Exploring the limits of LET-based target-RBE enhancement in proton therapy for lung cancer
Feasible gains and their therapeutic relevance
M.O.M. Koch (TU Delft - Mechanical Engineering)
M.S. Hoogeman – Mentor (TU Delft - Applied Sciences)
Steven Habraken – Mentor (Leiden University Medical Center)
Jenneke De Jong – Mentor (Erasmus MC)
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Abstract
Background and purpose: The variable RBE of protons could be strategically harnessed by confining high RBE to the tumor by optimizing the LET distribution, which has been shown to strongly correlate with RBE and does not contain the uncertainties associated with variable RBE models. However, increasing target LET compromises target dose robustness against setup and range uncertainties, as LET rises sharply past the Bragg peak, where the dose gradient is steep. Previous studies can lack thorough robustness analyses and rely on LET-based objectives in optimization, which are not available to all institutions. Lung cancer, in particular, remains underexplored in the context of target-LET optimization. This study therefore (i) investigates the elevation of target LET without relying on LET-based optimization objectives, (ii) determines the maximum feasible increase while maintaining
adequate target dose robustness and adherence to clinical goals, and (iii) assesses whether such increases translate into meaningful improvements in tumor control probability in a cohort of recently treated lung cancer patients.
Materials and methods: A LET-painting technique using two sets of opposing beams with beam-specific minimum dose objectives for proximal target segments was employed to elevate target LET. To find the near-feasible target LET, high inhomogeneity was
leveraged in combination with CTV-based planning, under the assumption of motion-mitigation. Probabilistic evaluation using Polynomial Chaos Expansion (PCE) was then performed to ensure precise adherence to adequate robustness. LET-optimized
treatment plans, employing this recipe, were then compared to dose-optimized treatment plans for 10 lung cancer patients, based on dose-averaged LET (LETd), LETd×D, Unkelbach RBE, and EUD-based TCP values.
Results: An increase of 50% in target LETd was observed for the probabilistically robust LET-optimized treatment plans compared to the dose-optimized plans, raising the RBE-weighted dose by 6 Gy and mean target RBE from 1.1 to 1.16. These gains were
associated with increased mean target dose, reduced target dose robustness and increased beam-entry doses. The elevated LETd significantly improved tumor control probability, although a large part of the total gain in TCP was due to increased physical dose.
Conclusion: Clinically significant increases in TCP due to enhanced target LETd are possible without the use of LETd-based objectives, by leveraging high inhomogeneity and precisely adhering to adequate target dose robustness. It should be determined
whether these trade-offs in addition to changes in OAR doses are clinically acceptable and should be directly compared to dose escalation strategies alone. Future technologies might help enhance benefits or improve trade-offs between inhomogeneity, robustness
and target LET, making target RBE-enhancement through LET to improve treatment efficacy more clinically viable.