Optimized Echo Decorrelation Imaging Feedback for Bulk Ultrasound Ablation Control

Abstract

Feasibility of controlling bulk ultrasound (US) thermal ablation using echo decorrelation imaging was investigated in ex vivo bovine liver. The first of two ablation and control procedures used a sequence of constant-intensity sonication cycles, ceased when the minimum echo decorrelation within a control region of interest (ROI) exceeded a predetermined threshold. The second procedure used a variable-intensity sonication sequence, with spatially averaged decorrelation as the stopping criterion. US exposures and echo decorrelation imaging were performed by a linear image-ablate array. Based on preliminary experiments, control ROIs and thresholds for the minimum-decorrelation and average-decorrelation criteria were specified. Controlled trials for the minimum-decorrelation and average-decorrelation criteria were compared with uncontrolled trials employing 9 or 18 cycles of matching sonication sequences. Lesion dimensions, treatment times, ablation rates, and areas under receiver operating characteristic curves were statistically compared. Successfully controlled trials using both criteria required significantly shorter treatment times than corresponding 18-cycle treatments, with better ablation prediction performance than uncontrolled 9-cycle and 18-cycle treatments. Either control approach resulted in greater ablation rate than corresponding 9-cycle or 18-cycle uncontrolled approaches. A post hoc analysis studied the effect of exchanging control criteria between the two series of controlled experiments. For either group, the average time needed to exceed the alternative decorrelation threshold approximately matched the average duration of successfully controlled experimental trials. These results indicate that either approach, using minimum-decorrelation or average-decorrelation criteria, is feasible for control of bulk US ablation. In addition, use of a variable-intensity sonication sequence for bulk US thermal ablation can result in larger ablated regions compared to constant-intensity sonication sequences.

Fig. 1:

Experimental setup. (a) 64-element image-treat array aligned with top surface of ex vivo bovine liver. (b) Control geometry for bulk US thermal ablation. The control ROI, bounded by a yellow line, is superimposed on a hybrid echo decorrelation/B-mode image. (c) Feedback control algorithm flow chart. (d) Treatment timing diagram.

Fig. 2:

Optimization approach for control criteria. Segmented TTC-stained tissue sections of preliminary ablation trials were classified into (a) ablated-ROI and (b) unablated-ROI groups for ROI size selection. Sensitivity and specificity curves for the chosen ROIs were used to optimize Δ_th for (c) minimum-decorrelation (N=30) and (d) average-decorrelation (N=86) prediction of complete ROI ablation. The blue line represents the selected ablation control threshold for each approach.

Fig 3:

Representative histologic and US images for controlled and uncontrolled trails using the minimum-decorrelation feedback approach. Rows (I-III) represent 9-cycle uncontrolled, successfully controlled, and 18-cycle uncontrolled trails with segmentation of tissue boundaries and ablated regions. Red and green lines represent segmented tissue and ablation region boundaries, while white and dashed green lines indicate the segmented tissue and predicted ablation region boundaries in the hybrid echo decorrelation/B-mode images. Columns (a-c) represent trails with approximately minimum, average, and maximum measured lesion depth for each group.

Fig. 4:

Statistical analysis of ablation results using the minimum-decorrelation feedback approach. (a) ROC curves for successfully controlled, 9-cycle uncontrolled, and 18-cycle uncontrolled groups (AUC: area under ROC curve). Means and standard errors are shown for (b) lesion width, (c) lesion depth, and (d) ablation rate. (** p < 10⁻² and *** p < 10⁻³)

Fig. 5:

Representative histologic and US images for controlled and uncontrolled trials using the average-decorrelation feedback approach. Rows (I-III) represent 9-cycle, controlled, and 18-cycle trials with segmentation of tissue boundaries and ablated regions. Red and green lines represent segmented tissue and ablation region boundaries, while white and dashed green lines indicate the segmented tissue and predicted ablation region boundaries in the hybrid echo decorrelation/B-mode images. Columns (a-c) represent trials with approximately minimum, average, and maximum measured lesion depth of each group.

Fig. 6:

Statistical analysis of results from ablation trials using the average-decorrelation feedback approach. (a) ROC curves for successfully controlled, 9-cycle uncontrolled, and 18-cycle uncontrolled groups. Means and standard errors are shown for (b) lesion width, (c) lesion depth, and (d) ablation rate. (e) Box plot of average echo decorrelation value inside the control ROI for trials with observed audible sound (N=17) and with no audible sound (N =16). (*** p < 10⁻³)

Fig. 7:

Statistical comparison of ablation results for successfully controlled trials using the minimum-decorrelation and average-decorrelation feedback criteria. Means and standard errors are shown for (a) lesion width, (b) lesion depth, (c) treatment time and (d) ablation rate. (* p < 0.05 and *** p < 10⁻³)

Fig. 8:

Comparison of predicted vs. measured ablation areas. Scatter plots are shown for (a) 9-cycle, (b) successfully controlled, and (c) 18-cycle groups using (I) minimum-decorrelation and (II) average-decorrelation control approaches.

Fig. 9:

Experimental and post hoc results for trials controlled by (a) minimum- decorrelation and (b) average-decorrelation criteria. Red, black and blue lines represent the experimental, post hoc, and threshold echo decorrelation values inside the region of interest, respectively.