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Variable RBE in proton therapy: comparison of different model predictions and their influence on clinical-like scenarios

Overview of attention for article published in Radiation Oncology, May 2016
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Title
Variable RBE in proton therapy: comparison of different model predictions and their influence on clinical-like scenarios
Published in
Radiation Oncology, May 2016
DOI 10.1186/s13014-016-0642-6
Pubmed ID
Authors

Giulia Giovannini, Till Böhlen, Gonzalo Cabal, Julia Bauer, Thomas Tessonnier, Kathrin Frey, Jürgen Debus, Andrea Mairani, Katia Parodi

Abstract

In proton radiation therapy a constant relative biological effectiveness (RBE) of 1.1 is usually assumed. However, biological experiments have evidenced RBE dependencies on dose level, proton linear energy transfer (LET) and tissue type. This work compares the predictions of three of the main radio-biological models proposed in the literature by Carabe-Fernandez, Wedenberg, Scholz and coworkers. Using the chosen models, a spread-out Bragg peak (SOBP) as well as two exemplary clinical cases (single field and two fields) for cranial proton irradiation, all delivered with state-of-the-art pencil-beam scanning, have been analyzed in terms of absorbed dose, dose-averaged LET (LET D ), RBE-weighted dose (D RBE) and biological range shift distributions. In the systematic comparison of RBE predictions by the three models we could show different levels of agreement depending on (α/β) x and LET values. The SOBP study emphasizes the variation of LET D and RBE not only as a function of depth but also of lateral distance from the central beam axis. Application to clinical-like scenario shows consistent discrepancies from the values obtained for a constant RBE of 1.1, when using a variable RBE scheme for proton irradiation in tissues with low (α/β) x , regardless of the model. Biological range shifts of 0.6- 2.4 mm (for high (α/β) x ) and 3.0 - 5.4 mm (for low (α/β) x ) were found from the fall-off analysis of individual profiles of RBE-weighted fraction dose along the beam penetration depth. Although more experimental evidence is needed to validate the accuracy of the investigated models and their input parameters, their consistent trend suggests that their main RBE dependencies (dose, LET and (α/β) x ) should be included in treatment planning systems. In particular, our results suggest that simpler models based on the linear-quadratic formalism and LETD might already be sufficient to reproduce important RBE dependencies for re-evaluation of plans optimized with the current RBE = 1.1 approximation. This approach would be a first step forward to consider RBE variations in proton therapy, thus enabling a more robust choice of biological dose delivery. The latter could in turn impact clinical outcome, especially in terms of reduced toxicities for tumors adjacent to organs at risk.

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Mendeley readers

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Greece 1 <1%
Unknown 131 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 30%
Researcher 23 17%
Student > Master 17 13%
Student > Bachelor 8 6%
Professor > Associate Professor 7 5%
Other 14 11%
Unknown 24 18%
Readers by discipline Count As %
Physics and Astronomy 58 44%
Medicine and Dentistry 16 12%
Engineering 8 6%
Nursing and Health Professions 5 4%
Biochemistry, Genetics and Molecular Biology 4 3%
Other 8 6%
Unknown 33 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 May 2016.
All research outputs
#14,703,374
of 16,669,654 outputs
Outputs from Radiation Oncology
#1,405
of 1,676 outputs
Outputs of similar age
#221,291
of 266,999 outputs
Outputs of similar age from Radiation Oncology
#1
of 1 outputs
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