Shuichi Ozawa

Background: Small‐field dosimetry plays a pivotal role in stereotactic body radiation therapy (SBRT), where high‐precision dose delivery is essential. In multi‐institutional clinical trials, quality assurance (QA) becomes increasingly critical due to the variability in linear accelerator (linac) output calibration and treatment planning system (RTPS) configurations. Conventional relative dose factor, which assess relative dose outputs, lack absolute dose information and thus cannot verify the consistency of linac calibration or monitor unit (MU)‐to‐dose conversion across institutions. These limitations may compromise treatment quality and undermine the integrity of clinical trials. Therefore, an enhanced QA method that incorporates absolute dosimetry is required. Purpose: This study introduces and implements a novel credentialing procedure for small‐field dosimetry in SBRT clinical trials using the absorbed dose per MU, expressed in cGy/MU. By integrating absolute dose information into the verification process, this method aims to evaluate both linac output calibration and small‐field modeling accuracy across institutions. Methods: A nationwide dosimetric survey was conducted involving 545 beams from 120 institutions participating in Japan Clinical Oncology Group (JCOG) trials. Treatment plans were created in each institution's RTPS by prescribing 10 Gy to the isocenter for square field sizes of 2 × 2 to 10 × 10 cm ² . Doses were calculated at depths of 5 and 10 cm in a virtual water phantom under a fixed source‐to‐surface distance of 90 cm. The absorbed dose per MU values were calculated and compared against multicenter averages stratified by linac type and beam energy. A ±3% tolerance criterion was applied for credentialing. Institutions with deviations were contacted and corrective actions were taken as needed. Results: Of the 545 beams analyzed, 97.8% met the ±3% tolerance criteria. Discrepancies in the ten beams were attributed to small‐field beam modeling errors or incorrect RTPS MU‐to‐dose settings, which were subsequently corrected through feedback. Although variations were observed between the dose calculation algorithms and RTPSs, the differences were within 0.6%, 0.4%, and 1.6%, respectively. The credentialing process proved robust in standardizing dose calculations for clinical trial participation. Conclusion: The proposed absorbed dose per MU‐based method enables comprehensive small‐field dosimetry evaluation by incorporating absolute dose verification into the credentialing process. This approach effectively identifies calibration inconsistencies that are not detectable using traditional relative dose factor methods. Its application across a large cohort of institutions demonstrated high accuracy and inter‐institutional consistency, reinforcing its utility as a practical QA tool in SBRT clinical trials. By enhancing standardization in RTPS performance and linac output verification, this method strengthens the foundation of safe and reliable SBRT implementation in multi‐center clinical research.

This study evaluates current practices and challenges associated with computed tomography number-to-mass density (CT–MD) conversion tables in helical tomotherapy across Japan and explores directions for standardization and quality improvement amid the increasing adoption of adaptive radiotherapy (ART). A nationwide web-based survey was conducted across 34 institutions utilizing the Radixact system. Data were collected on CT acquisition protocols, calibration phantoms, density plugs, reconstruction algorithms, table registration timing and quality assurance (QA) frequency. Registered CT–MD tables were categorized by CT modality: Simulation CT (SimCT), ClearRT and CTrue. ClearRT tables were analyzed by phantom setup (full vs half), and CTrue tables by reconstruction method [filtered back projection (FPB) vs iterative reconstruction (IR)]. Inter-institutional variations in CT numbers and the number of data points were assessed. SimCT tables exhibited the widest variation in the number of data points (median = 10) and high-density CT numbers. ClearRT tables (median = 8) showed variations of up to 300 Hounsfield units (HU) in cortical bone; the half-phantom setup reduced inter-institutional variability. CTrue tables (median = 8) demonstrated high consistency, with negligible differences between IR and FPB. All plug CT numbers of CTrue remained within the tolerance defined by the American Association of Physicists in Medicine Task Group 148. However, CT numbers for air plugs varied by ~±30 HU, indicating inconsistent handling of air reference values. Additionally, 43% of institutions did not perform routine QA. Standardizing phantom geometry, air CT number handling and QA protocols—particularly using half-phantom calibration—may improve CT–MD table consistency and dose accuracy in ART.

This study quantitatively evaluated the impact of differences in computed tomography (CT) numbers and elemental compositions between commercially available brain-tissue-equivalent density plugs (BDPs) and actual brain tissue on dose calculations in a radiation therapy treatment planning system (RTPS). The mass density and elemental composition of BDP were analyzed using elemental analysis and X-ray fluorescence spectroscopy. The CT numbers of the BDP and actual brain tissue were measured and compared, with effective atomic numbers (EANs) calculated based on compositional analysis and the International Commission on Radiological Protection Publication 110 data for brain tissues. The theoretical CT numbers were derived using the stoichiometric CT number calibration (SCC) method. The dose calculations were performed using the modified CT number-to-relative electron density (RED) and mass density (MD) conversion tables in Eclipse v16.1, employing AAA and Acuros XB algorithms, employing the physical material table in AcurosXB_13.5. The dose metrics D_2%, D_50%, and D_98% were evaluated. Significant differences in elemental composition were found, particularly in carbon (73.26% in BDP vs. 14.3% in brain tissue) and oxygen (12.52% in BDP vs. 71.3% in brain tissue). The EANs were 6.6 for BDP and 7.4 for brain tissue. The mean CT numbers were 23.30 HU for the BDP and 37.30 HU for brain tissue, a 14 HU discrepancy. Nevertheless, dose calculation deviations were minimal, typically within ± 0.2%, with a maximum discrepancy of 0.6% for D_98%. Although CT numbers and elemental compositions exhibited notable differences, their impact on dose calculations in the evaluated RTPS algorithms was negligible.

Electrometers are important devices that are part of the standard dosimetry system. Therefore, we evaluated the variation of electrometer calibration coefficients (k_elec) over 1 year in this study. We investigated two types of electrometers: a rate mode and an integrate mode. Each electrometer was connected to a charge generator, a constant charge was applied, and k_elec was determined by measuring the current. The current measurements were repeated once a month. For electrometers with multiple ranges, measurements were taken at low and medium ranges. Almost all k_elec measurements agreed within 0.2% of the initial measurements. However, the low range of the electrometer with an integrate mode showed seasonal variation, with a variation greater than 0.2%. This study shows that electrometers may exhibit errors that cannot be detected through annual inspections. The importance of quality assurance using a charge generator at one’s own institution was demonstrated.

Background and purpose: The standard dosimetry system of medical accelerators in radiotherapy consists of an ionization chamber, an electrometer, and cables. Guidance for TG‐51 reference dosimetry reported that the electrometer correction factor (P_elec) should be checked every few years. Therefore, continuous Pelec measurements have not been reported. The purpose of this study is to measure the Pelec with a charge generator at our institution and to evaluate variations over time. The measurements are compared with calibration data given by an Accredited Dosimetry Calibration Laboratory (ADCL).Materials and methods: We used four reference‐class electrometers: RT521R (RTQM system/EMF Japan), Model 35040 (FLUKE), RAMTEC Duo (Toyo medic), and UNIDOS‐E (PTW). Each electrometer was connected to the charge generator, and the required charge was applied. The measurement points used were the same as those used for calibration by the ADCL. From the measured charges at each point, the P_elec was obtained from the slope of the linear regression function. The measurements were repeated over a 3‐month period to evaluate variations over time for each electrometer. Additionally, error budgets for the P_elec measurements were estimated, and the overall uncertainty was determined.Results: The measured P_elec values were 1.0000, 0.9995, 1.0009/0.9999, and 0.9995/0.9998 for RT521R, Model 35040, the low/medium (L/M) ranges of RAMTEC Duo, and the L/M ranges of UNIDOS‐E, respectively. The measured P_elec values agreed within 0.1% with those given by the ADCL. We found a small drift in the measurements for one electrometer. Additionally, the uncertainty considered was 0.26% for k = 2 (k, coverage factor).Conclusion: In this study, stable P_elec values were obtained for four electrometers using a charge generator over a three‐month period. The measured P_elec values were within the overall uncertainty stated in the electrometer guidelines. However, performing periodic measurements for the P_elec was able to help in detecting small errors.

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.

This study aims to evaluate the effect of different air computed tomography (CT) numbers of the image value density table (IVDT) on the retrospective dose calculation of head‐and‐neck (HN) radiotherapy using TomoTherapy megavoltage CT (MVCT) images. The CT numbers of the inside and outside air and each tissue‐equivalent plug of the “Cheese” phantom were obtained from TomoTherapy MVCT. Two IVDTs with different air CT numbers were created and applied to MVCT images of the HN anthropomorphic phantom and recalculated by Planned Adaptive to verify dose distribution. We defined the recalculation dose with MVCT images using both inside and outside air of the IVDT as and , respectively. Treatment planning doses calculated on kVCT images were compared with those calculated on MVCT images using two different IVDT tables, namely, and . The difference between average MVCT numbers ±1 standard deviation on inside and outside air of the calibration phantom was 65 ± 36 HU. This difference in MVCT number of air exceeded the recommendation lung tolerance for dose calculation error of 2%. The dose differences between the planning target volume (PTV): D_98%, D_50%, D_2% and the organ at risk (OAR): D_max, D_mean recalculated by and using MVCT images were a maximum of 0.7% and 1.2%, respectively. Recalculated doses to the PTV and OAR with MVCT showed that was 0.5%–0.7% closer to the kVCT treatment planning dose than . This study showed that was more accurate than in recalculating the dose HN cases of MVCT using TomoTherapy.