An optimal algorithm for configuring delivery options of a one-dimensional intensity-modulated beam.

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Generating delivery options for one-dimensional intensity-modulated beams (1D IMBs) is crucial for intensity-modulated radiation therapy.
• Existing methods, like brute-force, are computationally intensive and inefficient for complex beam configurations.

Purpose of the Study:

• To develop an optimal-time algorithm for generating all distinct delivery options for arbitrary 1D IMBs.
• To improve the efficiency and applicability of delivery option generation in radiation therapy planning.

Main Methods:

• The study presents a novel algorithm based on the 'rightmost-preference' method.
• This approach imposes a specific order for pairing left and right leaf positions, optimizing the generation process.

Main Results:

• The new algorithm achieves optimal running time, linearly proportional to the number of distinct delivery options produced.
• Experiments show the rightmost-preference algorithm runs significantly faster than brute-force methods, enabling handling of larger IMBs.
• The algorithm supports additional constraints and random subset generation for managing numerous delivery options.

Conclusions:

• The developed rightmost-preference algorithm offers a substantial improvement in efficiency for generating 1D IMB delivery options.
• This advancement has potential applications in intensity-modulated arc therapy and 2D modulations, enhancing radiation therapy planning.