Considering marker visibility during leaf sequencing for segmental intensity-modulated radiation therapy.

Area of Science:

• Medical Physics
• Radiation Oncology
• Image-Guided Therapy

Background:

• Segmental intensity-modulated radiation therapy (IMRT) utilizes sequential beam segments to achieve precise dose distributions.
• Existing leaf sequencing algorithms aim to minimize delivered monitor units (MUs) and segment count, thereby reducing treatment time.
• The integration of real-time detection technology necessitates leaf sequencing algorithms that account for marker detectability.

Purpose of the Study:

• To develop and evaluate a novel leaf sequencing algorithm for segmental IMRT.
• The algorithm aims to optimize both monitor unit (MU) efficiency and marker visibility.
• To enhance the precision of image-guided radiation therapy through improved marker detection probability.

Main Methods:

• A new leaf sequencing algorithm was developed, building upon the Kamath algorithm.
• The algorithm incorporates a 'marker visibility' metric, representing marker detection probability.
• The proposed method involves initial sequencing via the Kamath algorithm, followed by column transformations for optimization.
• Performance was assessed using both artificial and clinical IMRT fields from prostate cancer patient plans.

Main Results:

• The new algorithm successfully increased marker visibility across various field sizes compared to the Kamath algorithm.
• Marker visibility improvements ranged from 31% to 91% for artificial fields and 9% to over 40% for clinical fields.
• The algorithm maintained or improved MU efficiency without increasing total delivered intensity.
• Marker visibility did not change in 4 out of 15 clinical fields evaluated.

Conclusions:

• A novel leaf sequencing algorithm has been developed for segmental IMRT.
• The algorithm optimizes for both monitor unit (MU) efficiency and marker visibility.
• The optimality of the developed algorithm was rigorously demonstrated.