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Updated: Jun 16, 2026

Multi-timescale Microscopy Methods for the Characterization of Fluorescently-labeled Microbubbles for Ultrasound-Triggered Drug Release
Published on: June 12, 2021
Temperature change near microbubbles within a capillary network during focused ultrasound
Alexander R Klotz1, Liis Lindvere, Bojana Stefanovic
1Sunnybrook Health Sciences Centre, Toronto, Ontario, M5R1B5, Canada. klotza@physics.mcgill.ca
Preformed gas bubbles enhance ultrasound treatments by increasing energy absorption. This study simulated heat transfer, revealing high localized temperatures near bubbles, crucial for optimizing therapeutic ultrasound planning.
Area of Science:
- Biomedical Engineering
- Acoustic Physics
- Medical Imaging
Background:
- Preformed gas bubbles enhance ultrasound energy absorption, suggesting their use in ultrasound treatments.
- In vivo studies show increased tissue temperature with bubbles, but microscopic temperature distribution remains uninvestigated.
Purpose of the Study:
- To simulate heat transfer between bubbles and tissue during focused ultrasound.
- To investigate the microscopic temperature distribution induced by microbubble oscillations.
Main Methods:
- Simulated microbubble oscillations within a rat cortical microvascular network.
- Used microbubble oscillation power density as input for the Pennes bioheat transfer equation.
- Mapped temperature solutions onto vascular data to create 3D temperature maps.
Main Results:
- Simulations showed high temperatures near bubbles and slow temperature rise in surrounding tissue.
- Heating increased with bubble frequency and insonation pressure, exhibiting a frequency-dependent peak.
- Induced temperature elevations were nonuniform, potentially impacting bio-effects.
Conclusions:
- Microbubble-induced heating is highly localized and dependent on frequency and pressure.
- Understanding these nonuniform temperature distributions is critical for effective therapeutic ultrasound planning.
- Further research can optimize bubble-enhanced ultrasound treatments by characterizing parameter effects.
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