A kernel smoothing algorithm for ablation visualization in ultrasound elastography.

Three-dimensional visualization of tumor ablation procedures have significant clinical value because the ability to accurately visualize ablated volumes can help clinicians gauge the extent of ablated tissue necrosis and plan future treatment steps. Better control over ablation volume can prevent recurrence of tumors treated using ablative procedures. This paper presents a kernel based smoothing algorithm called MatérnSmooth to reconstruct shear wave velocity maps from data acquired through ultrasound electrode vibration elastography. Shear wave velocity estimates are acquired on several intersecting imaging planes that share a common axis of intersection collinear with the ablation needle. An objective method of choosing smoothing parameters from underlying data is outlined through simulations. Experimental validation was performed on data acquired from a tissue mimicking phantom. Volume estimates were found to be within 20% of the true value.

Post-Procedure Evaluation of Microwave Ablations of Hepatocellular Carcinomas Using Electrode Displacement Elastography.

Microwave ablation has been used clinically as an alternative to surgical resection. However, lack of real-time imaging to assess treated regions may compromise treatment outcomes. We previously introduced electrode displacement elastography (EDE) for strain imaging and verified its feasibility in vivo on porcine animal models. In this study, we evaluated EDE on 44 patients diagnosed with hepatocellular carcinoma, treated using microwave ablation. The ablated region was identified on EDE images for 40 of the 44 patients. Ablation areas averaged 13.38 ± 4.99 cm2 on EDE, compared with 7.61 ± 3.21 cm2 on B-mode imaging. Contrast and contrast-to-noise ratios obtained with EDE were 232% and 98%, respectively, significantly higher than values measured on B-mode images (p < 0.001). This study indicates that EDE is feasible in patients and provides improved visualization of the ablation zone compared with B-mode ultrasound.

Ultrasonic tracking of shear waves using a particle filter.

PURPOSE: This paper discusses an application of particle filtering for estimating shear wave velocity in tissue using ultrasound elastography data. Shear wave velocity estimates are of significant clinical value as they help differentiate stiffer areas from softer areas which is an indicator of potential pathology. METHODS: Radio-frequency ultrasound echo signals are used for tracking axial displacements and obtaining the time-to-peak displacement at different lateral locations. These time-to-peak data are usually very noisy and cannot be used directly for computing velocity. In this paper, the denoising problem is tackled using a hidden Markov model with the hidden states being the unknown (noiseless) time-to-peak values. A particle filter is then used for smoothing out the time-to-peak curve to obtain a fit that is optimal in a minimum mean squared error sense. RESULTS: Simulation results from synthetic data and finite element modeling suggest that the particle filter provides lower mean squared reconstruction error with smaller variance as compared to standard filtering methods, while preserving sharp boundary detail. Results from phantom experiments show that the shear wave velocity estimates in the stiff regions of the phantoms were within 20% of those obtained from a commercial ultrasound scanner and agree with estimates obtained using a standard method using least-squares fit. Estimates of area obtained from the particle filtered shear wave velocity maps were within 10% of those obtained from B-mode ultrasound images. CONCLUSIONS: The particle filtering approach can be used for producing visually appealing SWV reconstructions by effectively delineating various areas of the phantom with good image quality properties comparable to existing techniques.