Determining efficient helical IMRT modulation factor from the MLC leaf-open time distribution on precision treatment planning system
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Updated: Jan 26, 2026

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
Robert Boyd1, Kyoungkeun Jeong1, Wolfgang A Tomé1
1Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA.
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.
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