Assessing software upgrades, plan properties and patient geometry using intensity modulated radiation therapy (IMRT)...

Area of Science:

• Medical Physics
• Radiation Oncology
• Radiotherapy Planning

Background:

• Intensity Modulated Radiation Therapy (IMRT) plan complexity is crucial for treatment efficacy and safety.
• Evaluating IMRT plan complexity requires sensitive and reliable metrics.
• Assessing complexity changes due to software upgrades, parameter adjustments, and patient geometry is essential.

Purpose of the Study:

• To compare the sensitivity of various complexity metrics in detecting changes in IMRT plan complexity.
• To evaluate correlations between different complexity metrics.
• To determine the most suitable metric for IMRT optimization.

Main Methods:

• Developed a program to calculate Modulation Index (MI), Modulation Complexity Score (MCS), and Plan Intensity Map Variation (PIMV).
• Assessed metrics using prostate IMRT patients after software upgrades (DAO) and parameter changes (field size, segment number).
• Evaluated metrics across different treatment sites and geometries; correlated metrics for 20 prostate IMRT patients.

Main Results:

• All metrics detected reduced complexity after optimization leaf sequencer upgrade.
• MI and MCS identified complexity reduction with direct aperture optimization (DAO).
• All metrics except PIMV detected complexity reduction with increased minimum field size; all except MI showed site-specific complexity differences. MCS and MI correlated better with treatment deliverability.

Conclusions:

• Complexity metrics are valuable tools in IMRT planning.
• IMRT plan complexity is influenced by software versions, planning parameters, and treatment site.
• MCS is the most suitable metric for IMRT optimization cost functions due to its sensitivity and deliverability correlation.