A moment-based approach for DVH-guided radiotherapy treatment plan optimization

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Optimization

Background:

• Dose-volume histograms (DVHs) are crucial for assessing radiation therapy plan quality.
• Incorporating DVH constraints into intensity-modulated radiation therapy (IMRT) optimization is desirable but computationally challenging due to non-convexity.

Purpose of the Study:

• To develop a computationally tractable method for incorporating DVH constraints into IMRT optimization.
• To generate Pareto-optimal treatment plans that meet or exceed desired DVH objectives.

Main Methods:

• Proposed a novel convex-moment-based optimization approach.
• Replaced non-convex DVH constraints with a set of convex moment constraints.
• Applied two and three moment formulations to approximate desired DVHs in a prostate cancer case.

Main Results:

• The convex-moment-based approach effectively overcomes computational difficulties associated with non-convex DVH constraints.
• Generated Pareto-optimal treatment plans with DVHs comparable or superior to desired objectives.
• Demonstrated the approach's effectiveness in a clinical prostate cancer patient case.

Conclusions:

• The proposed convex-moment-based optimization is a viable and effective method for integrating DVH constraints into IMRT planning.
• This approach offers a practical solution for improving radiation therapy treatment plan quality and computational efficiency.