Modifications to the IMFAST leaf sequencing optimization algorithm

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Intensity Modulated Radiation Therapy (IMRT) planning aims to optimize dose delivery while minimizing treatment time.
• The IMFAST (Intensity Modulated Fast Leaf Sequencer) algorithm is used to minimize IMRT treatment times.
• Existing algorithms may not achieve optimal segment and level reduction, impacting treatment efficiency.

Purpose of the Study:

• To modify the IMFAST algorithm for improved efficiency in IMRT.
• To reduce the number of segments and relative fluence in treatment plans.
• To evaluate the modified algorithm's performance on clinical head and neck cancer cases.

Main Methods:

• Modified the segment extraction process in IMFAST to prioritize fewer segments and levels.
• Allowed successive optimization parameter values to increase.
• Tested the modified algorithm on two clinical head and neck IMRT cases, considering interdigitation and tongue-and-groove constraints.

Main Results:

• The modified IMFAST algorithm reduced segments by 7%-11% and relative fluence by 8%-17% compared to the original algorithm.
• Compared to the sweeping window algorithm, segment reduction ranged from 35%-55% with a -9% to 16% change in relative fluence.
• The modified IMFAST demonstrated the greatest segment reduction with minimal fluence increase compared to other published algorithms.

Conclusions:

• The modified IMFAST algorithm offers significant improvements in IMRT planning efficiency.
• This optimization leads to fewer segments and reduced relative fluence, potentially shortening treatment times.
• The enhanced algorithm provides superior performance for head and neck IMRT, especially with complex constraints.