Evaluation of Microwave Ablation Efficacy by Strain Elastography and Shear Wave Elastography in ex Vivo Porcine Liver

Experimental study on monitoring microwave ablation efficacy by real-time shear wave elastography in ex vivo porcine brain

Objective: Glioma constitutes the most common primary malignant tumor in the central nervous system. In recent years, microwave ablation (MWA) was expected to be applied in the minimally invasive treatment of brain tumors. This study aims to evaluate the feasibility and accuracy of microwave ablation in ex vivo brain tissue by Shear Wave Elastography (SWE) to explore the application value of real-time SWE in monitoring the process of MWA of brain tissue.Methods: Thirty ex vivo brain tissues were treated with different microwave power and ablation duration. The morphologic and microscopic changes of MWA tissues were observed, and the diameter of the ablation areas was measured. In this experiment, SWE is used to quantitatively evaluate brain tissue's degree of thermal injury immediately after ablation.Results: This study It is found that the ablation range measured by SWE after ablation is in good consistency with the pathological range [ICCSWEL1-L1 = 0.975(95% CI:0.959 - 0.985), ICCSWEL2-L2 = 0.887(95% CI:0.779 - 0.938)]. At the same time, the SWE value after ablation is significantly higher than before (mean ± SD,9.88 ± 2.64 kPa vs.23.6 ± 13.75 kPa; p < 0.001). In this study, the SWE value of tissues in different pathological states was further analyzed by the ROC curve (AUC = 0.86), and the threshold for distinguishing normal tissue from tissue after ablation was 13.7 kPa. The accuracy of evaluating ablation tissue using SWE can reach 84.72%, providing data support for real-time quantitative observation of the ablation range.Conclusion: In conclusion the accurate visualization and real-time evaluation of the organizational change range of the MWA process can be realized by real-time SWE.

Ultrasound image segmentation using Gamma combined with Bayesian model for focused-ultrasound-surgery lesion recognition

This study aims to investigate the feasibility of combined segmentation for the separation of lesions from non-ablated regions, which allows surgeons to easily distinguish, measure, and evaluate the lesion area, thereby improving the quality of high-intensity focused-ultrasound (HIFU) surgery used for the non-invasive tumor treatment. Given that the flexible shape of the Gamma mixture model (GΓMM) fits the complex statistical distribution of samples, a method combining the GΓMM and Bayes framework is constructed for the classification of samples to obtain the segmentation result. An appropriate normalization range and parameters can be used to rapidly obtain a good performance of GΓMM segmentation. The performance values of the proposed method under four metrics (Dice score: 85%, Jaccard coefficient: 75%, recall: 86%, and accuracy: 96%) are better than those of conventional approaches including Otsu and Region growing. Furthermore, the statistical result of sample intensity indicates that the finding of the GΓMM is similar to that obtained by the manual method. These results indicate the stability and reliability of the GΓMM combined with the Bayes framework for the segmentation of HIFU lesions in ultrasound images. The experimental results show the possibility of combining the GΓMM with the Bayes framework to segment lesion areas and evaluate the effect of therapeutic ultrasound.

Real-Time Elastography versus Shear Wave Elastography on Evaluating the Timely Radiofrequency Ablation Effect of Rabbit Liver: A Preliminary Experimental Study

Purpose: to evaluate and monitor the timely thermal ablation changes of rabbit liver by using two elastographic methods—real-time elastography (RTE) and shear wave elastography (SWE)—as compared to contrast-enhanced ultrasound (CEUS) and physical specimens. Materials and Methods: 20 ablation zones were created in the livers of 20 rabbits using radiofrequency ablation (RFA). After the ablation, RTE and SWE were used to measure the elastic properties of the twenty ablation zones. The consistency of efficacy evaluation for RTE and SWE measurements was analyzed using the Bland–Altman test. The areas of the thermal ablation zones were also measured and compared according to the images provided by RTE, SWE, CEUS, and gross physical specimen measurement. Results: RTE and SWE could clearly display the shape of RFA ablation zones within one hour after the ablation. The average elasticity ratio for the ablation zone measured by RTE was 3.41 ± 0.67 (2.23–4.76); the average elasticity value measured by SWE was 50.7 ± 11.3 kPa (33.2–70.4 kPa). The mean areas of the ablation zones measured with RTE, SWE, gross specimen, and CEUS were 1.089 ± 0.199 cm2, 1.059 ± 0.201 cm2, 1.081 ± 0.201 cm2, and 3.091 ± 0.591 cm2, respectively. The Bland–Altman test showed that RTE and SWE have great consistency. Area measurements by CEUS were significantly larger than those of the other three methods (p < 0.05). Conclusion: RTE and SWE are both able to accurately confirm the range of ablation zones shortly after the ablation for rabbit livers.

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.