Projects per year
Abstract
Background
In proton therapy, the clinical application of linear energy transfer (LET) optimisation remains contentious, in part due to challenges associated with the definition and calculation of LET and its exact relationship with RBE due to large variation in experimental in vitro data. This has raised interest in other metrics with favourable properties for biological optimisation, such as the number of proton track-ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track-end counts.
Methods
We develop an ‘effective dose concept’ to translate between the total proton track-end count per unit mass in a voxel, and a proton relative biological effectiveness (RBE) value. Dose, track-end and dose-averaged LET (LETd) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track-ends and regions of elevated biological effectiveness in comparison to LETd-based models of RBE.
Results
Track-ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LETd. In patient simulations, our track-end model identified the same biological hotspots as predicted by LETd based radiobiological models of proton RBE.
Conclusion
These results suggest that, for clinical optimisation and evaluation, an RBE model based on proton track-end counts may match LETd-based models in terms of information provided, while also offering superior statistical properties.
In proton therapy, the clinical application of linear energy transfer (LET) optimisation remains contentious, in part due to challenges associated with the definition and calculation of LET and its exact relationship with RBE due to large variation in experimental in vitro data. This has raised interest in other metrics with favourable properties for biological optimisation, such as the number of proton track-ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track-end counts.
Methods
We develop an ‘effective dose concept’ to translate between the total proton track-end count per unit mass in a voxel, and a proton relative biological effectiveness (RBE) value. Dose, track-end and dose-averaged LET (LETd) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track-ends and regions of elevated biological effectiveness in comparison to LETd-based models of RBE.
Results
Track-ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LETd. In patient simulations, our track-end model identified the same biological hotspots as predicted by LETd based radiobiological models of proton RBE.
Conclusion
These results suggest that, for clinical optimisation and evaluation, an RBE model based on proton track-end counts may match LETd-based models in terms of information provided, while also offering superior statistical properties.
Original language | English |
---|---|
Journal | International Journal of Radiation: Oncology - Biology - Physics |
Early online date | 13 Jan 2023 |
DOIs | |
Publication status | E-pub ahead of print - 13 Jan 2023 |
Keywords
- Proton therapy
- Relative biological effectiveness
- Proton track-ends
- Linear energy transfer
Research Beacons, Institutes and Platforms
- Manchester Cancer Research Centre
Fingerprint
Dive into the research topics of 'Proposing a clinical model for RBE based on proton track-end counts'. Together they form a unique fingerprint.Projects
- 2 Finished
-
Grand Challenge Network in Network+ in Proton Therapy.
Kirkby, K. (PI) & Taylor, M. (CoI)
1/05/16 → 31/10/21
Project: Research
-
Global Challenge Network + in Advanced Radiotherapy.
Kirkby, K. (PI), Illidge, T. (CoI), Kirkby, N. (CoI), Mackay, R. (CoI), Merchant, M. (CoI) & Owen, H. (CoI)
1/07/15 → 30/06/21
Project: Research