title: Ultrasound-guided characterization of interstitial ablated tissue using RF time series: feasibility study.
abstract: This paper presents the results of a feasibility study to demonstrate the application of ultrasound RF time series imaging to accurately differentiate ablated and nonablated tissue. 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 nonablated tissue in a supervised-learning framework. In cross-validation evaluation, a subset of four features extracted from RF time series produce a classification accuracy of 84.5%, an area under ROC curve of 0.91 for ex vivo data, and an accuracy of 85% for in situ data. Ultrasound RF time series is a promising approach for characterizing ablated tissue.
authors: Department of Electrical and Computer Engineering, Queen’s university, Kingston, ON K7L 3N6, Canada. farhad@cs.queensu.ca
authors: Farhad
authors: F
authors: Imani
authors: Purang
authors: P
authors: Abolmaesumi
authors: Mark Z
authors: MZ
authors: Wu
authors: Andras
authors: A
authors: Lasso
authors: Everett C
authors: EC
authors: Burdette
authors: Goutam
authors: G
authors: Ghoshal
authors: Tamas
authors: T
authors: Heffter
authors: Emery
authors: E
authors: Williams
authors: Paul
authors: P
authors: Neubauer
authors: Gabor
authors: G
authors: Fichtinger
authors: Parvin
authors: P
authors: Mousavi
mesh_terms: D000818:Animals; D002645:Chickens; D005240:Feasibility Studies; D057086:High-Intensity Focused Ultrasound Ablation / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000601:surgery; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000601:surgery; D011846:Radio Waves; D012815:Signal Processing, Computer-Assisted; D013552:Swine