Nakagami-m parametric imaging for characterization of thermal coagulation and cavitation erosion induced by HIFU

Ultrasonic Nakagami imaging for automatically positioning and identifying the treated lesion induced by histotripsy

Histotripsy has been proposed as a non-invasive surgical procedure for clinical use that liquefies the tissue into acellular debris by utilizing the mechanical mechanism of bubbles. Accurate and reliable imaging guidance is essential for successful clinical histotripsy implementation. Nakagami imaging is a promising method to evaluate the microstructural change induced by high intensity focused ultrasound. However, practically, it is difficult for the Nakagami imaging to distinguish the treated lesion induced by histotripsy from the surrounding normal biological tissues. In this study, we introduce the use of noise-assisted correlation algorithm (NCA) in Nakagami images as a solution to suppress the background normal tissue and identify the treated lesion induced by histotripsy. Experiments are conducted on fresh porcine liver ex vivo by cavitation-cloud histotripsy. Results show that the contrast-to-noise ratio between the treated lesion and surrounding tissue corresponding to the Nakagami image after NCA and original Nakagami image is 3.434 and 0.505, respectively. The optimal artificial noise level is 1-fold of the background normal tissue amplitude, and the corresponding optimal threshold of correlation coefficient should be between 0.6 and 0.8 in the application of NCA. Therefore, the use of NCA in Nakagami image can suppress the background normal tissues without affecting the information of treated lesion for an appropriate artificial noise level and threshold used in the NCA. Moreover, the Nakagami images after the application of the NCA can also be used for automatically distinguishing and measuring the tissue fractionation accurately using binarization. The proposed Nakagami images overlaid on the B-mode images can provide a promising method for positioning and visualizing the treated lesion to achieve precise histotripsy treatment.

A Review of Quantitative Ultrasound-Based Approaches to Thermometry and Ablation Zone Identification Over the Past Decade

Percutaneous thermal therapy is an important clinical treatment method for some solid tumors. It is critical to use effective image visualization techniques to monitor the therapy process in real time because precise control of the therapeutic zone directly affects the prognosis of tumor treatment. Ultrasound is used in thermal therapy monitoring because of its real-time, non-invasive, non-ionizing radiation, and low-cost characteristics. This paper presents a review of nine quantitative ultrasound-based methods for thermal therapy monitoring and their advances over the last decade since 2011. These methods were analyzed and compared with respect to two applications: ultrasonic thermometry and ablation zone identification. The advantages and limitations of these methods were compared and discussed, and future developments were suggested.

High contrast ultrasonic method with multi-spatiotemporal compounding for monitoring catheter-based ultrasound thermal therapy: Development and Ex Vivo Evaluations

OBJECTIVE

Changes in ultrasound backscatter energy (CBE) imaging can monitor thermal therapy. Catheter-based ultrasound (CBUS) can treat deep tumors with precise spatial control of energy deposition and ablation zones, of which CBE estimation can be limited by low contrast and robustness due to small or inconsistent changes in ultrasound data. This study develops a multi-spatiotemporal compounding CBE (MST-CBE) imaging approach for monitoring specific to CBUS thermal therapy.

METHODS

Ex vivo thermal ablations were performed with stereotactic positioning of a 180 directional CBUS applicator, temperature monitoring probes, endorectal US probe, and subsequent lesion sectioning and measurement. Five frames of raw radiofrequency data were acquired throughout in 15s intervals. Using window-by-window estimation methods, absolute and positive components of MST-CBE images at each point were obtained by the compounding ratio of squared envelope data within an increasing spatial size in each short-time window.

RESULTS

Compared with conventional US, Nakagami, and CBE imaging, the detection contrast and robustness quantified by tissue-modification-ratio improved by 37.24.7 (p<0.001), 37.55.2 (p<0.001), and 6.44.0 dB (p<0.05) in the MST-CBE imaging, respectively. Correlation coefficient and bias between cross-sectional dimensions of the ablation zones measured in tissue sections and estimated from MST-CBE were up to 0.91 (p<0.001) and -0.02 mm2, respectively.

CONCLUSION

The MST-CBE approach can monitor the detailed changes within target tissues and effectively characterize the dimensions of the ablation zone during CBUS energy deposition.

SIGNIFICANCE

The MST-CBE approach could be practical for improved accuracy and contrast of monitoring and evaluation for CBUS thermal therapy.

Monitoring microwave ablation using ultrasound homodyned K imaging based on the noise-assisted correlation algorithm: An ex vivo study

In this paper, we proposed ultrasound homodyned K (HK) imaging based on the noise-assisted correlation algorithm (NCA) for monitoring microwave ablation of porcine liver ex vivo. The NCA-based HK (α_NCA and k_NCA) imaging was compared with NCA-based Nakagami (m_NCA) imaging and NCA-based cumulative echo decorrelation (CED_NCA) imaging. Backscattered ultrasound radiofrequency signals of porcine liver ex vivo during and after the heating of microwave ablation were collected (n = 15), which were processed for constructing B-mode imaging, NCA-based HK imaging, NCA-based Nakagami imaging, and NCA-based CED imaging. To quantitatively evaluate the final coagulation zone, the polynomial approximation (PAX) technique was applied. The accuracy of detecting coagulation area with α_NCA, k_NCA, m_NCA, and CED_NCA parametric imaging was evaluated by comparing the PAX imaging with the gross pathology. The receiver operating characteristic (ROC) curve was used to further evaluate the performance of the three quantitative ultrasound imaging methods for detecting the coagulation zone. Experimental results showed that the average accuracies of α_NCA, k_NCA, m_NCA, and CED_NCA parametric imaging combined with PAX imaging were 89.6%, 83.25%, 89.23%, and 91.6%, respectively. The average areas under the ROC curve (AUROCs) of α_NCA, k_NCA, m_NCA, and CED_NCA parametric imaging were 0.83, 0.77, 0.83, and 0.86, respectively. The proposed NCA-based HK imaging may be used as a new method for monitoring microwave ablation.

Nakagami imaging with related distributions for advanced thermogram pseudocolorization

Pseudocoloring algorithms embedded in the software of thermal cameras gradually colorize original intensity thermograms generated by detecting temperatures and contrast. Maximum and minimum based algorithms, however, executed by thresholding, applied to intensity thermograms for revealing and coloring the outliers instead. Although the common pseudocoloring protocols employed for general purposes may provide crucial information on the superficial contrast between radiation emitted by various sources; their common kernel is not sufficient for detecting and differentiating high radiated regions from surrounding areas, which is mandatory for recognition of abnormalities. Therefore, we propose novel imaging methodology based on Nakagami and related distributions, including gamma, Rayleigh, Weibull, chi-square and exponential, for enhancing thermal images and also for creating adequate discrimination. We initially define the boundaries of tumor and surrounding area in a synthetically generated breast thermogram already diagnosed as retroareolar tumor. Using Nakagami and transformations supported by mathematical foundations, we conducted several experiments to find the discrimination factor of the pseudocoloring techniques by calculating difference of average contrast between the tumor and the surrounding area. The performance is greatly encouraging that we achieved considerably better discrimination factor, designated for this study, up to 106.80 compared to the results of existing built-in pseudocolorization methods computed as 11.56.

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.

Delay multiply and sum beamforming method applied to enhance linear-array passive acoustic mapping of ultrasound cavitation

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.