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Understanding the Influence of Flow Velocity, Wall Motion Filter, Pulse Repetition Frequency, and Aliasing on Power Doppler Image Quantification
Ist Teil von
Journal of ultrasound in medicine, 2018-01, Vol.37 (1), p.255-261
Ort / Verlag
England
Erscheinungsjahr
2018
Quelle
Wiley Online Library - AutoHoldings Journals
Beschreibungen/Notizen
Objectives
Although power Doppler imaging has been used to quantify tissue and organ vascularity, many studies showed that limitations in defining adequate ultrasound machine settings and attenuation make such measurements complex to be achieved. However, most of these studies were conducted by using the output of proprietary software, such as Virtual Organ computer‐aided analysis (GE Healthcare, Kretz, Zipf, Austria); therefore, many conclusions may not be generalizable because of unknown settings and parameters used by the software. To overcome this limitation, our goal was to evaluate the impact of the flow velocity, pulse repetition frequency (PRF), and wall motion filter (WMF) on power Doppler image quantification using beam‐formed ultrasonic radiofrequency data.
Methods
The setup consisted of a blood‐mimicking fluid flowing through a phantom. Radiofrequency signals were collected using PRFs ranging from 0.6 to 10 kHz for 6 different flow velocities (5–40 cm/s). Wall motion filter cutoff frequencies were varied between 50 and 250 Hz.
Results
The power Doppler magnitude was deeply influenced by the WMF cutoff frequency. The effect of using different WMF values varied with the PRF; therefore, the power Doppler signal intensity was dependent on the PRF. Finally, we verified that power Doppler quantification can be affected by the aliasing effect, especially when using a PRF lower than 1.3 kHz.
Conclusions
The WMF and PRF greatly influenced power Doppler quantification, mainly when flow velocities lower than 20 cm/s were used. Although the experiments were conducted in a nonclinical environment, the evaluated parameters are equivalent to those used in clinical practice, which makes them valuable for aiding the interpretation of related data in future research.