Lung IMRT planning with automatic determination of beam angle configurations

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Beam angle configuration is critical in intensity-modulated radiation therapy (IMRT) planning, impacting dose distribution and treatment quality, particularly for complex lung cancer cases.
• Current IMRT planning often requires manual adjustments for optimal beam configurations, especially when incorporating noncoplanar beams.

Purpose of the Study:

• To develop and validate a novel, fully automated IMRT planning algorithm that incorporates noncoplanar beam configurations.
• To improve dose distributions and treatment quality in challenging lung cancer cases through automated planning.

Main Methods:

• A novel method for automatic beam angle selection was developed, utilizing a beam efficiency index map that considers individual beam contributions and multi-beam effects.
• This method was integrated with a previously reported organ-at-risk (OAR) dose-volume histogram (DVH) prediction model to create a complete automated planning algorithm.
• The algorithm was validated on complex lung IMRT cases with existing clinical plans that used noncoplanar beams.

Main Results:

• The automated planning algorithm successfully incorporated noncoplanar beam configurations in challenging lung cancer cases.
• Plans generated by the automated algorithm showed significant improvements in planning target volume (PTV) dose conformity and homogeneity compared to clinical plans.
• Most OAR dose metrics in the automated plans were statistically better than or comparable to those in clinical plans, with the exception of lung V5Gy.

Conclusions:

• The proposed automated IMRT planning algorithm can efficiently generate high-quality treatment plans for complex lung cancer cases, closely approximating clinical plan quality.
• The integration of noncoplanar beams and automated planning offers a promising approach to enhance IMRT treatment efficacy and efficiency.