Dual-frequency acoustic droplet vaporization detection for medical imaging.
IEEE Trans Ultrason Ferroelectr Freq Control
; 62(9): 1623-33, 2015 Sep.
Article
em En
| MEDLINE
| ID: mdl-26415125
ABSTRACT
Liquid-filled perfluorocarbon droplets emit a unique acoustic signature when vaporized into gas-filled microbubbles using ultrasound. Here, we conducted a pilot study in a tissue-mimicking flow phantom to explore the spatial aspects of droplet vaporization and investigate the effects of applied pressure and droplet concentration on image contrast and axial and lateral resolution. Control microbubble contrast agents were used for comparison. A confocal dual-frequency transducer was used to transmit at 8 MHz and passively receive at 1 MHz. Droplet signals were of significantly higher energy than microbubble signals. This resulted in improved signal separation and high contrast-to-tissue ratios (CTR). Specifically, with a peak negative pressure (PNP) of 450 kPa applied at the focus, the CTR of B-mode images was 18.3 dB for droplets and -0.4 for microbubbles. The lateral resolution was dictated by the size of the droplet activation area, with lower pressures resulting in smaller activation areas and improved lateral resolution (0.67 mm at 450 kPa). The axial resolution in droplet images was dictated by the size of the initial droplet and was independent of the properties of the transmit pulse (3.86 mm at 450 kPa). In post-processing, time-domain averaging (TDA) improved droplet and microbubble signal separation at high pressures (640 kPa and 700 kPa). Taken together, these results indicate that it is possible to generate high-sensitivity, high-contrast images of vaporization events. In the future, this has the potential to be applied in combination with droplet-mediated therapy to track treatment outcomes or as a standalone diagnostic system to monitor the physical properties of the surrounding environment.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Ultrassonografia
/
Microscopia Acústica
/
Fluorocarbonos
Tipo de estudo:
Diagnostic_studies
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article