Determining efficient helical IMRT modulation factor from the MLC leaf‐open time distribution on precision treatment planning system. Issue 5 (8th April 2019)

• Record Type: Journal Article
• Authors: Boyd, Robert; Jeong, Kyoungkeun; Tomé, Wolfgang A.
• Is Part Of: Journal of applied clinical medical physics. Volume 20:Issue 5(2019)
• Page Start: 64
• Page End: 74
• Publication Date: 2019-04-08
• Subjects: leaf‐open time -- modulation factor -- tomotherapy -- treatment planning; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.12581
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: Purpose: Since the modulation factor (MF) impacts both plan quality and delivery efficiency in tomotherapy Intensity Modulated Radiation Therapy (IMRT) treatment planning, the purpose of this study was to demonstrate a technique in determining an efficient MF from the Multileaf Collimator (MLC) leaf‐open time (LOT) distribution of a tomotherapy treatment delivery plan. Methods: Eight clinical plans of varying complexity were optimized with the highest allowed MF on the Accuracy Precision treatment planning system. Using a central limit theorem argument a range of reduced MFs were then determined from the first two moments of the LOT distribution. A step down approach was used to calculate the reduced‐MF plans and plan comparison tools available on the Precision treatment planning system were used to evaluate dose differences with the reference plan. Results: A reduced‐MF plan that balanced delivery time and dosimetric quality was found from the set of five MFs determined from the LOT distribution of the reference plan. The reduced‐MF plan showed good agreement with the reference plan (target and critical organ dose‐volume region of interest dose differences were within 1% and 2% of prescription dose, respectively). Discussion: Plan evaluation and acceptance criteria can vary depending on individual clinical expectations and dosimetric quality trade‐offs. With the scheme presented in this paper a planner should be able to efficiently generate a high‐quality plan with efficient delivery time without knowing a good MF beforehand. Conclusion: A methodology for deriving a reduced MF from the LOT distribution of a high MF treatment plan using the central limit theorem has been presented. A scheme for finding a reduced MF from a set of MFs that results in a plan balanced in both dosimetric quality and treatment delivery efficiency has also been presented.