Can automated treatment plans gain traction in the clinic?. Issue 8 (16th July 2019)

• Record Type: Journal Article
• Authors: Amaloo, Christopher; Hayes, Lane; Manning, Matthew; Liu, Han; Wiant, David
• Is Part Of: Journal of applied clinical medical physics. Volume 20:Issue 8(2019)
• Page Start: 29
• Page End: 35
• Publication Date: 2019-07-16
• Subjects: automation -- eclipse -- prostate -- RapidPlan -- scripting -- VMAT; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.12674
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: Recently, there has been an increased interest in the feasibility and impact of automation within the field of medical dosimetry. While there have been many commercialized solutions for automatic treatment planning, the use of an application programming interface to achieve complete plan generation for specific treatment sites is a process only recently available for certain commercial vendors. Automatic plan generation for 20 prostate patients was achieved via a stand‐alone automated planning script that accessed a knowledge‐based planning solution. Differences between the auto plans and clinically treated, baseline plans were analyzed and compared. The planning script successfully initialized a treatment plan, accessed the knowledge‐based planning model, optimized the plan, assessed for constraint compliance, and normalized the treatment plan for maximal coverage while meeting constraints. Compared to baseline plans, the auto‐generated plans showed significantly improved rectal sparing with similar coverage for targets and comparable doses to the remaining organs‐at‐risk. Utilization of a script, with its associated time saving and integrated process management, can quickly and automatically generate an acceptable clinical treatment plan for prostate cancer with either improved or similar results compared to a manually created plan.