Tolerance levels of mass density for CT number calibration in photon radiation therapy.

Computed tomography (CT) data are required to calculate the dose distribution in a patient's body. Generally, there are two CT number calibration methods for commercial radiotherapy treatment planning system (RTPS), namely CT number-relative electron density calibration (CT-RED calibration) and CT number-mass density calibration (CT-MD calibration). In a previous study, the tolerance levels of CT-RED calibration were established for each tissue type. The tolerance levels were established when the relative dose error to local dose reached 2%. However, the tolerance levels of CT-MD calibration are not established yet. We established the tolerance levels of CT-MD calibration based on the tolerance levels of CT-RED calibration. In order to convert mass density (MD) to relative electron density (RED), the conversion factors were determined with adult reference computational phantom data available in the International Commission on Radiological Protection publication 110 (ICRP-110). In order to validate the practicability of the conversion factor, the relative dose error and the dose linearity were validated with multiple RTPSes and dose calculation algorithms for two groups, namely, CT-RED calibration and CT-MD calibration. The tolerance levels of CT-MD calibration were determined from the tolerance levels of CT-RED calibration with conversion factors. The converted RED from MD was compared with actual RED calculated from ICRP-110. The conversion error was within ±0.01 for most standard organs. It was assumed that the conversion error was sufficiently small. The relative dose error difference for two groups was less than 0.3% for each tissue type. Therefore, the tolerance levels for CT-MD calibration were determined from the tolerance levels of CT-RED calibration with the conversion factors. The MD tolerance levels for lung, adipose/muscle, and cartilage/spongy-bone corresponded to ±0.044, ±0.022, and ±0.045 g/cm3 , respectively. The tolerance levels were useful in terms of approving the CT-MD calibration table for clinical use.

Tolerance levels of CT number to electron density table for photon beam in radiotherapy treatment planning system.

The accuracy of computed tomography number to electron density (CT-ED) calibration is a key component for dose calculations in an inhomogeneous medium. In a previous work, it was shown that the tolerance levels of CT-ED calibration became stricter with an increase in tissue thickness and decrease in the effective energy of a photon beam. For the last decade, a low effective energy photon beam (e.g., flattening-filter-free (FFF)) has been used in clinical sites. However, its tolerance level has not been established yet. We established a relative electron density (ED) tolerance level for each tissue type with an FFF beam. The tolerance levels were calculated using the tissue maximum ratio (TMR) and each corresponding maximum tissue thickness. To determine the relative ED tolerance level, TMR data from a Varian accelerator and the adult reference computational phantom data in the International Commission on Radiological Protection publication 110 (ICRP-110 phantom) were used in this study. The 52 tissue components of the ICRP-110 phantom were classified by mass density as five tissues groups including lung, adipose/muscle, cartilage/spongy-bone, cortical bone, and tooth tissue. In addition, the relative ED tolerance level of each tissue group was calculated when the relative dose error to local dose reached 2%. The relative ED tolerances of a 6 MVFFF beam for lung, adipose/muscle, and cartilage/spongy-bone were ±0.044, ±0.022, and ±0.044, respectively. The thicknesses of the cortical bone and tooth groups were too small to define the tolerance levels. Because the tolerance levels of CT-ED calibration are stricter with a decrease in the effective energy of the photon beam, the tolerance levels are determined by the lowest effective energy in useable beams for radiotherapy treatment planning systems.

[Development of a Phantom and Analysis Program for Assessment of Positional Accuracy of Image-guided Radiation Therapy].

PURPOSE: We created a phantom and analysis program for the assessment of IGRT positional accuracy. We verified the accuracy of analysis and the practicality of this evaluation method at several facilities. METHOD: End-to-end test was performed using an in-house phantom, and EPID images were acquired after displacement by an arbitrary amount using a micrometer, with after image registration as the reference. The difference between the center of the target and the irradiated field was calculated using our in-house analysis program and commercial software. The end-to-end test was conducted at three facilities, and the IGRT positional accuracy evaluation was verified. RESULT: The maximum difference between the displacement of the target determined from the EPID image and the arbitrary amount of micrometer displacement was 0.24 mm for the in-house analysis program and 0.30 mm for the commercial software. The maximum difference between the center of the target and the irradiation field on EPID images acquired at the three facilities was 0.97 mm. CONCLUSION: The proposed evaluation method using our in-house phantom and analysis program can be used for the assessment of IGRT positional accuracy.

CT number calibration audit in photon radiation therapy.

BACKGROUND: Inadequate computed tomography (CT) number calibration curves affect dose calculation accuracy. Although CT number calibration curves registered in treatment planning systems (TPSs) should be consistent with human tissues, it is unclear whether adequate CT number calibration is performed because CT number calibration curves have not been assessed for various types of CT number calibration phantoms and TPSs. PURPOSE: The purpose of this study was to investigate CT number calibration curves for mass density (ρ) and relative electron density (ρe ). METHODS: A CT number calibration audit phantom was sent to 24 Japanese photon therapy institutes from the evaluating institute and scanned using their individual clinical CT scan protocols. The CT images of the audit phantom and institute-specific CT number calibration curves were submitted to the evaluating institute for analyzing the calibration curves registered in the TPSs at the participating institutes. The institute-specific CT number calibration curves were created using commercial phantom (Gammex, Gammex Inc., Middleton, WI, USA) or CIRS phantom (Computerized Imaging Reference Systems, Inc., Norfolk, VA, USA)). At the evaluating institute, theoretical CT number calibration curves were created using a stoichiometric CT number calibration method based on the CT image, and the institute-specific CT number calibration curves were compared with the theoretical calibration curve. Differences in ρ and ρe over the multiple points on the curve (Δρm and Δρe,m , respectively) were calculated for each CT number, categorized for each phantom vendor and TPS, and evaluated for three tissue types: lung, soft tissues, and bones. In particular, the CT-ρ calibration curves for Tomotherapy TPSs (ACCURAY, Sunnyvale, CA, USA) were categorized separately from the Gammex CT-ρ calibration curves because the available tissue-equivalent materials (TEMs) were limited by the manufacturer recommendations. In addition, the differences in ρ and ρe for the specific TEMs (ΔρTEM and Δρe,TEM , respectively) were calculated by subtracting the ρ or ρe of the TEMs from the theoretical CT-ρ or CT-ρe calibration curve. RESULTS: The mean ± standard deviation (SD) of Δρm and Δρe,m for the Gammex phantom were -1.1 ± 1.2 g/cm3 and -0.2 ± 1.1, -0.3 ± 0.9 g/cm3 and 0.8 ± 1.3, and -0.9 ± 1.3 g/cm3 and 1.0 ± 1.5 for lung, soft tissues, and bones, respectively. The mean ± SD of Δρm and Δρe,m for the CIRS phantom were 0.3 ± 0.8 g/cm3 and 0.9 ± 0.9, 0.6 ± 0.6 g/cm3 and 1.4 ± 0.8, and 0.2 ± 0.5 g/cm3 and 1.6 ± 0.5 for lung, soft tissues, and bones, respectively. The mean ± SD of Δρm for Tomotherapy TPSs was 2.1 ± 1.4 g/cm3 for soft tissues, which is larger than those for other TPSs. The mean ± SD of Δρe,TEM for the Gammex brain phantom (BRN-SR2) was -1.8 ± 0.4, implying that the tissue equivalency of the BRN-SR2 plug was slightly inferior to that of other plugs. CONCLUSIONS: Latent deviations between human tissues and TEMs were found by comparing the CT number calibration curves of the various institutes.

Stoichiometric CT number calibration using three-parameter fit model for ion therapy.

PURPOSE: Treatment planning for ion therapy involves the conversion of computed tomography number (CTN) into a stopping-power ratio (SPR) relative to water. The purpose of this study was to create a CTN-to-SPR calibration table using a stoichiometric CTN calibration model with a three-parameter fit model for ion therapy, and to demonstrate its effectiveness by comparing it with a conventional stoichiometric CTN calibration model. METHODS: We inserted eight tissue-equivalent materials into a CTN calibration phantom and used six CT scanners at five radiotherapy institutes to scan the phantom. We compared the theoretical CTN-to-SPR calibration tables created using the three-parameter fit and conventional models to the measured CTN-to-SPR calibration table in three tissue types: lung, adipose/muscle, and cartilage/spongy bone. We validated the estimated SPR differences in all cases and in a worst-case scenario, which revealed the largest estimated SPR difference in lung tissue. RESULTS: For all cases, the means ± standard deviations of the estimated SPR difference for the three-parameter fit method model were -0.1 ± 1.0%, 0.3 ± 0.7%, and 2.4 ± 0.6% for the lung, adipose/muscle, and cartilage/spongy bone, respectively. For the worst-case scenario, the estimated SPR differences of the conventional and the three-parameter fit models were 2.9% and -1.4% for the lung tissue, respectively. CONCLUSIONS: The CTN-to-SPR calibration table of the three-parameter fit model was consistent with that of the measurement and decreased the calibration error for low-density tissues, even for the worst-case scenario.

Development of a CT number calibration audit phantom in photon radiation therapy: A pilot study.

PURPOSE: In photon radiation therapy, computed tomography (CT) numbers are converted into values for mass density (MD) or relative electron density to water (RED). CT-MD or CT-RED calibration tables are relevant for human body dose calculation in an inhomogeneous medium. CT-MD or CT-RED calibration tables are influenced by patient imaging (CT scanner manufacturer, scanning parameters, and patient size), the calibration process (tissue-equivalent phantom manufacturer, and selection of tissue-equivalent material), differences between tissue-equivalent materials and standard tissues, and the dose calculation algorithm applied; however, a CT number calibration audit has not been established. The purposes of this study were to develop a postal audit phantom, and to establish a CT number calibration audit process. METHODS: A conventional stoichiometric calibration conducts a least square fit of the relationships between the MD, material weight, and measured CT number, using two parameters. In this study, a new stoichiometric CT number calibration scheme has been empirically established, using three parameters to harmonize the calculated CT number with the measured CT number for air and lung tissue. In addition, the suitable material set and the minimal number of materials required for stoichiometric CT number calibration were determined. The MDs and elemental weights from the International Commission on Radiological Protection Publication 110 were used as standard tissue data, to generate the CT-MD and CT-RED calibration tables. A small-sized, CT number calibration phantom was developed for a postal audit, and stoichiometric CT number calibration with the phantom was compared to the CT number calibration tables registered in the radiotherapy treatment planning systems (RTPSs) associated with five radiotherapy institutions. RESULTS: When a least square fit was performed for the stoichiometric CT number calibration with the three parameters, the calculated CT number showed better agreement with the measured CT number. We established stoichiometric CT number calibration using only two materials because the accuracy of the process was determined not by the number of used materials but by the number of elements contained. The stoichiometric CT number calibration was comparable to the tissue-substitute calibration, with a dose difference less than 1%. An outline of the CT number calibration audit was demonstrated through a multi-institutional study. CONCLUSIONS: We established a new stoichiometric CT number calibration method for validating the CT number calibration tables registered in RTPSs. We also developed a CT number calibration phantom for a postal audit, which was verified by the performances of multiple CT scanners located at several institutions. The new stoichiometric CT number calibration has the advantages of being performed using only two materials, and decreasing the difference between the calculated and measured CT numbers for air and lung tissue. In the future, a postal CT number calibration audit might be achievable using a smaller phantom.

[Dosimetric perturbation due to scattered rays released by a gold marker used for tumor tracking in external radiotherapy].

Image-guided radiation therapy using a gold marker-based tumor tracking technique provides precise patient setup and monitoring. However, the marker consists of high-Z material, and the resulting scattered rays tend to have adverse effects on the dose distribution of radiotherapy. The purpose of this study was to evaluate the dosimetric perturbation due to the use of a gold marker for radiotherapy in the lungs. The relative dose distributions were compared with film measurement, Monte Carlo simulation, and XiO calculation with the multi grid superposition algorithm using two types of virtual lung phantoms, which were composed of tough water phantoms, tough lung phantoms, cork boards, and a 2.0-mm-diameter gold ball. No dose increase and decrease in the vicinity of the gold ball was seen in the XiO calculations, although it was seen in the film measurements and the Monte Carlo simulation. The dose perturbation due to a gold marker cannot be evaluated using XiO calculation with the superposition algorithm when the tumor is near a gold marker (especially within 0.5 cm). To rule out the presence of such dose perturbations due to a gold marker, the distance between the gold marker and the tumor must therefore be greater than 0.5 cm.