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Updated: Jul 12, 2026
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The Visual Colorimetric Detection of Multi-nucleotide Polymorphisms on a Pneumatic Droplet Manipulation Platform
Published on: September 27, 2016
Monte Carlo-based prediction models for nanodroplet-mediated proton range verification
Bram Carlier1, Brent van der Heyden2,3, Sophie Heymans4,5
1Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium.
Physics in Medicine and Biology
|July 9, 2026
Summary
A new in silico model predicts nanodroplet response for proton range verification. This breakthrough enables contrast-mediated treatment verification, improving radiation therapy accuracy.
Area of Science:
- Medical Physics
- Radiotherapy Technology
- Nanotechnology
Background:
- Radiation-sensitive nanodroplets offer potential for in vivo proton range verification.
- Ultrasound contrast from radiation-induced droplet vaporization visualizes radiation deposition.
Purpose of the Study:
- Develop and validate an in silico model to predict nanodroplet radiation response.
- Enable contrast-mediated treatment verification using nanodroplets.
Main Methods:
- Combined theory of radiation-induced nucleation with Monte Carlo simulations.
- Determined effective ionizing particle fluence for nanodroplet vaporization.
- Validated model against phantom and rat experiments.
Main Results:
- Model accurately predicted vaporization distributions in phantoms.
- Achieved sub-millimeter proton range retrieval performance at body temperature.
- Demonstrated qualitative agreement with preclinical CT scans.
Conclusions:
- The prediction model is crucial for clinical nanodroplet-mediated proton range verification.
- The model's simplicity and generalizability support diverse radiotherapy applications.
