MLC Leaf Adjustment for Direct-Aperture Optimization Treatment Planning

¹Radiation Oncology Department, Guangxi People’s Hospital, Nanning, China

²Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, USA

*Corresponding author: Dr. CM Charlie Ma, Ph.D. Radiation Oncology Department Fox Chase Cancer Center, 333 Cottman Avenue Philadelphia, PA 19111, USA, Tel: (215) 728-2996, Fax: (215) 728-4789, Email: [email protected]

Received Date: December 27, 2024

Published Date: January 21, 2025

Citation: Wu D, et al. (2025). MLC Leaf Adjustment for Direct-Aperture Optimization Treatment Planning. Mathews J Cancer Sci. 10(1):50.

Copyrights: Wu D, et al. © (2025).

ABSTRACT

Direct-aperture optimization (DAO) combines both dose optimization and leaf sequencing in the same optimization process. Due to the random selection of aperture shapes it is often time- consuming to find optimal aperture shapes in DAO and prone to target hot/cold spots. This study investigates MLC leaf position optimization for DAO treatment planning. Fifteen patients were unarchived from our clinical database, who were previously planned using the Varian Eclipse treatment planning system. These patients were re-planned using Prowess RT Pro with the same beam angles, dose constraints and optimization parameters. Manual MLC leaf adjustment was performed for these RT Pro plans to remove hot spots inside the target and cold spots near the target border. Plan quality was evaluated using the homogeneity index (HI), conformity index (CI), D_max (D1%), and D_min (D99%) for IMRT/VMAT, and R50% and D_2cm for SBRT, and dose- volume and D_mean for organs at risk (OAR). Treatment plan quality was significantly improved after adjusting MLC leaf positions following four simple rules for RT Pro plans generated using the DAO algorithm. The removal of hot spots inside the target and cold spots near the target border improved CI, HI and OAR mean doses as well as OAR dose-volume parameters. Minor adjustment of aperture shapes and/or removal of ineffective segments for RT Pro plans could significantly improve the plan quality to generate identical superior treatment plans as original Eclipse plans. The method developed in this work can be further programmed as a post- optimization tool to improve treatment planning quality and efficiency.

Keywords: Multileaf Collimator (MLC), Intensity Modulated Radiation Therapy (IMRT), Radiobiology, Direct-Aperture Optimization (DAO), Treatment Planning.