Contrast-Enhanced Imaging of Histotripsy Bubble Clouds Using Chirp-Coded Excitation and Volterra Filtering.
IEEE Trans Ultrason Ferroelectr Freq Control
; 70(9): 989-998, 2023 09.
Article
en En
| MEDLINE
| ID: mdl-37379172
ABSTRACT
Histotripsy is a focused ultrasound therapy that ablates tissue via bubble cloud activity. Real-time ultrasound image guidance is used to ensure safe and effective treatment. Plane-wave imaging enables tracking of histotripsy bubble clouds at a high frame rate but lacks adequate contrast. Furthermore, bubble cloud hyperechogenicity is reduced in abdominal targets, making the development of contrast-specific sequences for deep-seated targets an active area of research. Chirp-coded subharmonic imaging was reported previously to enhance histotripsy bubble cloud detection by a modest 4-6 dB compared to the conventional sequence. Incorporating additional steps into the signal processing pipeline could enhance bubble cloud detection and tracking. In this study, we evaluated the feasibility of combining chirp-coded subharmonic imaging with Volterra filtering for enhancing bubble cloud detection in vitro. Chirped imaging pulses were used to track bubble clouds generated in scattering phantoms at a 1-kHz frame rate. Fundamental and subharmonic matched filters were applied to the received radio frequency signals, followed by a tuned Volterra filter to extract bubble-specific signatures. For subharmonic imaging, the application of the quadratic Volterra filter improved the contrast-to-tissue ratio from 5.18 ± 1.29 to 10.90 ± 3.76 dB, relative to the application of the subharmonic matched filter. These findings demonstrate the utility of the Volterra filter for histotripsy image guidance.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Litotricia
/
Ultrasonido Enfocado de Alta Intensidad de Ablación
Tipo de estudio:
Diagnostic_studies
/
Guideline
Límite:
Humans
Idioma:
En
Revista:
IEEE Trans Ultrason Ferroelectr Freq Control
Asunto de la revista:
MEDICINA NUCLEAR
Año:
2023
Tipo del documento:
Article