-section).
- Included elevation and axial plane pressure distributions and mechanical index (MI) disruption/detection boundaries.
- Evaluated model performance in a flow phantom, assessing robustness to motion artifacts and accuracy of velocity estimation.
Main Results:
- The proposed model demonstrated improved robustness against simulated motion artifacts compared to the mono-exponential model.
- Velocity estimation accuracy was significantly better with the new model (3-10% error) versus the traditional model (90% error).
- Accurate velocity quantification requires accounting for the ultrasound beam profile, with errors up to 56% if depth-dependent thickness is ignored.
Conclusions:
- The general analytic disruption replenishment model offers a more physically grounded approach to CEUS quantification.
- This advanced model improves accuracy and robustness, particularly in the presence of motion artifacts.
- The findings highlight the importance of incorporating detailed physical parameters for precise microvascular flow assessment using CEUS.
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