Authors
Hao Yu, Jue Zhang
Published in
Ultrasound in medicine & biology. Aug 19, 2026. Epub Aug 19, 2026.
Abstract
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.
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.
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.
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.
PMID:
42618383
Bibliographic data and abstract were imported from PubMed on 20 Aug 2026.
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