Probabilistic objective functions for margin-less IMRT planning.

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Intensity-modulated radiation therapy (IMRT) planning traditionally relies on safety margins to account for geometric uncertainties.
• These margins can lead to unnecessary dose exposure to healthy tissues, particularly when planning target volumes overlap organs at risk.

Purpose of the Study:

• To develop and evaluate a probabilistic treatment planning method for IMRT that directly incorporates geometric uncertainties into the optimization process.
• To eliminate the need for safety margins and improve the balance between target coverage and organ-at-risk sparing.

Main Methods:

• A custom software plugin was developed for a commercial treatment planning system to implement probabilistic objective functions.
• The method directly includes geometrical uncertainties (translations and rotations) during optimization by blurring and shifting dose distributions.
• Prostate cancer treatment planning was used as a model, incorporating a novel technique for rotational uncertainties.

Main Results:

• Probabilistic plans achieved comparable or superior dose distributions to clinical plans, showing improved target coverage and rectum wall sparing.
• The method successfully incorporated random and systematic errors, including rotational uncertainties, without explicit safety margins.
• Plan optimization times were approximately double those of the conventional system, deemed acceptable for clinical implementation.

Conclusions:

• A practical, margin-less probabilistic treatment planning tool for IMRT has been developed and validated.
• This approach offers a feasible solution for clinical implementation, enabling more robust and precise radiation delivery.
• The method demonstrates the potential to improve treatment outcomes by optimizing dose distribution based on inherent uncertainties.