The well-known clinical benefits of proton therapy are achieved through higher target-conformality and normal tissue sparing than conventional radiotherapy. However, there is an increased sensitivity to uncertainties in patient motion/setup, proton range and radiobiological effect. Although recent efforts have mitigated some uncertainties, radiobiological effect remains unresolved due to a lack of clinical data for relevant endpoints. Therefore, RBE optimisations may be currently unsuitable for clinical treatment planning. LET optimisation is a novel method that substitutes RBE with LET, shifting LET hotspots outside critical structures. This review outlines the current status of LET optimisation in proton therapy, highlighting knowledge gaps and possible future research. Following the PRISMA 2020 guidelines, a search of the MEDLINE${}^{\circledR }$ and Scopus databases was performed in July 2023, identifying 70 relevant articles. Generally, LET optimisation methods achieved their treatment objectives; however, clinical benefit is patient-dependent. Inconsistencies in the reported data suggest further testing is required to identify therapeutically favourable methods. We discuss the methods which are suitable for near-future clinical deployment, with fast computation times and compatibility with existing treatment protocols. Although there is some clinical evidence of a correlation between high LET and adverse effects, further developments are needed to inform future patient selection protocols for widespread application of LET optimisation in proton therapy.

Objective. Pancreatic adenocarcinoma (PDAC) is notoriously difficult to treat due to treatment-resistance and the pancreas’ proximity to organs at risks (OARs). Tumour hypoxia further complicates treatment, with substantial intra- and inter-tumour heterogeneity limiting predictability of treatment response, and often requiring multimodal therapy. Proton beam therapy (PBT) with concurrent chemotherapy has been proposed as a promising alternative for patients with locally-advanced unresectable disease. This study aims to evaluate the impact of tumour hypoxia on PBT outcomes in PDAC, and whether concurrent chemotherapy can offset hypoxia-related reductions in local control. Approach. Thirty PBT treatment plans from previous work were utilised. An in silico model was developed to generate multiple hypoxia scenarios within plausible bounds reported in literature on PDAC. The effect of intra-fraction reoxygenation was modelled, followed by the addition of concurrent gemcitabine-based chemotherapy from clinical data. For each scenario, three-dimensional distributions of biologically effective dose, survival fraction, and tumour control probability were evaluated. Main results. Tumour hypoxia significantly reduced the weighted average TCP in larger internal target volumes, particularly where PBT dose was constrained by proximity to OARs. Intra-fraction reoxygenation improved TCP by up to 13.4% [95%CI:6.5, 20.4], and was most effective in tumours with high-grade hypoxia and dose-limited regions. Chemotherapy improved TCP by up to 21.9% [95%CI:20.1, 26.2], though its benefit mitigated dose-loss due to nearby OARs rather than directly mitigating hypoxia. Significance. These findings highlight the importance of considering hypoxia and spatial dose limitations when evaluating treatment efficacy with PBT. Quantifying tumour hypoxia and reoxygenation dynamics before and during treatment could offer insight into local control outcomes. Concurrent chemotherapy can enhance tumour control, but its effect is more influenced by surrounding anatomy than hypoxia, suggesting that while it improves local control, it is insufficient as a standalone treatment for locally-advanced PDAC.