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AIM AND BACKGROUND: IGRT based on bone matching may produce a large target positioning error in terms of the reproducibility of expiration breath-holding on SBRT for liver cancer. We evaluated the intrafractional and interfractional errors using the diaphragm position at the end of expiration by utilising Abches and analysed the factor of the interfractional error. MATERIALS AND METHODS: Intrafractional and interfractional errors were measured using a couple of frontal kV images, planning computed tomography (pCT) and daily cone-beam computed tomography (CBCT). Moreover, max-min diaphragm position within daily CBCT image sets with respect to pCT and the maximum value of diaphragm position difference between CBCT and pCT were calculated. RESULTS: The mean ± SD (standard deviation) of the intra-fraction diaphragm position variation in the frontal kV images was 1.0 ± 0.7 mm in the C-C direction. The inter-fractional diaphragm changes were 0.4 ± 4.6 mm in the C-C direction, 1.4 ± 2.2 mm in the A-P direction, and -0.6 ± 1.8 mm in the L-R direction. There were no significant differences between the maximum value of the max-min diaphragm position within daily CBCT image sets with respect to pCT and the maximum value of diaphragm position difference between CBCT and pCT. CONCLUSIONS: Residual intrafractional variability of diaphragm position is minimal, but large interfractional diaphragm changes were observed. There was a small effect in the patient condition difference between pCT and CBCT. The impact of the difference in daily breath-holds on the interfractional diaphragm position was large or the difference in daily breath-holding heavily influenced the interfractional diaphragm change.
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BACKGROUND: An important issue in indirect dynamic tumor tracking with the Vero4DRT system is the accuracy of the model predictions of the internal target position based on surrogate infrared (IR) marker measurement. We investigated the predictive uncertainty of 4D modeling using an external IR marker, focusing on the effect of the target and surrogate amplitudes and periods. METHODS: A programmable respiratory motion table was used to simulate breathing induced organ motion. Sinusoidal motion sequences were produced by a dynamic phantom with different amplitudes and periods. To investigate the 4D modeling error, the following amplitudes (peak-to-peak: 10-40 mm) and periods (2-8 s) were considered. The 95th percentile 4D modeling error (4D-E95%) between the detected and predicted target position (µ + 2SD) was calculated to investigate the 4D modeling error. RESULTS: 4D-E95% was linearly related to the target motion amplitude with a coefficient of determination R2 = 0.99 and ranged from 0.21 to 0.88 mm. The 4D modeling error ranged from 1.49 to 0.14 mm and gradually decreased with increasing target motion period. CONCLUSIONS: We analyzed the predictive error in 4D modeling and the error due to the amplitude and period of target. 4D modeling error substantially increased with increasing amplitude and decreasing period of the target motion.
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We proposed a simple visual method for evaluating the dynamic tumor tracking (DTT) accuracy of a gimbal mechanism using a light field. A single photon beam was set with a field size of 30 × 30 mm2 at a gantry angle of 90°. The center of a cube phantom was set up at the isocenter of a motion table, and 4D modeling was performed based on the tumor and infrared (IR) marker motion. After 4D modeling, the cube phantom was replaced with a sheet of paper, which was placed perpen-dicularly, and a light field was projected on the sheet of paper. The light field was recorded using a web camera in a treatment room that was as dark as possible. Calculated images from each image obtained using the camera were summed to compose a total summation image. Sinusoidal motion sequences were produced by moving the phantom with a fixed amplitude of 20 mm and different breathing periods of 2, 4, 6, and 8 s. The light field was projected on the sheet of paper under three conditions: with the moving phantom and DTT based on the motion of the phantom, with the moving phantom and non-DTT, and with a stationary phantom for comparison. The values of tracking errors using the light field were 1.12 ± 0.72, 0.31 ± 0.19, 0.27 ± 0.12, and 0.15 ± 0.09 mm for breathing periods of 2, 4, 6, and 8s, respectively. The tracking accuracy showed dependence on the breath-ing period. We proposed a simple quality assurance (QA) process for the tracking accuracy of a gimbal mechanism system using a light field and web camera. Our method can assess the tracking accuracy using a light field without irradiation and clearly visualize distributions like film dosimetry.
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Neoplasias/radioterapia , Aceleradores de Partículas/instrumentação , Imagens de Fantasmas , Garantia da Qualidade dos Cuidados de Saúde/normas , Radioterapia de Intensidade Modulada/instrumentação , Radioterapia de Intensidade Modulada/normas , Humanos , Movimento , Planejamento da Radioterapia Assistida por Computador/métodos , Radioterapia Guiada por Imagem/métodosRESUMO
AIM: In high-precision radiation therapy, kilovoltage cone-beam computed tomography plays an important role in verifying the position of patient and localization of the target. However, the exposure dose is a problem with kilovoltage cone-beam computed tomography. Flux overlap region increases the patient dose around the center when the scan is performed in a full-scan mode. We assessed the influence of flux overlap region in a full-scan mode to understand the relationship between dose and image quality and investigated methods to achieve a dose reduction. METHOD: A Catphan phantom was scanned using various flux overlap region patterns in the pelvis on a full-scan mode. We used an intensity-modulated radiation therapy phantom for measuring the central dose. DoseLab was used to perform image analysis and to evaluate the linearity of the computed tomography values, uniformity, high-contrast resolution, and contrast-to-noise ratio. RESULTS: The Hounsfield unit value varied by ±40 Hounsfield unit of the acceptance value for the X1 field size of 3.5 cm. However, there were no differences in high-contrast resolution and contrast-to-noise ratio among different scan patterns. The absorbed dose decreased by 7% at maximum for the case within the tolerance value. CONCLUSION: Dose reduction is possible by reducing the overlap region after calibration and by performing computed tomography in the appropriate overlap region.
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PURPOSE: Resilience engineering is the ability of a system to adjust its own functions and maintain the required behavior in the face of changes and disturbances, and resilience potential is a necessary requirement. We aimed to clarify the relationship between resilience potential and error prevention cases. METHOD: Based on the error cases reported in our department, we aggregated the relationship with resilience potential for each radiation treatment process. RESULT: As a result of tabulating the relationship, we were able to recognize and prevent errors by taking preventive measures from past cases. On the other hand, in cases that slipped through the check mechanism, errors were discovered because of a sense of discomfort in unusual situations, and some error cases could be prevented by increasing the resilience potential. CONCLUSION: This study found that preparation, observation, coping, and utilization of past experiences are related to resilience potential in preventive cases.
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Resiliência Psicológica , Capacidades de Enfrentamento , Inquéritos e QuestionáriosRESUMO
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.
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Tomografia Computadorizada por Raios X , Água , Calibragem , Imagens de Fantasmas , Planejamento da Radioterapia Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodosRESUMO
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.
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Imagens de Fantasmas , Fótons , Tomografia Computadorizada por Raios X/instrumentação , Calibragem , Projetos PilotoRESUMO
The characteristics of a flattening filter-free (FFF) beam are different from those of a beam with a flattening filter. For small-field dosimetry, the beam data needed by the radiation treatment planning system (RTPS) includes the percent depth dose (PDD), off-center ratio (OCR), and output factor (OPF) for field sizes down to 3 × 3 cm2 to calculate the beam model. The purpose of this study was to evaluate the accuracy of calculations for the FFF beam by the Eclipse™ treatment planning system for field sizes smaller than 3 × 3 cm2 (2 × 2 and 1 × 1 cm2). We used 6X and 10X FFF beams by the Varian TrueBeam™ to produce. The AAA and AXB algorithms of the Eclipse were used to compare the Monte Carlo (MC) calculation and the measurements from three dosimeters, a diode detector, a PinPoint dosimeter, and EBT3 film. The PDD curves and the penumbra width in the OCR calculated by the Eclipse, measured data, and those from the MC calculations were in good agreement to within ±2.8 % and ±0.6 mm, respectively. However, the difference in the OPF values between AAA and AXB for a field size of 1 × 1 cm2 was 5.3 % for the 6X FFF beam and 7.6 % for the 10X FFF beam. Therefore, we have to confirm the small field data that is included for the RTPS commission procedures.
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Modelos Teóricos , Radioterapia de Intensidade Modulada/métodos , Algoritmos , Planejamento da Radioterapia Assistida por ComputadorRESUMO
PURPOSE: In this study, we demonstrate the feasibility of using split-arcs in volumetric modulated arc therapy (VMAT), tailored for expiratory breath-hold in stereotactic body radiation therapy (SBRT) for liver tumors. We compare it with three-dimensional conformal radiation therapy (3D-CRT) and continuous-VMAT, for ten randomly selected hepatocellular carcinoma cases. METHODS: Four coplanar and four non-coplanar beams were used for the 3D-CRT plans. A pair of partial arcs, chosen using a back-and-forth rotating motion, were used for the continuous-VMAT plans. Split-VMAT plans were created using the same arc range as the continuous-VMAT plans, but were split into smaller arcs (<90°), to simulate an expiratory breath hold of <15s. The dose distribution, treatment delivery efficiency, and patient specific quality assurance of the split-VMAT, were verified to ensure that the outcomes were equal, or better than, those for 3D-CRT and continuous-VMAT. The prescription was 48Gy/4 fractions, to 95% of the PTV, using 10MV FFF X-ray beams. RESULTS: The mean dose of the liver-GTV was lower in the split-VMAT compared with that of 3D-CRT. Split-VMAT was more conformal compared with 3D-CRT. The total treatment time for split-VMAT was shorter than that of 3D-CRT. Similar dosimetric indices were observed for split-VMAT and continuous-VMAT. All VMAT plans passed the gamma acceptance test. CONCLUSIONS: Split-VMAT designed to accommodate an expiratory breath-hold period of 15s is a feasible and efficient use of liver SBRT, because it does not compromise the quality of the plan, when compared with 3D-CRT or continuous-VMAT.
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Carcinoma Hepatocelular/radioterapia , Radiocirurgia , Planejamento da Radioterapia Assistida por Computador , Radioterapia de Intensidade Modulada , Suspensão da Respiração , Humanos , Dosagem RadioterapêuticaRESUMO
PURPOSE: Image-guided radiotherapy (IGRT) based on bone matching can produce large target-positioning errors because of expiration breath-hold reproducibility during stereotactic body radiation therapy (SBRT) for liver tumors. Therefore, the feasibility of diaphragm-based 3D image matching between planning computed tomography (CT) and pretreatment cone-beam CT was investigated. METHODS: In 59 liver SBRT cases, Lipiodol uptake after transarterial chemoembolization was defined as a tumor marker. Further, the relative isocenter coordinate that was obtained by Lipiodol matching was defined as the reference coordinate. The distance between the relative isocenter coordinate and reference coordinate, which was obtained from diaphragm matching and bone matching techniques, was defined as the target positioning error. Furthermore, the target positioning error between liver matching and Lipiodol matching was evaluated. RESULTS: The positioning errors in all directions by the diaphragm matching were significantly smaller than those obtained by using by the bone matching technique (p < 0.05). Further, the positioning errors in the A-P and C-C directions that were obtained by using liver matching were significantly smaller than those obtained by using bone matching (p < 0.05). The estimated PTV margins calculated by the formula proposed by van Herk for diaphragm matching, liver matching, and bone matching were 5.0 mm, 5.0 mm, and 11.6 mm in the C-C direction; 3.6 mm, 2.4 mm, and 6.9 mm in the A-P direction; and 2.6 mm, 4.1 mm, and 4.6 mm in the L-R direction, respectively. CONCLUSIONS: Diaphragm matching-based IGRT may be an alternative image matching technique for determining liver tumor positions in patients.