Ultrasound-guided Characterization of Interstitial Ablated Tissue Using RF Time Series: Feasibility Study

Ablation therapy is an active field of study as a minimally invasive cancer treatment modality in the last few decades. Using this modality, the surrounding tissue can be preserved while targeting specific tumour locations. The limitation associated with ablation therapy is primarily the difficulties in monitoring the temperature rise and the extent of the ablated region in the tissue.

In this project, we present the results of a feasibility study to demonstrate the application of ultrasound RF time series imaging to accurately differentiate ablated and non-ablated tissue. We perform ex vivo ablation experiments on homogeneous chicken breast tissue specimens and in situ ablation experiments on porcine liver in the operating room immediately after an animal is sacrificed using ultrasound interstitial thermal therapy applicators (USITT). For 12 ex vivo and two in situ tissue samples, RF ultrasound signals are acquired prior to, and following, high intensity ultrasound ablation. Spatial and temporal features of these signals are used to characterize ablated and non-ablated tissue in a supervised-learning framework. In cross-validation evaluation, a subset of four features extracted from RF time series are able to produce a classification accuracy of 84.5%, and an area under ROC curve of 0.91 for ex vivo data, and an accuracy of 85% for in situ data.