Program Information
Mechanistic Linear-Quadratic-Linear (LQL) Model for Large Doses Per Fraction
M Guerrero1*, M Carlone2, (1) University of Maryland School of Medicine, Baltimore, MD, (2) Princess Margaret Hospital, TORONTO, ON
TH-A-BRB-2 Thursday 8:00:00 AM - 9:55:00 AM Room: Ballroom BThe Linear-Quadratic (LQ) model has been successfully used for at least two decades to quantify radiation effects at standard (1.2-3Gy) doses. The validity of the standard LQ model for larger doses per fraction has been called into question by many authors, in part due to the continuous bending of the cell survival curve at large doses, contrary to results from in-vitro experiments. In recent years, Stereotactic Body Radiation Therapy (SBRT) treatments with large fraction doses have become more common, making the modeling for large doses per fraction of significant clinical relevance. Many authors have proposed extensions of the LQ model to address the shape of the cell survival curve at larger doses by arbitrary adding a phenomenological parameter to the LQ model. In this work, we discuss a Linear-Quadratic-Linear (LQL) model with a mechanistic formulation. This LQL model has one additional parameter with respect to the standard LQ model and can be derived by mechanistic arguments. The additional parameter makes the survival curve linear at high doses and has been estimated using in-vivo and in-vitro data. The advantage of a mechanistic model is that it allows for modeling of radiation effects for any given dose-rate and fractionation scheme. As an example, we present the LQL prediction for split dose experiments and low-dose-rate (LDR) prostate brachytherapy. The LQL model is equivalent to other mechanistic models like the Lethal-Potentially-Lethal model (LPL) but it retains the well-known parameters from the standard LQ model. As a clinical application, using estimated values of the additional parameter, we investigate the impact on the biologically effective dose (BED) for clinical SBRT treatment schedules of various cancer sites.
Learning Objectives:
1. Understand the limitations of the standard LQ model for large doses per fraction.
2. Understand the mechanistic formulation of the proposed LQL.
3. Understand how the LQL can be used to calculate the BED for SBRT radiation treatment schedules and compare them with standard fractionation.
Contact Email