Ultrafast optical and passive acoustic mapping characterization of nanoscale cavitation nuclei based on gas vesicle proteins

Genetically encodable gas-filled particles, known as gas vesicles (GVs), have shown promise as a biomolecular contrast agent for ultrasound imaging and have the potential to be used as cavitation nuclei for ultrasound therapy. In this study, we used passive acoustic mapping techniques to characterize GV-seeded cavitation, utilizing 0.5 and 1.6 MHz ultrasound insonation over peak rarefactional pressures ranging from 100 to 2200 kPa. We found that GVs produce cavitation for the duration of the first applied pulse, up to at least 5000 cycles, but that bubble activity diminishes rapidly over subsequent pulses. At 0.5 MHz, the frequency content of cavitation emissions was predominantly broadband in nature, while at 1.6 MHz, narrowband content at harmonics of the main excitation frequency dominated. Simulations and high-speed camera imaging suggest that the received cavitation emissions come not from individual GVs but instead from the coalescence of GV-released gas into larger bubbles during the applied ultrasound pulse. These results will aid the future development of GVs as cavitation nuclei in ultrasound therapy.

Authors

Institutions

Publication Details

Journal
AIP Advances
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0239607
Citations
3
Primary Topic
Ultrasound and Hyperthermia Applications
Type
article
Field-Weighted Citation Impact
2.02

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ultrafast optical and passive acoustic mapping characterization of nanoscale cavitation nuclei based on gas vesicle proteins

Constantin Coussios, Cameron A. B. Smith, Mikhail G. Shapiro, Luca Baù et al.
3 citations
AIP Advances
Ultrasound and Hyperthermia Applications
2.02
article

Ultrafast optical and passive acoustic mapping characterization of nanoscale cavitation nuclei based on gas vesicle proteins

Constantin Coussios, Cameron A. B. Smith, Mikhail G. Shapiro, Luca Baù, Dina Malounda, Eleanor Stride, Avinoam Bar‐Zion, Qiang Wu
article en
3 citations

Abstract

Genetically encodable gas-filled particles, known as gas vesicles (GVs), have shown promise as a biomolecular contrast agent for ultrasound imaging and have the potential to be used as cavitation nuclei for ultrasound therapy. In this study, we used passive acoustic mapping techniques to characterize GV-seeded cavitation, utilizing 0.5 and 1.6 MHz ultrasound insonation over peak rarefactional pressures ranging from 100 to 2200 kPa. We found that GVs produce cavitation for the duration of the first applied pulse, up to at least 5000 cycles, but that bubble activity diminishes rapidly over subsequent pulses. At 0.5 MHz, the frequency content of cavitation emissions was predominantly broadband in nature, while at 1.6 MHz, narrowband content at harmonics of the main excitation frequency dominated. Simulations and high-speed camera imaging suggest that the received cavitation emissions come not from individual GVs but instead from the coalescence of GV-released gas into larger bubbles during the applied ultrasound pulse. These results will aid the future development of GVs as cavitation nuclei in ultrasound therapy.

AIP AdvancesVol. 15(2)
California Institute of Technology (US), Howard Hughes Medical Institute (US), University of Oxford (GB)
David and Lucile Packard Foundation, Chan Zuckerberg Initiative, Human Frontier Science Program, National Institutes of Health, Engineering and Physical Sciences Research Council
Affordable and clean energy
Openalex Percentile: Top 16%
Ultrasound and Hyperthermia Applications
2.02
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.