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Optimization of Fluence Map for CyberKnife Raster Scanning Intensity Modulated Radiotherapy

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Background/Aim: Stereotactic body radiotherapy for prostate cancer using CyberKnife with circular cone requires a long treatment time. Raster scanning intensity modulated radiotherapy (RS-IMRT) has a potential of improving treatment efficacy,… Click to show full abstract

Background/Aim: Stereotactic body radiotherapy for prostate cancer using CyberKnife with circular cone requires a long treatment time. Raster scanning intensity modulated radiotherapy (RS-IMRT) has a potential of improving treatment efficacy, introducing shorter treatment time, better target dose uniformity, and lower organ at risk (OAR) dose. The purpose of the study was to develop a fluence optimization system for RS-IMRT. Patients and Methods: RS-IMRT plans were created for five prostate cancer patients treated with the Novalis system and parameters were compared to the Novalis treatment plans. From 80 nodes available for the CyberKnife, twelve nodes were arbitrarily selected. On the beam’s eye view of each beam, a 100×100 matrix of optimization points was created at the target center plane. The beam fluence map was optimized using the attraction-repulsion model (ARM). The beam fluence maps were converted to the scanning sequence using the ARM and a final dose calculation was performed. Results: For planning target volume (PTV), RS-IMRT plans showed higher dose covering 2% of the volume (D2%) and lower D98% compared to the Novalis plans. However, the homogeneity was within our Institutional clinical protocol. The RS-IMRT plans showed significantly lower OAR dose parameters including bladder volume receiving 100% of prescribed dose (V100%) and dose delivered to 5 cm3 of rectum (D5 cc). Conclusion: We developed a fluence optimization system for RS-IMRT that performs the entire RS-IMRT treatment planning process, including scanning sequence optimization and final dose calculation. The RS-IMRT was capable of generating clinically acceptable plans.

Keywords: intensity modulated; fluence; raster scanning; treatment; optimization; scanning intensity

Journal Title: AntiCancer Research
Year Published: 2023

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