Development of a plan complexity mitigation algorithm based on gamma passing rate predictions for...

Area of Science:

• Radiation Oncology
• Medical Physics
• Radiotherapy Technology

Background:

• Volumetric-modulated arc therapy (VMAT) offers precise dose delivery but faces challenges with plan complexity and dose discrepancies.
• Discrepancies between calculated and measured doses in VMAT can impact treatment efficacy and safety.

Purpose of the Study:

• To develop and evaluate an algorithm for mitigating VMAT plan complexity.
• To improve the gamma passing rate (GPR) by optimizing multileaf collimator (MLC) positions.

Main Methods:

• A cohort of 50 VMAT patients with GPR below 85% were analyzed.
• A GPR prediction model identified problematic MLC positions for optimization.
• A nonlinear algorithm optimized MLC positions under mechanical constraints, followed by dose re-normalization.

Main Results:

• The algorithm reduced VMAT modulated complexity score (MCSv), averaged aperture area (AA), and monitor unit per gray (MU/Gy).
• Calculated dose parameters for target and surrounding regions remained consistent within 1%.
• Gamma passing rates improved by 1.8% (5%/1mm) and 1.3% (3%/2mm) for mitigated plans.

Conclusions:

• The developed algorithm effectively mitigates VMAT plan complexity.
• The algorithm shows potential for improving GPR in VMAT through minor MLC modifications.
• This feasibility study supports the clinical utility of the developed algorithm for VMAT.