Minimax optimization for handling range and setup uncertainties in proton therapy.

Area of Science:

• Radiation Oncology
• Medical Physics
• Computational Biology

Background:

• Intensity modulated proton therapy (IMPT) plans are highly sensitive to setup and range uncertainties.
• Conventional planning margins are often inadequate for robust IMPT delivery.
• Robust optimization methods are needed to account for treatment uncertainties.

Purpose of the Study:

• To develop and evaluate a minimax optimization method for robust IMPT planning.
• To incorporate range and setup uncertainties directly into the optimization process.
• To compare the minimax method against conventional uncertainty management techniques.

Main Methods:

• A minimax optimization approach was developed, minimizing the worst-case scenario penalty.
• Physically realizable error scenarios were considered to avoid unnecessary plan conservatism.
• The method was applied to lung, paraspinal (with titanium), and prostate cancer cases.

Main Results:

• Minimax optimization achieved robust target coverage in all tested cases.
• It demonstrated superior sparing of organs at risk (lung, spinal cord, rectum) compared to conventional methods.
• The method effectively handled complexities like low-density lung tissue and high-density titanium implants.

Conclusions:

• Minimax optimization offers a robust solution for IMPT planning, ensuring target coverage and sparing healthy tissues.
• Conventional methods like margins, SFUD, and MO are less effective and may lead to suboptimal dose delivery.
• This approach maximizes the potential of IMPT by addressing uncertainties during optimization.