Abstract
Photoacoustic flowmetry (PAF) based on time-domain cross correlation of photoacoustic signals is a promising technique for deep tissue measurement of blood flow velocity. Signal processing has previously been developed for single element transducers. Here, the processing methods for acoustic resolution PAF using a clinical ultrasound transducer array are developed and validated using a 64-element transducer array with a -6 dB detection band of 11 to 17MHz. Measurements were performed on a flow phantom consisting of a tube (580 μm inner diameter) perfused with human blood flowing at physiological speeds ranging from 3 to 25 mm / s. The processing pipeline comprised: image reconstruction, filtering, displacement detection, and masking. High-pass filtering and background subtraction were found to be key preprocessing steps to enable accurate flow velocity estimates, which were calculated using a cross-correlation based method. In addition, the regions of interest in the calculated velocity maps were defined using a masking approach based on the amplitude of the cross-correlation functions. These developments enabled blood flow measurements using a transducer array, bringing PAF one step closer to clinical applicability.
Highlights
Many pathologies affect the perfusion of tissues, making knowledge about the blood flow speed a crucial diagnostic aid
Pulsed Doppler ultrasound (PD-US) is often used to image deep tissue blood flow; without exogenous contrast agents this modality is typically limited to relatively large vessels with diameters in the range of millimeters and larger
The beam diameter at the tube was ∼5 mm in diameter, which is large in comparison to the resolution of the reconstructed images, and imaging was performed in the acoustic resolution regime
Summary
Many pathologies affect the perfusion of tissues, making knowledge about the blood flow speed a crucial diagnostic aid. There have been a number of advances in applying the PA effect to the measurement of flow.[1] One approach is based on thermal tagging of flow using laser light[2,3,4] or high-intensity-focused ultrasound.[5,6] Other methods exploit the Doppler effect in which motion-induced time, phase, or frequency shifts in the PA signal are used to calculate velocity. This was initially implemented using continuous wave excitation with intensitymodulated light.[7] Analogous to Doppler ultrasound, the received signal contains a Doppler shift of the input modulation
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