title: Using passive cavitation images to classify high-intensity focused ultrasound lesions.
abstract: Passive cavitation imaging provides spatially resolved monitoring of cavitation emissions. However, the diffraction limit of a linear imaging array results in relatively poor range resolution. Poor range resolution has limited prior analyses of the spatial specificity and sensitivity of passive cavitation imaging in predicting thermal lesion formation. In this study, this limitation is overcome by orienting a linear array orthogonal to the high-intensity focused ultrasound propagation direction and performing passive imaging. Fourteen lesions were formed in ex vivo bovine liver samples as a result of 1.1-MHz continuous-wave ultrasound exposure. The lesions were classified as focal, "tadpole" or pre-focal based on their shape and location. Passive cavitation images were beamformed from emissions at the fundamental, harmonic, ultraharmonic and inharmonic frequencies with an established algorithm. Using the area under a receiver operating characteristic curve (AUROC), fundamental, harmonic and ultraharmonic emissions were found to be significant predictors of lesion formation for all lesion types. For both harmonic and ultraharmonic emissions, pre-focal lesions were classified most successfully (AUROC values of 0.87 and 0.88, respectively), followed by tadpole lesions (AUROC values of 0.77 and 0.64, respectively) and focal lesions (AUROC values of 0.65 and 0.60, respectively).
authors.affiliation: Division of Cardiovascular Health and Disease, Department of Internal Medicine, University of Cincinnati, Cincinnati, Ohio, USA; Biomedical Engineering Program, University of Cincinnati, Cincinnati, Ohio, USA. Electronic address: kevin.haworth@uc.edu.
authors.forename: Kevin J
authors.initials: KJ
authors.lastname: Haworth
authors.affiliation: Biomedical Engineering Program, University of Cincinnati, Cincinnati, Ohio, USA.
authors.forename: Vasant A
authors.initials: VA
authors.lastname: Salgaonkar
authors.affiliation: Biomedical Engineering Program, University of Cincinnati, Cincinnati, Ohio, USA.
authors.forename: Nicholas M
authors.initials: NM
authors.lastname: Corregan
authors.affiliation: Division of Cardiovascular Health and Disease, Department of Internal Medicine, University of Cincinnati, Cincinnati, Ohio, USA; Biomedical Engineering Program, University of Cincinnati, Cincinnati, Ohio, USA.
authors.forename: Christy K
authors.initials: CK
authors.lastname: Holland
authors.affiliation: Biomedical Engineering Program, University of Cincinnati, Cincinnati, Ohio, USA.
authors.forename: T Douglas
authors.initials: TD
authors.lastname: Mast
mesh_terms: D000465:Algorithms; D000818:Animals; D002417:Cattle; D006498:Hepatectomy / Q000379:methods; D057086:High-Intensity Focused Ultrasound Ablation / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D066298:In Vitro Techniques; D008099:Liver / Q000000981:diagnostic imaging* / Q000601:surgery*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014463:Ultrasonography / Q000379:methods*
keywords: Cavitation; Passive acoustic mapping; Receiver operating characteristic curve; Thermal ablation monitoring; Ultrasound-guided ablation