High-contrast active cavitation imaging technique based on multiple bubble wavelet transform

Numerical and experimental investigation of impacts of nonlinear scattering encapsulated microbubbles on Nakagami distribution

PURPOSE

The Nakagami statistical model and Nakagami shape parameter m have been widely used in linear tissue characterization and preliminarily characterized the envelope distributions of nonlinear encapsulated microbubbles (EMBs). However, the Nakagami distribution of nonlinear scattering EMBs lacked a systematical investigation. Thus, this study aimed to investigate the Nakagami distribution of EMBs and illustrate the impact of EMBs' nonlinearity on the Nakagami model.

METHOD

A group of simulated EMB phantoms and in vitro EMB dilutions with an increasing concentration distribution under various EMB nonlinearities, as regulated by acoustic parameters, were characterized by using the window-modulated compounding Greenwood-Durand estimator.

RESULTS

Raw envelope histograms of simulated and in vitro EMBs were well matched with the Nakagami distribution with a high correlation coefficient of 0.965 ± 0.021 (P < 0.005). The mean values and gradients of m parameters of simulated and in vitro EMBs were smaller than those of linear scatterers due to the stronger nonlinearity. These m values exhibited a quasi-linear improvement with the increase in second harmonic nonlinear-to-linear component ratio regulated by pulse lengths and excitation frequencies at low- and high-concentration conditions.

CONCLUSIONS

The Nakagami distribution was suitable for the EMBs characterization but the corresponding m parameter was affected by the EMBs' nonlinearity. These validations provided support and nonlinear impact assessment for the EMBs' characterization using the Nakagami statistical model in the future.

Bubble-echo based deconvolution of contrast-enhanced ultrasound imaging: Simulation and experimental validations

PURPOSE

Improvement of both the imaging resolution and the contrast-to-tissue ratio (CTR) is a current emphasis of contrast-enhanced ultrasound (CEUS) for microvascular perfusion imaging. Based on the strong nonlinear characteristics of contrast agents, the CTRs have been significantly enhanced using various advanced CEUS methods. However, the imaging resolution of these methods is limited by the finite bandwidth of the imaging process. This study aimed to propose a bubble-echo based deconvolution (BED) method for CEUS with both improved resolution and CTR.

METHOD

The method is built on a modified convolution model and uses novel bubble-echo based point-spread-functions to reconstruct the images by regularized inverse Wiener filtering. Performances of the proposed BED for three CEUS modes are investigated through simulations and in vivo perfusion experiments.

RESULTS

BED of fundamental imaging was found to have the highest improvement in imaging resolution with the resolution gain up to 2.0 ± 0.2 times, which was comparable to the approved cepstrum-based deconvolution (CED). BED of second-harmonic imaging had the best performance in CTR with an enhancement of 9.8 ± 2.3 dB, which was much higher than CED. Pulse inversion BED had both a better resolution and a higher CTR.

CONCLUSION

All results indicate that BED could obtain CEUS image with both an improved resolution and a high CTR, which has important significance to microvascular perfusion evaluation in deep tissue.

DCEUS-based multiparametric perfusion imaging using pulse-inversion Bubblet decorrelation

PURPOSE

This study aimed to clarify the influences of composite dynamic contrast-enhanced ultrasound (DCEUS) on multiparametric perfusion imaging (PPI) and to develop a novel PPI scheme through pulse-inversion Bubblet decorrelation (PIBD) to improve its contrast and detailed discriminability.

METHOD

In in vivo perfusion experiments on rabbit kidneys, a pair of phase-inverted "Bubblets" was constructed. Phase-inverted raw radiofrequency echoes were reconstructed by using the maximum coefficients obtained from Bubblet decorrelation analysis and summed to form DCEUS loops. Nine perfusion parameters were estimated from these loops and color coded to create the corresponding PIBD-based PPIs.

RESULTS

In addition to time-related PPIs, the contrast and detailed discriminability quantified by the average contrast and information entropy of intensity- and ratio-related PPIs were proportional to the microbubble detection sensitivity and microvascular discriminability evaluated by CTR in DCEUS techniques. Compared with the second harmonic, the CTR of DCEUS and the average contrast and information entropy of PPI were significantly improved by 9.03 ± 5.39 dB (P < 0.01), 6.39 ± 1.38 dB (P < 0.01), and 0.57 ± 0.15 (P < 0.05) in PIBD technique, respectively.

CONCLUSIONS

As a multiparametric functional imaging technique, these improvements in the proposed scheme can be beneficial to accurately quantify and depict the hemodynamic perfusion features and details of tumor angiogenesis, and further can also assist clinicians in making a confirmed diagnosis.