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

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.

Tolerance levels of mass density for adaptive helical tomotherapy using MVCT

Daily dose distributions for adaptive radiotherapy (ART) using helical tomotherapy (HT) are calculated using megavoltage computed tomography (MVCT). Generally, the MVCT number is converted to mass density (MD) using an MD calibration table (MVCT-MD table). The aims of this study are to calculate the tolerance levels of the MD for ART and to evaluate the tolerance levels using clinical patient plans. These tolerance levels of MD were calculated based on the tissue maximum ratio (TMR) of 6MV flattening-filter-free (FFF) beam of HT and the effective tissue thickness data from an International Commission on Radiological Protection 110 phantom data for lung, adipose/muscle and cartilage/spongy-bone. These tolerance levels were determined by considering both the MD causing a dose error of 2% and the variation in MVCT numbers. Subsequently, the stability of the MD values was estimated with the standard deviations (SD) in the MVCT number over 6 months. The dose distribution for clinical patient plans was calculated using the MVCT-MD table with added tolerance levels. These tolerance levels were determined as MD differences causing a dose error of 2%, and were ± 0.049 g/cm3, ± 0.030 g/cm3 and ± 0.049 g/cm3 for lung, adipose/muscle and cartilage/spongy-bone, respectively. The calculated dose distribution errors using the MVCT-MD table added tolerance levels were within 2%. We proposed these tolerance levels in MD for the quality control of the MVCT-MD table.

Evaluation of brass alloy density as tissue equivalence bolus using electron density phantom and optical density method

The brass mesh bolus alloy has been shown to be a promising substitute for tissue-equivalent bolus to increase the surface dose during breast cancer radiotherapy treatment. This study is aimed to evaluate the brass alloy density in order to better understand the brass qualities as a bolus in radiotherapy. The mass density of brass alloy determined in this work are using solid approaches, i) traditional density method, ii) Computed Tomography (CT) number using electron density phantom and CT scan and iii) mean pixel value via ImageJ software. According to ANOVA F (2,6) 2.982, p0.126, there was no statistically significant difference between the groups. As a result, all methods for calculating the density of brass alloy are valid. The X² test of CT number of brass plug to breast substitute in electron density phantom indicates no association. Density analysis using computed tomography and an electron density phantom, as well as the traditional density method and Image J analysis, were all shown to be acceptable methods for estimating the density of the brass alloy. Considering this, brass alloy can be considered as a potential substitute for tissue-equivalent bolus with further extensive of research in conjunction to CT number.

Effects of lung tissue characterization in radiotherapy of breast cancer under deep inspiration breath hold when using Monte Carlo dosimetry

PURPOSE

To investigate the sensitivity of Monte Carlo (MC) calculated lung dose distributions to lung tissue characterization in external beam radiotherapy of breast cancer under Deep Inspiration Breath Hold (DIBH).

METHODS

EGSnrc based MC software was employed. Mean lung densities for one hundred patients were analysed. CT number frequency and clinical dose distributions were calculated for 15 patients with mean lung density below 0.14 g/cm³. Lung volume with a pre-defined CT numbers was also considered. Lung tissue was characterized by applying different CT calibrations in the low-density region and air-lung tissue thresholds. Dose impact was estimated by Dose Volume Histogram (DVH) parameters.

RESULTS

Mean lung densities below 0.14 g/cm³ were found in 10% of the patients. CT numbers below -960 HU dominated the CT frequency distributions with a high rate of CT numbers at -990 HU. Mass density conversion approach influenced the DVH shape. V_4Gy and V_8Gy varied by 7% and 5% for the selected patients and by 9% and 3.5% for the pre-defined lung volume. V_16Gy and V_20Gy, were within 2.5%. Regions above 20 Gy were affected. Variations in air- lung tissue differentiation resulted in DVH parameters within 1%. Threshold at -990 HU was confirmed by the CT number frequency distributions.

CONCLUSIONS

Lung dose distributions were more sensitive to variations in the CT calibration curve below lung (inhale) density than to air-lung tissue differentiation. Low dose regions were mostly affected. The dosimetry effects were found to be potentially important to 10% of the patients treated under DIBH.

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.