Technical Note: A fast online adaptive replanning method for VMAT using flattening filter free beams

Area of Science:

• Radiation Oncology
• Medical Physics
• Image-Guided Radiation Therapy

Background:

• Online replanning is crucial for Volumetric Modulated Arc Therapy (VMAT) to adapt to interfractional variations.
• Flattening Filter Free (FFF) beams offer faster treatment delivery but require efficient adaptive planning.
• Current adaptive strategies may not always provide optimal target coverage or account for daily anatomical changes.

Purpose of the Study:

• To develop and evaluate a rapid Segment Aperture Morphing (SAM) algorithm for online VMAT replanning.
• To assess the efficacy of SAM for adaptive planning using FFF beams in various cancer types.
• To compare SAM-based adaptive plans against standard image-guided radiation therapy (IGRT) repositioning and full reoptimization.

Main Methods:

• A software tool was created to integrate with a VMAT research planning system for parameter input/output.
• The SAM algorithm modified multileaf collimator positions based on daily imaging (CT/CBCT/MRI) changes.
• Leaf travel distance was limited to maintain VMAT delivery times; 11 patient cases were analyzed.

Main Results:

• SAM adaptive plans demonstrated improved target and organ-at-risk quality compared to IGRT repositioning.
• Plan quality, measured by PTV-V100, was comparable between SAM adaptive (97.61% ± 1.45%) and reoptimization plans (98.85% ± 1.13%).
• The SAM algorithm executed in under 10 seconds on standard hardware, enabling rapid online replanning.

Conclusions:

• The SAM algorithm provides a fast and effective method for online adaptive VMAT replanning with FFF beams.
• SAM-generated plans achieve plan quality comparable to full reoptimization, addressing interfractional variations.
• This approach facilitates timely adaptation to daily anatomical changes, enhancing radiation therapy precision.