Non-invasive Coronary Microvascular Flow Velocity Measurement via Multi-cycle Phase Clustering Color Doppler Flow
Insights
A new ultrafast ultrasound method, clustering color Doppler flow imaging (cCDFI), accurately measures coronary microvascular flow velocity. This non-invasive technique aids in diagnosing coronary microvascular dysfunction early.
Area of Science:
- Cardiovascular Imaging
- Ultrasound Technology
- Hemodynamics
Background:
- Coronary microvascular dysfunction (CMD) is underdiagnosed, impacting ischemia with no obstructive coronary arteries.
- Accurate assessment of coronary microvascular flow velocity is vital for early CMD intervention.
- Current clinical practice lacks effective non-invasive imaging for coronary microvascular flow velocity.
Purpose of the Study:
- To develop and validate a novel ultrafast ultrasound-based method for measuring in vivo coronary microvascular flow velocity.
- To address the limitations of existing techniques in assessing coronary microvascular function.
- To enable full cardiac cycle assessment of coronary microvascular flow velocity.
Main Methods:
- Utilized ultrafast ultrasound-based clustering color Doppler flow imaging (cCDFI).
- Employed a multi-cycle phase clustering strategy with B-mode motion information.
- Applied clutter filtering, auto-correlation, and an effective mask for high flow sensitivity.
Main Results:
- cCDFI demonstrated high consistency with tracking-based velocity benchmarks in vivo.
- Successfully captured velocity fluctuations aligned with phasic coronary hemodynamic characteristics.
- Confirmed the capability of contrast-free cCDFI for full cardiac cycle imaging.
Conclusions:
- The proposed cCDFI method offers a high-precision tool for in vivo coronary microvascular flow velocity research.
- cCDFI shows significant potential for early diagnosis and intervention of CMD.
- The technique is non-invasive, safe, and accessible for clinical applications.
Objective:
Coronary microvascular dysfunction is an underlying mechanism of ischemia with no obstructive coronary arteries, yet it remains severely under-diagnosed. Accurate assessment of coronary microvascular flow velocity is crucial for early intervention, but clinical practice currently lacks an effective, non-invasive imaging technique. To address this issue, this study proposes a novel ultrafast ultrasound-based clustering color Doppler flow imaging (cCDFI) method designed to measure in vivo coronary microvascular flow velocity throughout the full cardiac cycle amid vigorous cardiac motion.
Methods:
cCDFI utilizes a multi-cycle phase clustering strategy via the motion information inherent in B-mode, and performs clutter filtering and auto-correlation on frames of the same phase across multiple cycles. Subsequently, by employing an effective mask, cCDFI achieves high blood flow sensitivity in coronary microvascular flow velocity measurements.
Results:
In vivo experiments demonstrated that cCDFI velocity estimations were highly consistent with tracking-based velocity measurement benchmarks, with the velocity fluctuations that align with phasic coronary hemodynamic characteristics successfully captured. Additionally, this study confirms the capability of contrast-free cCDFI imaging throughout the full cardiac cycle.
Conclusion:
The proposed cCDFI method provides a high-precision digital quantification tool for in vivo coronary microvascular flow velocity research, demonstrating significant potential for the early diagnosis and therapeutic intervention of coronary microvascular dysfunction due to its non-invasive, safe and accessible nature.
