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Generalized mathematical framework for contrast-enhanced ultrasound imaging with pulse inversion spectral deconvolution.

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A generalized mathematical framework for performing contrast-enhanced ultrasound (CEUS) imaging is introduced. Termed pulse inversion spectral deconvolution (PISD), this CEUS approach is founded on Gaussian derivative functions (GDFs). PISD pulses… Click to show full abstract

A generalized mathematical framework for performing contrast-enhanced ultrasound (CEUS) imaging is introduced. Termed pulse inversion spectral deconvolution (PISD), this CEUS approach is founded on Gaussian derivative functions (GDFs). PISD pulses are used to form two inverted pulse sequences, which are then used to filter backscattered ultrasound (US) data for isolation of the nonlinear (NL) microbubble (MB) signal component. An US scanner equipped with a linear array transducer was used for data acquisition. With a vascular flow phantom perfused with MBs, data was collected using PISD and NL-based CEUS imaging. The role of wide-beam transmit aperture size (32 or 64 elements) was also evaluated using an US pulse frequency of 6.25 MHz. Image enhancement was quantified by a contrast-to-noise ratio (CNR). Preliminary in vivo data was collected in the hindlimb and kidney of healthy rats. Overall, in vitro wide-beam CEUS imaging using an aperture size of 64 elements yielded improved CNR values. Specifically, PISD-based CEUS imaging produced CNR values of 37.3 dB. For comparison, CNR values obtained using B-mode US or NL approaches were 2.1 and 12.1 dB, respectively. In vivo results demonstrated that PISD-based CEUS imaging improved vascular visualization compared to the NL imaging strategy.

Keywords: generalized mathematical; ceus imaging; ceus; contrast enhanced; mathematical framework

Journal Title: Ultrasonics
Year Published: 2022

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