Aperture generation based on threshold segmentation for intensity modulated radiotherapy treatment planning

Area of Science:

• Medical Physics
• Radiotherapy
• Computational Biology

Background:

• Radiotherapy planning aims to optimize dose delivery while minimizing toxicity.
• Current methods like column-generation-based (cg) planning can be computationally intensive and time-consuming.
• Efficient aperture generation is crucial for improving treatment planning workflows.

Purpose of the Study:

• To introduce a novel, simplified aperture generation technique based on threshold segmentation (agts).
• To evaluate the agts method's effectiveness in reducing computation and planning time compared to the established cg method.
• To assess the impact of agts on treatment plan quality, including target coverage and organ-at-risk sparing.

Main Methods:

• The agts method involves two main steps: noise cancellation using a fuzzy controller and aperture generation via threshold segmentation.
• The proposed agts strategy was applied to seven prostate tumor cases.
• Treatment plans generated by agts were compared against those from the cg method using metrics such as homogeneity index, conformity number, OAR sparing, and total planning time.

Main Results:

• The agts technique successfully generated treatment plans comparable in quality to those produced by the cg method.
• A significant reduction in planning time was observed with agts, averaging approximately 58.61% ± 0.40 less than the cg method.
• Key plan quality metrics, including target volume coverage and OAR sparing, were maintained with the agts approach.

Conclusions:

• The agts algorithm offers a viable alternative for aperture generation in radiotherapy planning.
• This method effectively reduces planning time without compromising treatment plan quality.
• The agts approach presents a promising strategy for streamlining radiotherapy workflows.