Dynamic Mode Decomposition for Transient Cavitation Bubbles Imaging in Pulsed High-Intensity Focused Ultrasound Therapy

• Published in: IEEE transactions on ultrasonics, ferroelectrics, and frequency control Vol. 71; no. 5; pp. 596 - 606
• Main Authors: Song, Minho, Sapozhnikov, Oleg A., Khokhlova, Vera A., Khokhlova, Tatiana D.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01-05-2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustics; Blood flow; Bubbles; Cavitation; Cavitation imaging; Cluster analysis; Clustering; Contrast agents; Datasets; Decay rate; Doppler effect; dynamic mode decomposition (DMD); Filters; Frequency control; High pass filters; high-intensity focused ultrasound (US); Imaging; Impulse response; Mapping; Plane waves; planewave Doppler; Singular value decomposition; Transient analysis; Transient cavitation; Ultrasonic imaging; Vector quantization
• ISSN: 0885-3010; 1525-8955; 1525-8955
• DOI: 10.1109/TUFFC.2024.3387351

Pulsed high-intensity focused ultrasound (pHIFU) can induce sparse de novo inertial cavitation without the introduction of exogenous contrast agents, promoting mild mechanical disruption in targeted tissue. Because the bubbles are small and rapidly dissolve after each HIFU pulse, mapping transient bubbles and obtaining real-time quantitative metrics correlated with tissue damage are challenging. Prior work introduced Bubble Doppler, an ultrafast power Doppler imaging method as a sensitive means to map cavitation bubbles. The main limitation of that method was its reliance on conventional wall filters used in Doppler imaging and its optimization for imaging blood flow rather than transient scatterers. This study explores Bubble Doppler enhancement using dynamic mode decomposition (DMD) of a matrix created from a Doppler ensemble for mapping and extracting the characteristics of transient cavitation bubbles. DMD was first tested in silico with a numerical dataset mimicking the spatiotemporal characteristics of backscattered signal from tissue and bubbles. The performance of DMD filter was compared to other widely used Doppler wall filter-singular value decomposition (SVD) and infinite impulse response (IIR) high-pass filter. DMD was then applied to an ex vivo tissue dataset where each HIFU pulse was immediately followed by a plane wave Doppler ensemble. In silico DMD outperformed SVD and IIR high-pass filter and ex vivo provided physically interpretable images of the modes associated with bubbles and their corresponding temporal decay rates. These DMD modes can be trackable over the duration of pHIFU treatment using k-means clustering method, resulting in quantitative indicators of treatment progression.