Robust Optimization for Spot-Scanning Proton Therapy based on Dose-Linear-Energy-Transfer Volume Constraints

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Traditional spot-scanning proton therapy (SSPT) planning uses separate dose-volume and linear energy transfer (LET) volume constraints.
• This separation can limit the ability to optimize both tumor control and organ-at-risk (OAR) protection simultaneously.
• Prostate cancer treatment planning requires careful balancing of dose and LET to minimize toxicity.

Purpose of the Study:

• To introduce a novel dose-LET-volume constraint robust optimization (DLVCRO) method for SSPT in prostate cancer.
• To achieve a superior joint dose and LET distribution, thereby minimizing adverse events.
• To enhance OAR protection while maintaining target coverage and plan robustness.

Main Methods:

• DLVCRO was developed, treating dose-LET-volume constraints (DLVCs) as soft constraints to shape dose-LET volume histogram (DLVH) curves.
• The method aims to minimize high LET/high dose overlap in OARs and redistribute LET from OARs to targets.
• Ten prostate cancer patients were retrospectively analyzed, comparing DLVCRO with conventional robust optimization (RO) using worst-case analysis and various histogram indices (DVH, LVH, xBDVH).

Main Results:

• DLVCRO significantly improved the joint dose and LET distribution for OAR protection in the nominal scenario compared to RO.
• Physical dose distributions in targets and OARs were comparable between the two methods.
• In the worst-case scenario, DLVCRO demonstrated markedly enhanced OAR protection while maintaining comparable target dose coverage and homogeneity robustness.

Conclusions:

• DLVCRO advances treatment planning from 2D DVH-based to 3D DLVH-based approaches.
• This method enables simultaneous and robust adjustment of dose and LET distributions.
• DLVCRO shows potential as a powerful tool for improving patient outcomes in SSPT.