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Proceedings Paper

Understanding quantification of microvascularity with high-frequency power Doppler ultrasound
Author(s): Stephen Z. Pinter; James C. Lacefield
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Paper Abstract

High-frequency power Doppler imaging of angiogenesis can be challenging given the presence of small blood vessels and slow flow velocities. In the presence of substantial Doppler artifacts such as false-positive color pixels or undetected vessels, color pixel density (CPD) and related vascularity metrics do not provide accurate estimates of vascular volume fraction. As a step towards improved microvascular quantification, flow-phantom experiments were performed to establish relationships between CPD and wall filter cut-off velocity for various combinations of vessel size (160, 200, 250, 300, and 360 μm), flow velocity (4, 3, 2, 1, and 0.5 mm/s), and transducer frequency (30 and 40 MHz). Three distinct regions were observed in plots of CPD versus wall filter cut-off velocity: overestimation of CPD at low cut-offs, underestimation of CPD at high cut-offs, and a plateau at intermediate cut-offs. The CPD at the plateau closely matched the phantom's actual vascular volume fraction. The length of the plateau corresponded with the flow-detection performance of the Doppler system, which was assessed using receiver operating characteristic analysis. Color pixel density versus wall filter cut-off curves from analogous in vivo experiments exhibited the same shape, including a distinct CPD plateau. The similar shape of the flow-phantom and in vivo curves suggests that the presence of a plateau can be used to identify the best-estimate CPD value in an in vivo experiment. The ability to identify the best CPD estimate is expected to improve quantification of angiogenesis and anti-angiogenic treatment responses with power Doppler.

Paper Details

Date Published: 14 March 2009
PDF: 9 pages
Proc. SPIE 7265, Medical Imaging 2009: Ultrasonic Imaging and Signal Processing, 72650U (14 March 2009); doi: 10.1117/12.811177
Show Author Affiliations
Stephen Z. Pinter, The Univ. of Western Ontario (Canada)
Robarts Research Institute, The Univ. of Western Ontario (Canada)
James C. Lacefield, The Univ. of Western Ontario (Canada)
Robarts Research Institute, The Univ. of Western Ontario (Canada)


Published in SPIE Proceedings Vol. 7265:
Medical Imaging 2009: Ultrasonic Imaging and Signal Processing
Stephen A. McAleavey; Jan D'hooge, Editor(s)

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