Quantitative Ultrasound for Monitoring High-Intensity Focused Ultrasound Treatment In Vivo

2D ultrasound thermometry during thermal ablation with high-intensity focused ultrasound

The clinical use of high intensity focused ultrasound (HIFU) therapy for noninvasive tissue ablation has recently gained momentum. Guidance is provided by either magnetic resonance imaging (MRI) or conventional B-mode ultrasound imaging, each with its own advantages and disadvantages. The main limitation of ultrasound imaging is its inability to provide temperature measurements over the ranges corresponding to the target temperatures during ablative thermal therapies (between 55 °C and 70 °C). Here, variations in ultrasound backscattered energy (ΔBSE) were used to monitor temperature increases in liver tissue up to an absolute value of 90 °C during and after HIFU treatment. In vitro experimental measurements were performed in 47 bovine liver samples using a toroidal HIFU transducer operating at 2.5 MHz to increase the temperature of tissues. An ultrasound imaging probe working at 7.5 MHz was placed in the center of the HIFU transducer to monitor the backscattered signals. The free-field acoustic power was set to 9 W, 12 W or 16 W in the different experiments. HIFU sonications were performed for 240 s using a duty cycle of 83 % to allow ultrasound imaging and raw radiofrequency data acquisition during exposures. Measurements showed a linear relationship between ΔBSE (in dB) and temperature (r = 0.94, p < 0.001) over a temperature range from 37 °C to 90 °C, with a high reliability of temperature measurements below 75 °C. Monitoring can be performed at the frame rate of ultrasound imaging scanners with an accuracy within an acceptable threshold of 5 °C, given the temperatures targeted during thermal ablations. If the maximum temperature reached is below 70 °C, ΔBSE is also a reliable approach for estimating the temperature during cooling. Histological analysis shown the impact of the treatment on the spatial arrangement of cells that can explain the observed variation of ΔBSE. These results demonstrate the ability of ΔBSE measurements to estimate temperature in ultrasound images within an effective therapeutic range. This method can be implemented clinically and potentially applied to other thermal-based therapies.

In vivo exposure of the bladder using a non-invasive high intensity focused ultrasound toroidal transducer

A toroidal high-intensity focused ultrasound (HIFU) transducer was used to expose normal bladder wall tissues non-invasively in vivo in a porcine model in order to investigate the potential to treat bladder tumors. The transducer was divided into 32 concentric rings with equal surface areas, operating at 2.5 MHz. Eight animals were split into two groups of 4. In the first group, post-mortem evaluation was performed immediately after ultrasound exposure. In the second group, animals survived for up to seven days before post-mortem evaluation. The ultrasound imaging guided HIFU device was hand-held during the procedure using optical tracking to ensure correct targeting. One thermal lesion in each animal was created using a 40 s exposure at 80 acoustic Watts (free-field) in the trigone region of the bladder wall. The average (±Standard Deviation) abdominal wall and bladder wall thicknesses were 10.3 ± 1.4 mm and 1.1 ± 0.4 mm respectively. The longest and shortest axes of the HIFU ablations were 7.7 ± 2.9 mm and 6.0 ± 1.8 mm, respectively, resulting in an ablation of the whole thickness of the bladder wall in most cases. Ablation were performed at an average depth (distance from the skin surface to the centre of the HIFU lesion) of 42.5 ± 3.8 mm and extended throughout the thickness of the bladder. There were two cases of injury to tissues immediately adjacent to the bladder wall but without signs of perforation, as confirmed by histological analysis. Non-invasive HIFU ablation using a hand-held toroidal transducer was successfully performed to destroy regions of the bladder wall in vivo.

Quantitative ultrasound techniques for assessing thermal ablation: Measurement of the backscatter coefficient from ex vivo human liver

BACKGROUND

Understanding the changes occurring in biological tissue during thermal ablation is at the heart of many current challenges in both therapy and medical imaging research.

PURPOSE

The objective of this work is to quantitatively interpret the scattering response of human liver samples, before and after thermal ablation. We report acoustic measurements performed involving n = 21 human liver samples. Thermal ablation is achieved at temperatures between 45 and 80°C and quantification of the irreversible changes in acoustic attenuation and Backscattering Coefficient (BSC) is reported, with a particular attention to the latter.

METHODS

Both attenuation coefficient and BSCs were measured in the frequency range from 10 to 52 MHz. Scans were performed before heating and after cooling down. Attenuation coefficients were calculated using spectral difference method and BSC estimated using the reference phantom method.

RESULTS

Strong increases of attenuation coefficients and BSCs with heating temperature were observed. Quantitative ultrasonic parameters obtained with the polydisperse structure factor model (poly-SFM)are compared to histological observations and seen to be close to hepatocyte mean diameter (HMD).

CONCLUSIONS

The results presented in this study provide a description of the impact of thermal ablation in human liver tissue on acoustic attenuation and the BSC. For the first time, quantitative agreement between the Effective Scatterer Diameter (ESD) estimated from BSC and HMD was shown, highlighting the important role of cellular network in the scattering response of the medium. This core result is an important step toward the determination of the nature of scattering sources in biological tissues.

Ultrasound Homodyned-K Contrast-Weighted Summation Parametric Imaging Based on H-scan for Detecting Microwave Ablation Zones

The homodyned-K (HK) distribution is a generalized model of envelope statistics whose parameters α (the clustering parameter) and k (the coherent-to-diffuse signal ratio) can be used to monitor the thermal lesions. In this study, we proposed an ultrasound HK contrast-weighted summation (CWS) parametric imaging algorithm based on the H-scan technique and investigated the optimal window side length (WSL) of the HK parameters estimated by the XU estimator (an estimation method based on the first moment of the intensity and two log-moments, which was used in the proposed algorithm) through phantom simulations. H-scan diversified ultrasonic backscattered signals into low- and high-frequency passbands. After envelope detection and HK parameter estimation for each frequency band, the α and k parametric maps were obtained, respectively. According to the contrast between the target region and background, the (α or k) parametric maps of the dual-frequency band were weighted and summed, and then the CWS images were yielded by pseudo-color imaging. The proposed HK CWS parametric imaging algorithm was used to detect the microwave ablation coagulation zones of porcine liver ex vivo under different powers and treatment durations. The performance of the proposed algorithm was compared with that of the conventional HK parametric imaging and frequency diversity and compounding Nakagami imaging algorithms. For two-dimensional HK parametric imaging, it was found that a WSL equal to 4 pulse lengths of the transducer was sufficient for estimating the α and k parameters in terms of both parameter estimation stability and parametric imaging resolution. The HK CWS parametric imaging provided an improved contrast-to-noise ratio over conventional HK parametric imaging, and the HK α_cws parametric imaging achieved the best accuracy and Dice score of coagulation zone detection.

Implementation of Non-Invasive Quantitative Ultrasound in Clinical Cancer Imaging

Quantitative ultrasound (QUS) is a non-invasive novel technique that allows treatment response monitoring. Studies have shown that QUS backscatter variables strongly correlate with changes observed microscopically. Increases in cell death result in significant alterations in ultrasound backscatter parameters. In particular, the parameters related to scatterer size and scatterer concentration tend to increase in relation to cell death. The use of QUS in monitoring tumor response has been discussed in several preclinical and clinical studies. Most of the preclinical studies have utilized QUS for evaluating cell death response by differentiating between viable cells and dead cells. In addition, clinical studies have incorporated QUS mostly for tissue characterization, including classifying benign versus malignant breast lesions, as well as responder versus non-responder patients. In this review, we highlight some of the important findings of previous preclinical and clinical studies and expand the applicability and therapeutic benefits of QUS in clinical settings. We summarized some recent clinical research advances in ultrasound-based radiomics analysis for monitoring and predicting treatment response and characterizing benign and malignant breast lesions. We also discuss current challenges, limitations, and future prospects of QUS-radiomics.

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.

Ultrasound Entropy Imaging for Detection and Monitoring of Thermal Lesion During Microwave Ablation of Liver

Ultrasonic B-mode imaging offers non-invasive and real-time monitoring of thermal ablation treatment in clinical use, however it faces challenges of moderate lesion-normal contrast and detection accuracy. Quantitative ultrasound imaging techniques have been proposed as promising tools to evaluate the microstructure of ablated tissue. In this study, we introduced Shannon entropy, a non-model based statistical measurement of disorder, to quantitatively detect and monitor microwave-induced ablation in porcine livers. Performance of typical Shannon entropy (TSE), weighted Shannon entropy (WSE), and horizontally normalized Shannon entropy (hNSE) were explored and compared with conventional B-mode imaging. TSE estimated from non-normalized probability distribution histograms was found to have insufficient discernibility of different disorder of data. WSE that improves from TSE by adding signal amplitudes as weights obtained area under receiver operating characteristic (AUROC) curve of 0.895, whereas it underestimated the periphery of lesion region. hNSE provided superior ablated area prediction with the correlation coefficient of 0.90 against ground truth, AUROC of 0.868, and remarkable lesion-normal contrast with contrast-to-noise ratio of 5.86 which was significantly higher than other imaging methods. Data distributions shown in horizontally normalized probability distribution histograms indicated that the disorder of backscattered envelope signal from ablated region increased as treatment went on. These findings suggest that hNSE imaging could be a promising technique to assist ultrasound guided percutaneous thermal ablation.

Multiparametric Quantitative US Examination of Liver Fibrosis: A Feature-engineering and Machine-learning Based Analysis

Quantitative ultrasound (QUS), which is commonly used to extract quantitative features from the ultrasound radiofrequency (RF) data or the RF envelope signals for tissue characterization, is becoming a promising technique for noninvasive assessments of liver fibrosis. However, the number of feature variables examined and finally used in the existing QUS methods is typically small, to some extent limiting the diagnostic performance. Therefore, this paper devises a new multiparametric QUS (MP-QUS) method which enables the extraction of a large number of feature variables from US RF signals and allows for the use of feature-engineering and machinelearning based algorithms for liver fibrosis assessment. In the MP-QUS, eighty-four feature variables were extracted from multiple QUS parametric maps derived from the RF signals and the envelope data. Afterwards, feature reduction and selection were performed in turn to remove the feature redundancy and identify the best combination of features in the reduced feature set. Finally, a variety of machine-learning algorithms were tested for classifying liver fibrosis with the selected features, based on the results of which the optimal classifier was established and used for final classification. The performance of the proposed MPQUS method for staging liver fibrosis was evaluated on an animal model, with histologic examination as the reference standard. The mean accuracy, sensitivity, specificity and area under the receiver-operating-characteristic curve achieved by MP-QUS are respectively 83.38%, 86.04%, 80.82% and 0.891 for recognizing significant liver fibrosis, and 85.50%, 88.92%, 85.24% and 0.924 for diagnosing liver cirrhosis. The proposed MP-QUS method paves a way for its future extension to assess liver fibrosis in human subjects.

Imaging of Thermal Effects during High-Intensity Ultrasound Treatment in Liver by Passive Elastography: A Preliminary Feasibility in Vitro Study

High-intensity focused ultrasound is a non-invasive modality for thermal ablation of tissues through locally increased temperature. Thermal lesions can be monitored by elastography, following the changes in the elastic properties of the tissue as reflected by the shear-wave velocity. Most studies on ultrasound elastography use shear waves created by acoustic radiation force. However, in the human body, the natural noise resulting from cardiac activity or arterial pulsatility can be used to characterize elasticity through noise-correlation techniques, in the method known as passive elastography. The objective of this study was to investigate the feasibility of monitoring high-intensity ultrasound treatments of liver tissue using passive elastography. Bovine livers were heated to 80°C using a high-intensity planar transducer and imaged with a high-frame-rate ultrasound imaging device. The dynamics of lesion formation are captured through tissue stiffening and lesion expansion.