Ultrasound single-phase CBE imaging for monitoring radiofrequency ablation

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.

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.

Detection of microwave ablation coagulation areas using ultrasound Nakagami imaging based on Gaussian pyramid decomposition: A feasibility study

In this paper, we explored the feasibility of using ultrasound Nakagami-m parametric imaging based on Gaussian pyramid decomposition (GPD) to detect microwave ablation coagulation areas. Monte Carlo simulation and phantom simulation results demonstrated that a 2-layer GPD model was sufficient to achieve the same m parameter estimation accuracy, smoothness and resolution as 3-layer and 4-layer. The performances of GPD, moment-based estimator (MBE) and window-modulated compounding (WMC) algorithms were compared in terms of parameter estimation, smoothness, resolution and contrast-to-noise (CNR). Results showed that the m parameter estimation obtained by GPD algorithm was better than that of MBE and WMC algorithms except the small window size (27 × 5). When using a window size of >3 pulse lengths, GPD algorithm could achieve better smoothness and CNR than MBE and WMC algorithms, but there was a certain loss of axial resolution. The computation time of GPD algorithm was less than that of WMC algorithm, while about 2.24 times that of MBE algorithm. Experimental results of porcine liver microwave ablation ex vivo (n = 20) illustrated that the average areas under the operating characteristic curve (AUCs) of Nakagami m_GPD, m_MBE and m_WMC parametric imaging and homodyned-K (HK) α and k parametric imaging to detect coagulation areas were significantly improved by polynomial approximation (PAX). Kruskal-Wallis test showed that the accuracy of coagulation area detection obtained by PAX imaging of m_GPD parameter had no significant difference with that of m_MBE, m_WMC, HK_α and HK_k parameters. This preliminary study suggested that Nakagami imaging based on GPD algorithm may have the potential to detect microwave ablation coagulation areas.

Ultrasound single-phase CBE imaging for monitoring radiofrequency ablation of the liver tumor: A preliminary clinical validation

Radiofrequency ablation (RFA) is an alternative treatment for early-stage hepatocellular carcinoma (HCC). The production of gas bubbles by RFA indicates threshold temperature of tissue necrosis and results in changes in backscattered energy (CBE) when ultrasound monitors RFA. In this study, ultrasound single-phase CBE imaging was used as a means of monitoring RFA of the liver tumor by analyzing the backscattering of ultrasound from gas bubbles in the liver. A total of 19 HCC patients were enrolled in the study. An ultrasound system was used during RFA to monitor the ablation process and acquire raw image data consisting of backscattered signals for single-phase CBE imaging. On the basis of single-phase CBE imaging, the area corresponding to the range of gas bubbles was compared with the tumor sizes and ablation zones estimated from computed tomography. During RFA, ultrasound single-phase CBE imaging enabled improved visualization of gas bubbles. Measured gas bubble areas by CBE were related to tumor size (the Spearman correlation coefficient r_s = 0.86; p < 0.05); less dependent on the ablation zone. Approximately 95% of the data fell within the limits of agreement in Bland-Altman plots, and 58% of the data fell within the 95% CI. This study suggests that single-phase CBE imaging provides information about liver tumor size because of the abundant vessels in liver tumors that promote the generation of gas bubbles, which serve as natural contrast agents in RFAs to enhance ultrasound backscattering. Ultrasound single-phase CBE imaging may allow clinicians to determine if the required minimum RFA efficacy level is reached by assessing gas bubbles in the liver tumors.

Radiofrequency Ablation for Liver: Comparison between Expert Eye and Hyperspectral Imaging Assessment

Liver/hepatic cancer (HC) is a disease that roughly afflicts 10% of cancer patients worldwide. HC is in charge of the death of 0.8 million patients on the earth. Multiple approaches, including thermal ablation, target the treatment of HC. In this study, we investigated radiofrequency (RF) ablation. Expert clinicians' visual assessment (VA) dominantly evaluated the outcome of ablation. Inattentively, the disfavors of VA are being subjective and eye-acuity dependent. In support, we propose hyperspectral imaging (HSI) for objective assessment of liver ablation. To verify our proposal, we computed the ablated liver area using VA and HSI. Unfortunately, HSI is a time-intensive technique. To make it less intensive, we present a way of reducing data analysis time. Saving time permits medical decisions, likewise continue or stop RF ablation, to be taken safer and faster. The way to reduce the time for HSI data analysis depends on narrowing the spectral bands of interest to only the most relevant ones to liver chromophores. Liver chromophores change in concentration because of thermal ablation. VA hardly senses these changes, however, HSI does it. Ultimately, the spectral band centered at 630 nm is optimal for objectively support RF ablation decision-makers.

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.

Deep heat therapy system with resonant cavity applicator for articular cartilage in knee osteoarthritis

[Purpose] Heat can prevent cartilage degeneration when applied to articular cartilage, but the size of the human knee joint makes it difficult to target cartilage during heat treatment. In this study, we aimed to establish a heat therapy method capable of safely applying heat to deep intra-articular tissues utilizing a resonant cavity applicator and to confirm the extent of cartilage heating in the human knee when using this system. [Participants and Methods] Heating experiments were carried out on the knees of healthy three volunteers using a resonant cavity applicator and a microwave diathermy system. After heat application, temperature distributions inside the knee were measured noninvasively using our measurement method based on ultrasound imaging techniques. [Results] We observed an increase in the temperature around the cartilage tissue in the knees of the volunteers using an ultrasonic thermometer; there was no increase in temperature in the overlying layers. During heating with up to 20 W of power, none of the volunteers experienced adverse reactions. [Conclusion] This study indicates the potential safety and effectiveness of the resonant cavity heat therapy system for knee osteoarthritis in a clinical setting.

Frequency-domain CBE imaging for ultrasound localization of the HIFU focal spot: a feasibility study

High-intensity focused ultrasound (HIFU) is a well-accepted tool for noninvasive thermal therapy. To control the quality of HIFU treatment, the focal spot generated in tissues must be localized. Ultrasound imaging can monitor heated regions; in particular, the change in backscattered energy (CBE) allows parametric imaging to visualize thermal information in the tissue. Conventional CBE imaging constructed in the spatial domain may be easily affected by noises when the HIFU focal spot is visualized. This study proposes frequency-domain CBE imaging to improve noise tolerance and image contrast in HIFU focal spot monitoring. Phantom experiments were performed in a temperature-controlled environment. HIFU of 2.12 MHz was applied to the phantoms, during which a clinical scanner equipped with a 3-MHz convex array transducer was used to collect raw image data consisting of backscattered signals for B-mode, spatial-, and frequency-domain CBE imaging. Concurrently, temperature changes were measured at the focal spot using a thermocouple for comparison with CBE values by calculating the correlation coefficient r. To further analyze CBE image contrast levels, a contrast factor was introduced, and an independent t-test was performed to calculate the probability value p. Experimental results showed that frequency-domain CBE imaging performed well in thermal distribution visualization, enabling quantitative detection of temperature changes. The CBE value calculated in the frequency domain also correlated strongly with that obtained using the conventional spatial-domain approach (r = 0.97). In particular, compared with the image obtained through the conventional method, the contrast of the CBE image obtained using the method based on frequency-domain analysis increased by 2.5-fold (4 dB; p < 0.05). Frequency-domain computations may constitute a new strategy when ultrasound CBE imaging is used to localize the focal spot in HIFU treatment planning.

Real-Time Radiofrequency Ablation Lesion Depth Estimation Using Multi-frequency Impedance With a Deep Neural Network and Tree-Based Ensembles

OBJECTIVE

Design and optimization of statistical models for use in methods for estimating radiofrequency ablation (RFA) lesion depths in soft real-time performance.

METHODS

Using tissue multi-frequency complex electrical impedance data collected from a low-cost embedded system, a deep neural network (NN) and tree-based ensembles (TEs) were trained for estimating the RFA lesion depth via regression.

RESULTS

Addition of frequency sweep data, previous depth data, and previous RF power state data boosted accuracy of the statistical models. The root mean square errors were 2 mm for NN and 0.5 mm for TEs for previous statistical models and the root mean square errors were 0.4 mm for NN and 0.04 mm for TEs for the statistical models presented in this paper. Simulation ablation performance showed a mean difference against physical measurements of 0.5 ±0.2 mm for the NN-based depth estimation method and 0.7 ±0.4 mm for the TE-based depth estimation method.

CONCLUSION

The results show that multi-frequency data significantly improves the depth estimation performance of the statistical models.

SIGNIFICANCE

The RFA lesion depth estimation methods presented in this work achieve millimeter-resolution accuracy with soft real-time performance on an ARMv7-based embedded system for potential translation to clinical RFA technologies.