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1.
Phys Med Biol ; 64(5): 058002, 2019 02 27.
Article in English | MEDLINE | ID: mdl-30811349

ABSTRACT

In this reply we present additional description of our linear model for LET optimization in response to the comments by Dr Gorissen. We clarify that this model cannot guarantee global optimal solutions to the sum-of-fractions problem. Based on our data, it could be used to optimize LET efficiently while dose constraints are maintained.


Subject(s)
Proton Therapy , Radiotherapy, Intensity-Modulated , Linear Energy Transfer , Organs at Risk , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted
2.
Phys Med Biol ; 63(1): 015013, 2017 12 19.
Article in English | MEDLINE | ID: mdl-29131808

ABSTRACT

The purpose of this study was to investigate the feasibility of incorporating linear energy transfer (LET) into the optimization of intensity modulated proton therapy (IMPT) plans. Because increased LET correlates with increased biological effectiveness of protons, high LETs in target volumes and low LETs in critical structures and normal tissues are preferred in an IMPT plan. However, if not explicitly incorporated into the optimization criteria, different IMPT plans may yield similar physical dose distributions but greatly different LET, specifically dose-averaged LET, distributions. Conventionally, the IMPT optimization criteria (or cost function) only includes dose-based objectives in which the relative biological effectiveness (RBE) is assumed to have a constant value of 1.1. In this study, we added LET-based objectives for maximizing LET in target volumes and minimizing LET in critical structures and normal tissues. Due to the fractional programming nature of the resulting model, we used a variable reformulation approach so that the optimization process is computationally equivalent to conventional IMPT optimization. In this study, five brain tumor patients who had been treated with proton therapy at our institution were selected. Two plans were created for each patient based on the proposed LET-incorporated optimization (LETOpt) and the conventional dose-based optimization (DoseOpt). The optimized plans were compared in terms of both dose (assuming a constant RBE of 1.1 as adopted in clinical practice) and LET. Both optimization approaches were able to generate comparable dose distributions. The LET-incorporated optimization achieved not only pronounced reduction of LET values in critical organs, such as brainstem and optic chiasm, but also increased LET in target volumes, compared to the conventional dose-based optimization. However, on occasion, there was a need to tradeoff the acceptability of dose and LET distributions. Our conclusion is that the inclusion of LET-dependent criteria in the IMPT optimization could lead to similar dose distributions as the conventional optimization but superior LET distributions in target volumes and normal tissues. This may have substantial advantages in improving tumor control and reducing normal tissue toxicities.


Subject(s)
Brain Neoplasms/radiotherapy , Linear Energy Transfer , Organs at Risk/radiation effects , Proton Therapy/standards , Radiotherapy Planning, Computer-Assisted/standards , Algorithms , Humans , Proton Therapy/methods , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methods , Relative Biological Effectiveness
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