Development and validation of a measurement‐based source model for kilovoltage cone‐beam CT Monte Carlo dosimetry simulations

Abstract

Purpose: The purpose of this study is to adapt an equivalent source model originally developed for conventional CT Monte Carlo dose quantification to the radiation oncology context and validate its application for evaluating concomitant dose incurred by a kilovoltage (kV) cone-beam CT (CBCT) system integrated into a linear accelerator. Methods: In order to properly characterize beams from the integrated kV CBCT system, the authors have adapted a previously developed equivalent source model consisting of an equivalent spectrum module that takes into account intrinsic filtration and an equivalent filter module characterizing the added bowtie filtration. An equivalent spectrum was generated for an 80, 100, and 125 kVp beam with beam energy characterized by half-value layer measurements. An equivalent filter description was generated from bowtie profile measurements for both the full-and half-bowtie. Equivalent source models for each combination of equivalent spectrum and filter were incorporated into the Monte Carlo software package MCNPX. Monte Carlo simulations were then validated against in-phantom measurements for both the radiographic and CBCT mode of operation of the kV CBCT system. Radiographic and CBCT imaging dose was measured for a variety of protocols at various locations within a body (32 cm in diameter) and head (16 cm in diameter) CTDI phantom. The in-phantom radiographic and CBCT dose was simulated at all measurement locations and converted to absolute dose using normalization factors calculated from air scan measurements and corresponding simulations. The simulated results were compared with the physical measurements and their discrepancies were assessed quantitatively. Results: Strong agreement was observed between in-phantom simulations and measurements. For the radiographic protocols, simulations uniformly underestimated measurements by 0.54%-5.14% (mean difference = −3.07%, SD = 1.60%). For the CBCT protocols, simulations uniformly underestimated measurements by 1.35%-5.31% (mean difference = −3.42%, SD = 1.09%). Conclusions: This work demonstrates the feasibility of using a measurement-based kV CBCT source model to facilitate dose calculations with Monte Carlo methods for both the radiographic and CBCT mode of operation. While this initial work validates simulations against measurements for simple geometries, future work will involve utilizing the source model to investigate kV CBCT dosimetry with more complex anthropomorphic phantoms and patient specific models.

A measurement-based generalized source model for Monte Carlo dose simulations of CT scans

“…These discrepancies may be caused by some specific settings in Spektr and SpekCalc related to the manufacturers’ specifications of x-ray tubes, which are not available to us. McMillan et al have also reported that their measurement-derived spectra for cone-beam CT were more than 10% harder than the spectra extracted with Spektr (McMillan et al , 2013). …”

“…Source modeling has been widely used in modern radiation therapy treatment planning dose calculation in patient anatomy for MV treatment systems such as linear accelerators (Chetty et al , 2000; Deng et al , 2000), Tomotherapy (Yuan et al , 2015) and CyberKnife (Deng et al , 2003; Deng et al , 2004), as well as kV imaging system such as kVCBCT (Spezi et al , 2011; McMillan et al , 2013). …”

Characterization of nanoDot optically stimulated luminescence detectors and high‐sensitivity MCP‐N thermoluminescent detectors in the 40–300 kVp energy range

“…The approach of using a combination of two beam quality indicators has been validated by other groups who have used it successfully to characterize the spectrum of an x‐ray beam for Monte Carlo dose computations using HVL 1 and kVp in one instance and HVL 1 and HVL 2 in another …”

Size-dependent scanning parameters (kVp and mAs) for photon-counting spectral CT system in pediatric imaging: simulation study

“…The method to measure the bowtie filter geometry is similar to that proposed by McMillan et al [41]. 2) where µ is the energy dependent attenuation coefficient, µ en is the energy absorption coefficient, and d air is the air thickness in the dosimeter.…”