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.