Potential Therapeutic Improvements in Prostate Cancer Treatment Using Pencil Beam Scanning Proton Therapy with LET(d) Optimization and Disease-Specific RBE Models

利用LET(d)优化和疾病特异性RBE模型进行笔形束扫描质子治疗在改善前列腺癌治疗方面的潜在疗效

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Abstract

PURPOSE: To demonstrate the feasibility of improving prostate cancer patient outcomes with PBS proton LET(d) optimization. METHODS: SFO, IPT-SIB, and LET-optimized plans were created for 12 patients, and generalized-tissue and disease-specific LET-dependent RBE models were applied. The mean LET(d) in several structures was determined and used to calculate mean RBEs. LET(d)- and dose-volume histograms (LVHs/DVHs) are shown. TODRs were defined based on clinical dose goals and compared between plans. The impact of robust perturbations on LET(d), TODRs, and DVH spread was evaluated. RESULTS: LET(d) optimization achieved statistically significant increased target volume LET(d) of ~4 keV/µm compared to SFO and IPT-SIB LET(d) of ~2 keV/µm while mitigating OAR LET(d) increases. A disease-specific RBE model predicted target volume RBEs > 1.5 for LET-optimized plans, up to 18% higher than for SFO plans. LET-optimized target LVHs/DVHs showed a large increase not present in OARs. All RBE models showed a statistically significant increase in TODRs from SFO to IPT-SIB to LET-optimized plans. RBE = 1.1 does not accurately represent TODRs when using LET(d) optimization. Robust evaluations demonstrated a trade-off between increased mean target LET(d) and decreased DVH spread. CONCLUSION: The demonstration of improved TODRs provided via LET(d) optimization shows potential for improved patient outcomes.

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