Delay multiply and sum beamforming method applied to enhance linear‐array passive acoustic mapping of ultrasound cavitation. Issue 10 (10th August 2019)

• Record Type: Journal Article
• Authors: Lu, Shukuan; Li, Renyan; Yu, Xianbo; Wang, Diya; Wan, Mingxi
• Is Part Of: Medical physics. Volume 46:Issue 10(2019)
• Page Start: 4441
• Page End: 4454
• Publication Date: 2019-08-10
• Subjects: delay multiply sum and integrate -- passive acoustic mapping -- point spread function -- signal‐to‐noise ratio -- ultrasound cavitation; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.13714
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: Passive acoustic mapping (PAM) has been proposed as a means of monitoring ultrasound therapy, particularly nonthermal cavitation‐mediated applications. In PAM, the most common beamforming algorithm is a delay, sum, and integrate (DSAI) approach. However, using DSAI leads to low‐quality images for the case where a narrow‐aperture receiving array such as a standard B‐mode linear array is used. This study aims to propose an enhanced linear‐array PAM algorithm based on delay, multiply, sum, and integrate (DMSAI). Methods: In the proposed algorithm, before summation, the delayed signals are combinatorially coupled and multiplied, which means that the beamformed output of the proposed algorithm is the spatial coherence of received acoustic emissions. We tested the performance of the proposed DMSAI using both simulated and experimental data and compared it with DSAI. The reconstructed cavitation images were evaluated quantitatively by using source location errors between the two algorithms, full width at half maximum (FWHM), size of point spread function (A50 area), signal‐to‐noise ratio (SNR), and computational time. Results: The results of simulations and experiments for single cavitation source show that, by introducing DMSAI, the FWHM and the A50 area are reduced and the SNR is improved compared with those obtained by DSAI. The simulation results for two symmetric or nonsymmetric cavitation sources and multiple cavitation sources show that DMSAI can significantly reduce the A50 area and improve the SNR, therefore improving the detectability of multiple cavitation sources. Conclusions: The results indicate that the proposed DMSAI algorithm outperforms the conventionally used DSAI algorithm. This work may have the potential of providing an appropriate method for ultrasound therapy monitoring.