Automated target placement for VMAT lattice radiation therapy: enhancing efficiency and consistency

格子(音乐) 蒙特卡罗方法 放射治疗计划 计算机科学 核医学 一致性(知识库) 医学物理学 放射治疗 算法 数学 医学 统计 人工智能 物理 外科 声学
作者
Christopher L. Deufel,Christopher Dodoo,James Kavanaugh,Randi R. Finley,Karen Lang,Kasie L. Sorenson,Sheri M. Spreiter,Jamison Brooks,D Moseley,Safia K. Ahmed,Michael G. Haddock,J. Daniel,Sean S. Park,Ivy A. Petersen,Dawn Owen,Michael P. Grams
出处
期刊:Physics in Medicine and Biology [IOP Publishing]
卷期号:69 (7): 075010-075010 被引量:12
标识
DOI:10.1088/1361-6560/ad2ee8
摘要

Abstract Objective . An algorithm was developed for automated positioning of lattice points within volumetric modulated arc lattice radiation therapy (VMAT LRT) planning. These points are strategically placed within the gross tumor volume (GTV) to receive high doses, adhering to specific separation rules from adjacent organs at risk (OARs). The study goals included enhancing planning safety, consistency, and efficiency while emulating human performance. Approach . A Monte Carlo-based algorithm was designed to optimize the number and arrangement of lattice points within the GTV while considering placement constraints and objectives. These constraints encompassed minimum spacing between points, distance from OARs, and longitudinal separation along the z -axis. Additionally, the algorithm included an objective to permit, at the user’s discretion, solutions with more centrally placed lattice points within the GTV. To validate its effectiveness, the automated approach was compared with manually planned treatments for 24 previous patients. Prior to clinical implementation, a failure mode and effects analysis (FMEA) was conducted to identify potential shortcomings. Main results. The automated program successfully met all placement constraints with an average execution time (over 24 plans) of 0.29 ±0.07 min per lattice point. The average lattice point density (# points per 100 c.c. of GTV) was similar for automated (0.725) compared to manual placement (0.704). The dosimetric differences between the automated and manual plans were minimal, with statistically significant differences in certain metrics like minimum dose (1.9% versus 1.4%), D5% (52.8% versus 49.4%), D95% (7.1% versus 6.2%), and Body-GTV V30% (20.7 c.c. versus 19.7 c.c.). Significance. This study underscores the feasibility of employing a straightforward Monte Carlo-based algorithm to automate the creation of spherical target structures for VMAT LRT planning. The automated method yields similar dose metrics, enhances inter-planner consistency for larger targets, and requires fewer resources and less time compared to manual placement. This approach holds promise for standardizing treatment planning in prospective patient trials and facilitating its adoption across centers seeking to implement VMAT LRT techniques.
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