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Purpose Existing phantom-less quality assurance (QA) platforms does not provide patient-specific QA for helical tomotherapy (HT). A new system, called TomoEQA, is presented to facilitate this using the leaf open time (LOT) of a binary multi-leaf collimator, as measured by an exit detector. Methods TomoEQA was designed to provide measurement-based LOTs based on detector data and to generate a new digital imaging and communication in medicine (DICOM) dataset that includes the measured LOTs for use by secondary check platforms. To evaluate the system, 20 patient-specific QAs were performed using the program in Mobius3D software, and the results were compared to conventional phantom-based QA results. Results From our assessment, most of the differences between the planned and measured (or calculated) data, excluding one case, were within the acceptance criteria comparing with those of conventional QA. Regarding the gamma analysis, all results considered in this study were within the acceptance criteria. In addition, the developed system was performed for a failed case and showed approximately the same trends as the conventional approach. Conclusions TomoEQA could perform patient-specific QAs of HT using Mobius3D and provide reliable patient-specific QAs results by evaluating point dose errors and 3D gamma passing rates. TomoEQA could also distinguish whether an intensity-modulated radiation therapy plan failed or not.

Purpose To provide practical guidelines for Mobius3D commissioning based on experiences of commissioning/clinical implementation of Mobius3D and MobiusFX as patient-specific quality assurance tools on multiple linear accelerators. Methods The vendor-suggested Mobius3D commissioning procedures, including beam model adjustment and dosimetric leaf gap (DLG) optimization, were performed for 6 MV X-ray beams of six Elekta linear accelerators. For the beam model adjustment, beam data, such as the percentage depth dose, off-axis ratio (OAR), and output factor (OF), were measured using a water phantom and compared to the vendor-provided reference values. DLG optimization was performed to determine an optimal DLG correction factor to minimize the mean difference between Mobius3D-calculated and measured doses for multiple volumetric modulated arc therapy (VMAT) plans. Small-field VMAT plans, in which Mobius3D has dose calculate uncertainties, were initially included in the DLG optimization, but excluded later. Results The measured beam data were consistent across the six linear accelerators. Relatively large differences between the reference and measured values were observed for the OAR at large off-axis distances (>5 cm) and for the OF for small fields ( Conclusions A reasonable agreement was found between the vendor-provided reference and measured beam models. DLG optimization results were dependent on the selection of the VMAT plans, requiring careful attention to the known dose calculation uncertainties of Mobius3D when determining a DLG correction factor.

Purpose To perform a detailed evaluation of dose calculation accuracy and clinical feasibility of Mobius3D. Of particular importance, multileaf collimator (MLC) modeling accuracy in the Mobius3D dose calculation algorithm was investigated. Methods Mobius3D was fully commissioned by following the vendor-suggested procedures, including dosimetric leaf gap (DLG) optimization. The DLG optimization determined an optimal DLG correction factor which minimized the average difference between calculated and measured doses for 13 patient volumetric-modulated arc therapy (VMAT) plans. Two sets of step-and-shoot plans were created to examine MLC and off-axis open fields modeling accuracy of the Mobius3D dose calculation algorithm: MLC test set and off-axis open field test set. The test plans were delivered to MapCHECK for the MLC tests and an ionization chamber for the off-axis open field test, and these measured doses were compared to Mobius3D-calculated doses. Results The mean difference between the calculated and measured doses across the 13 VMAT plans was 0.6% with an optimal DLG correction factor of 1.0. The mean percentage of pixels passing gamma from a 3%/1 mm gamma analysis for the MLC test set was 43.5% across the MLC tests. For the off-axis open field tests, the Mobius3D-calculated dose for 1.5 cm square field was −4.6% lower than the chamber-measured dose. Conclusions It was demonstrated that Mobius3D has dose calculation uncertainties for small fields and MLC tongue-and-groove design is not adequately taken into consideration in Mobius3D. Careful consideration of DLG correction factor, which affects the resulting dose distributions, is required when commissioning Mobius3D for patient-specific QA.

Purpose In this study, we developed a simple but useful computer program, called TomoMQA, to offer an automated quality assurance for mega‐voltage computed tomography (MVCT) images generated via helical tomotherapy. Methods TomoMQA is written in MATLAB and contains three steps for analysis: (a) open the DICOM dataset folder generated via helical tomotherapy (i.e., TomoTherapy® and Radixact™), (b) call the baseline data for the consistency test and click the “Analysis” button (or click the “Analysis” button without the baseline data and export the results as the baseline data), and (c) print an analyzed report. The overall procedure for the QA analysis included in TomoMQA is referred from the TG‐148 recommendation. Here, the tolerances for MVCT QA were implemented from TG‐148 recommended values as default; however, it can be modified by a user manually. Results To test the performance of the TomoMQA program, 15 MVCTs were prepared from five helical tomotherapy machines (1 of TomoTherapy® HD, 2 of TomoTherapy® HDA, and 2 of Radixact™) in 3 months and the QA procedures were performed using TomoMQA. From our results, the evaluation revealed that the developed program can successfully perform the MVCT QA analysis irrespective of the type of helical tomotherapy equipment. Conclusion We successfully developed a new automated analysis program for MVCT QA of a helical tomotherapy platform, called TomoMQA. The developed program will be made freely downloadable from the TomoMQA‐dedicated website.

In this study, the delivery quality assurance (DQA) results of commercially available dosimetric systems (ionization chamber and EBT film, MapCHECK, ArcCHECK, and dosimetry check (DC) software) for helical tomotherapy (HT) were compared, and the feasibility of performing pretreatment using MapCHECK, ArcCHECK, and DC for HT, instead of ionization chambers and EBT films, was assessed. Sixty-five HT-treated patients were considered. Point dose differences, dose profiles, and gamma passing rates were used to evaluate the agreement between the calculated and the measured data, and the outcomes of the four DQA devices were compared in various clinical cases. The calculated and the measured point doses were within ±5% of each other. In terms of the root-mean-square error (RMSE), the point dose differences were within 2.9 for the four tested devices in all of the studied cases. Gamma analysis was performed based on the 3%/3 mm and 2%/2 mm passing rate criteria. In terms of the average RMSE, the gamma passing rates of the four tested DQA devices were within 2.85 (3%/3 mm) and 7.30 (2%/2 mm). These DQA systems could be used interchangeably for routine DQA pretreatment in HT cases.

Radiation pneumonitis (RP) is a major radiation-induced lung injury in patients with lung cancer. When an extremely high risk of severe RP is predicted, it is a critical issue that severely affects radiation dose and treatment planning. It is essential to assess which prognostic factor affects the occurrence of RP before initiating radiation treatment. In this study, we aimed to identify the variable importance (VI) of prognostic factors related to RP by using an artificial neural network (ANN) containing complex association between several prognostic factors. We reviewed 110 cases in patients with lung cancer who received radiation therapy (RT) from August 2000 to December 2018. The multi-layer perceptron algorithm, which is a back-propagation ANN algorithm, was implemented by SPSS Modeler (verl3.1, IBM SPSS Inc., Chicago, IL). The fifteen input variables were set, and the target variable was the occurrence of RP. The VI, which indicates the effect of each prognostic factor on the occurrence of RP, was analyzed by the variance-based method. To evaluate the VI of the ANN, we qualitatively compared the VI of the ANN with the odds ratios (OR) obtained from previously published literature. Patients who had an RP grade >2 comprised 13.6%. The accuracy of the ANN model was 76.92% and the and the area under the curve (AUC) was 0.774. From the results of the VI from the ANN, mean lung dose (MLD) had the highest VI among the prognostic factors at 15.96%. The OR of interstitial lung disease (ILD) was the highest at 25.70. While the VI of the ANN includes complex associations of the prognostic factors, ORs include independent associations between exposure and outcome. This preliminary study is meaningful as it proposes a method to quantify the VI of prognostic factors related to patient outcome using even simple ML algorithm. By further acquiring the more refined big data, optimizing the ML model, and performing clinical validation, the accurate VI can be adopted for personalized RT planning.

Radiation toxicity grades must be reviewed based on existing knowledge-based clinical evidence or be assessed by referencing the clinical research literature to minimize radiation toxicity associated with radiotherapy. The aim of this study was to develop a radiation toxicity prediction system using metarule-guided mining of the clinical research literature to predict radiation pneumonitis and esophagitis in lung cancer patients. A semantic pattern database was built using 100 clinical research articles. Semantic patterns of prognostic factors and toxicity grades were extracted by metarule-guided mining. Feature analysis and correlation investigation of prognostic factors and toxicity grades were performed by using dendrogram and heatmap. A web-based user interface for the prediction system was designed. Patient prognostic factors were used in this prediction system to predict toxicity grade results. Radiation toxicity grades for patients with radiation pneumonitis and esophagitis were calculated through our prediction system. Age and chemotherapy were prognostic factors as were toxicity grades 1–3 and 5 based on the metarule-guided mining system. The odds ratios had similar trends to those in the existing meta-analysis literature. The radiation toxicity prediction system that we developed can potentially be used as a clinical decision support system for patient-specific radiation treatment after weighting of prognostic factors, performing a correlation analysis, and performing a validity evaluation.

We evaluated the feasibility of a magnetic resonance (MR) tumor model and the accuracy of 3D dosimetry for evaluating brain stereotactic radiotherapy (SRT). We first validated the stability of the BANG3 polymer gel dosimeter and performed a pre-clinical verification of this device for brain SRT. Gel-filled vials were irradiated with 6-MV beams to generate a dose calibration curve in relation to the R2 (1/T2) values on 9.4 T MR images. The dose linearity, inter-reproducibility and intra-reproducibility, and dose-rate dependence of the gel dosimeters were evaluated. We also developed an image tumor model for pre-clinical testing. A calibration kit for the gel dosimeter and two spherical tumor representations were fabricated by using 3D printing. Two planning target volumes (PTVs) were contoured onto the MR images of the tumor models comprised of dosimetric gel. To evaluate the geometric and dosimetric accuracy, we created a treatment plan such that the D95s for PTV1 and shifted PTV2 were more than the prescribed dose. The shifted PTV2 was produced by an intentional shift of 5 mm from the true target position. A 2 arc VMAT plan was created to deliver 35 Gy in 5 fractions. After irradiation, calibration vials and tumor model phantoms were scanned by using 9.4 T MRI, and the acquired images were then analyzed using ImageJ and DCMTK software libraries. Scanned MRI images of the tumor models were imported into a treatment planning system and registered to CT images. We also compared the agreement of results between the planned and the measured data in 1D (ion chamber), 2D (2D film), and 3D (gel dosimeter). The best dose linearity achieved was 0.99 (R2) at 180 TE (ms) under which conditions the reproducibility and dose rate dependence were less than 2.2% and 3.5%, respectively. The mean dose differences between the treatment plan and the ion-chamber results were 3.3%, 0.4%, and 4.5%, respectively, for PTV1 and 2 and for the shifted PTV. Moreover, the point dose differences between the treatment plan and the gel results were 0.9%, 2.6% and 3.7%, respectively, for PTV1 and 2 and for the shifted PTV. The gamma passing rates with 3%/3 mm criteria were greater than 99% for all plans. The isodose distributions and profiles showed good qualitative agreement between the gel dosimeter, EBT film and RTP data for all PTVs. Our present study results, thus, indicate that an MR tumor model can effectively evaluate the geometric and dosimetric accuracy of brain SRT. Image tumor models using gel dosimeters are, therefore, useful for validating the 3D dose distributions for patient-specific whole treatment processes. We are planning to improve this image tumor model by facilitating respiratory mobility and utilizing more complex tumor shapes for liver stereotactic body radiotherapy (SBRT) cases.

Purpose: The European Society of Radiation & Oncology and Advisory Committee on Radiation Oncology Practice (ESTRO-ACROP) presented new guidelines for clinical target volume (CTV) delineation in post-mastectomy radiation therapy (PMRT) after implant-based immediate breast reconstruction (IBR-i). This study evaluated the dosimetric characteristics, dosimetric accuracy, and delivery accuracy of these guidelines in volumetric modulated arc therapy (VMAT).Methods and Materials: This retrospective study included 15 patients with left breast cancer who underwent mastectomy with tissue expander placement followed by PMRT. An experienced radiation oncologist delineated the CTV twice on the same image datasets based on the ESTRO-ACROP (EA-TVD) and conventional target volume delineation (C-TVD) guidelines. All VMAT plans, which used a double partial arc, were generated using six MV photons. Clinically relevant dose-volume parameters for organs at risk were compared. Dosimetric accuracy of the treatment plans and delivery accuracy were assessed.Results: Target volume of EA-TVD was significantly smaller than that of C-TVD. Although no statistically significant difference was noted in the target coverage between the two VMAT plans, EA-TVD VMAT significantly reduced the mean heart dose (3.99 ± 1.02 vs. 5.84 ± 1.78 Gy, p = 0.000), the maximum left anterior descending coronary artery (LAD) dose (9.43 ± 3.04 vs. 13.97 ± 6.04 Gy, p = 0.026), and the mean LAD dose (4.52 ± 1.31 vs. 6.35 ± 2.79 Gy, p = 0.028) compared with C-TVD VMAT. No significant difference was observed with respect to the total monitor units, plan complexity, and delivery quality assurance.Conclusions: This is the first study to show significant dose reduction for the normal heart and LAD tissue offered by the EA-TVD, while maintaining dosimetric and delivery accuracy, in PMRT after IBR-i in VMAT for left-sided breast cancer patients.

Background This study investigated the effect of accumulated doses on radio-photoluminescence glass dosimeters (RPLGDs) from measurements involving mega-voltage photons. Methods Forty-five commercially available RPLGDs were irradiated to estimate their dose responses. Photon beams of 6, 10, and 15 MV were irradiated onto the RPLGDs inside a phantom, which were divided into five groups with different doses and energies. Groups 1 and 2 were irradiated at 1, 5, 10, 50, and 100 Gy in a sequential manner; Group 3 was irradiated 10 times with a dose of 10 Gy; and Groups 4 and 5 followed the same method as that of Group 3, but with doses of 50 Gy and 100 Gy, respectively. Each device was subjected to a measurement reading procedure each time irradiation. Results For the annealed Group 1, RPLGD exhibited a linearity response with variance within 5%. For the non-annealed Group 2, readings demonstrated hyperlinearity at 6 MV and 10 MV, and linearity at 15 MV. Following the 100 Gy irradiation, the readings for Group 2 were 118.7 ± 1.9%, 112.2 ± 2.7%, and 101.5 ± 2.3% at 6, 10, and 15 MV, respectively. For Groups 3, 4, and 5, the responsiveness of the RPLGDs gradually decreased as the number of repeated irradiations increased. The percentage readings for the 10th beam irradiation with respect to the readings for the primary beam irradiation were 84.6 ± 1.9%, 87.5 ± 2.4%, and 93.0 ± 3.0% at 6 MV, 10 MV, and 15 MV, respectively. Conclusions The non-annealed RPLGD response to dose was hyperlinear for the 6 MV and 10 MV photon beams but not for the 15 MV photon beam. Additionally, the annealed RPLGD exhibited a fading phenomenon when the measurement was repeated several times and demonstrated a relatively large fading effect at low energies than at high energies.

Purpose: This study assesses the dosimetric leaf gap (DLG) correction factor in Mobius3D commissioning affected by a couch top platform and calculates the optimal DLG value according to the point dose difference function. Methods: DLG optimizations were performed for 3 LINAC machines and a total of 30 patient VMAT plans (i.e., 10 plans per each LINAC). Point dose calculations were performed using an automatic dose calculation system in Mobius3D as well as Mobis3D calculation using an MVP-based QA plan with a carbon fiber couch top. Subsequently, the results were compared with measurement data. Results: The averaged point dose measured for the MVP with a couch top decreased by approximately 2% relative to that without the couch top. The average of the optimal DLG factors increased by 1.153 due to the couch top effect for a dose decrease of 2% at the measured point. Conclusions: Users should adjust the DLG correction factor using a specific phantom (including MVP) with a couch top. If the factor adjusted by using MVP automatic dose calculation system, the factor should be increased by approximately 1.153 per 2% dose difference considering user’s couch top effect.

The aim of this study was to derive a new plan-scoring index using normal tissue complication probabilities to verify different plans in the selection of personalized treatment. Plans for 12 patients treated with tomotherapy were used to compare scoring for ranking. Dosimetric and biological indexes were analyzed for the plans for a clearly distinguishable group (n = 7) and a similar group (n = 12), using treatment plan verification software that we developed. The quality factor (QF) of our support software for treatment decisions was consistent with the final treatment plan for the clearly distinguishable group (average QF = 1.202, 100% match rate, n = 7) and the similar group (average QF = 1.058, 33% match rate, n = 12). Therefore, we propose a normal tissue complication probability (NTCP) based on the plan scoring index for verification of different plans for personalized treatment-plan selection. Scoring using the new QF showed a 100% match rate (average NTCP QF = 1.0420). The NTCP-based new QF scoring method was adequate for obtaining biological verification quality and organ risk saving using the treatment-planning decision-support software we developed for prostate cancer.

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

PurposeThe aim of this study is to develop predictive models to predict organ at risk (OAR) complication level, classification of OAR dose-volume and combination of this function with our in-house developed treatment decision support system.Materials and methodsWe analysed the support vector machine and decision tree algorithm for predicting OAR complication level and toxicity in order to integrate this function into our in-house radiation treatment planning decision support system. A total of 12 TomoTherapyTM treatment plans for prostate cancer were established, and a hundred modelled plans were generated to analyse the toxicity prediction for bladder and rectum.ResultsThe toxicity prediction algorithm analysis showed 91·0% accuracy in the training process. A scatter plot for bladder and rectum was obtained by 100 modelled plans and classification result derived. OAR complication level was analysed and risk factor for 25% bladder and 50% rectum was detected by decision tree. Therefore, it was shown that complication prediction of patients using big data-based clinical information is possible.ConclusionWe verified the accuracy of the tested algorithm using prostate cancer cases. Side effects can be minimised by applying this predictive modelling algorithm with the planning decision support system for patient-specific radiotherapy planning.

The purpose of this study was to use various dosimetrical indices to determine the best intensitymodulated radiation therapy (IMRT) modality - for treating patients with prostate cancer. Ten patients with prostate cancer were included in this study. IMRT plans were designed to include different modalities, including the linac step and shoot, tomotherapy, RapidArc, and proton systems. Various dosimetrical indices, like the prescription isodose to target volume (PITV) ratio, conformity index (CI), homogeneity index (HI), target coverage index (TCI), modified dose homogeneity index (MHI), conformation number (CN), critical organ scoring index (COSI), and quality factor (QF), were determined to compare the different treatment plans. Biological indices, such as the generalized equivalent uniform dose (gEUD) based the tumor control probability (TCP), and the normal tissue complication probability (NTCP), were also calculated and used to compare the treatment plans. The RapidArc plan attained better PTV coverage, as evidenced by its superior PITV, CI, TCI, MHI, and CN values. Regarding organ at risks (OARs), proton therapy exhibited superior dose sparing for the rectum and the bowel in low dose volumes, whereas the tomotherapy and RapidArc plans achieved better dose sparing in high dose volumes. The QF scores showed no significant difference among these plans (p = 0.701). The average TCPs for prostate tumors in the RapidArc, linac and proton plans were higher than the average TCP for Tomotherapy (98.79%, 98.76%, and 98.75% vs. 98.70%, respectively). Regarding the rectum NTCP, RapidArc showed the most favorable result (0.09%) whereas linac resulted in the best bladder NTCP (0.08%).

Purpose This paper describes the hardware and software characteristics of a 3D optical scanner (P3DS) developed in-house. The P3DS consists of an LED light source, diffuse screen, step motor, CCD camera, and scanner management software with 3D reconstructed software. Materials and method We performed optical simulation, 2D and 3D reconstruction image testing, and pre-clinical testing for the P3DS. We developed the optical scanner with three key characteristics in mind. First, we developed a continuous scanning method to expand possible clinical applications. Second, we manufactured a collimator to improve image quality by reducing scattering from the light source. Third, we developed an optical scanner with changeable camera positioning to enable acquisition of optimal images according to the size of the gel dosimeter. Results We confirmed ray-tracing in P3DS with optic simulation and found that 2D projection and 3D reconstructed images were qualitatively similar to the phantom images. For pre-clinical tests, the dose distribution and profile showed good agreement among RTP, optical CT, and external beam radiotherapy film data for the axial and coronal views. The P3DS has shown that it can scan and reconstruct for evaluation of the gel dosimeter within 1 min. We confirmed that the P3DS system is a useful tool for the measurement of 3D dose distributions for 3D radiation therapy QA. Further experiments are needed to investigate quantitative analysis for 3D dose distribution.

We compare the dosimetrical differences between plans generated for helical tomotherapy by using the 2D or 3D the margining technique for the treatment of prostate cancer. Ten prostate cancer patients were included in this study. For 2D plans, the planning target volume (PTV) was created by adding 5 mm (lateral/anterior-posterior) to the clinical target volume (CTV). For 3D plans, a 5-mm margin was added not only lateral/anterior-posterior, but also superior-inferior, to the CTV. Various dosimetrical indices, including the prescription isodose to target volume (PITV) ratio, conformity index (CI), homogeneity index (HI), target coverage index (TCI), modified dose homogeneity index (MHI), conformation number (CN), critical organ scoring index (COSI), and quality factor (QF) were determined to compare the different treatment plans. Differences between the 2D and the 3D PTV indices were not significant except for the CI (p = 0.023). 3D margin plans (11195 MUs) resulted in higher (13.0%) monitor units than 2D margin plans (9728 MUs). There were no significant differences in any organs at risk (OARs) between the 2D and the 3D plans. Overall, the average dose for the 2D plan was slightly lower than that for the 3D plan dose. Compared to the 2D plan, the 3D plan increased the average treatment time by 1.5 minutes; however, this difference was not statistically significant (p = 0.082). We confirmed that the 2D and the 3D margin plans were not significantly different with regard to various dosimetric indices such as the PITV, CI, and HI for PTV and the OARs with tomotherapy.

We present preliminary results for a 3-dimensional dose evaluation software system ( P DRESS, patient-specific 3-dimensional dose real evaluation system). Scanned computed tomography (CT) images obtained by using dosimetry were transferred to the radiation treatment planning system (ECLIPSE, VARIAN, Palo Alto, CA) where the intensity modulated radiation therapy (IMRT) nasopharynx plan was designed. We used a 10 MV photon beam (CLiX, VARIAN, Palo Alto, CA) to deliver the nasopharynx treatment plan. After irradiation, the TENOMAG dosimeter was scanned using a VISTA™ scanner. The scanned data were reconstructed using VistaRecon software to obtain a 3D dose distribution of the optical density. An optical-CT scanner was used to readout the dose distribution in the gel dosimeter. Moreover, we developed the P DRESS by using Flatform, which were developed by our group, to display the 3D dose distribution by loading the DICOM RT data which are exported from the radiotherapy treatment plan (RTP) and the optical-CT reconstructed VFF file, into the independent P DRESS with an ioniz ation chamber and EBT film was used to compare the dose distribution calculated from the RTP with that measured by using a gel dosimeter. The agreement between the normalized EBT, the gel dosimeter and RTP data was evaluated using both qualitative and quantitative methods, such as the isodose distribution, dose difference, point value, and profile. The profiles showed good agreement between the RTP data and the gel dosimeter data, and the precision of the dose distribution was within ±3%. The results from this study showed significantly discrepancies between the dose distribution calculated from the treatment plan and the dose distribution measured by a TENOMAG gel and by scanning with an optical CT scanner. The 3D dose evaluation software system ( P DRESS, patient specific dose real evaluation system), which were developed in this study evaluates the accuracies of the three-dimensional dose distributions. Further applications of the system utility are expected to result from future studies.

In the research, we evaluated the use of leuco crystal violet (LCV) gel as a dosimeter for therapeutic radiation by investigating its optical characteristics at various component concentrations. We also investigated the aging effect of the LCV gel at different beam energies, doserates, and dosing times to evaluate the LCV’s applicability to radiation therapy. We confirmed that the optimal optical wavelength of the LCV gel dosimeter was 600 nm. The dose sensitivity increased with increasing concentration of LCV; however, the optimal concentration was 1 mM LCV because the transparency of the gel dosimeter is important for use in optical CT scanners. However, the dose sensitivity decreased with increasing concentration of trichloroacetic acid (TAA). Moreover, the transparency of LCV rapidly decreased because of the generation of a white precipitate at TAA concentrations below 25 mM. Thus, an optimal TAA concentration of 30 mM was used in this study. Triton X-100 (8 mM) was identified as the optimal reagent for determining the optimum gel transparency and dose sensitivity. Thus, we present an LCV gel dosimeter composed of 4% gelatin by mass, 1 mM LCV, 30 mM TAA, and 8-mM Triton X-100 for use with an optical CT scanner. We showed good dose linearity up to 30 Gy. There was a little doserate dependency at a beam energy of 6 MV while the doserate dependence was more than 4.2% at a beam energy of 10 MV. To evaluate the energy dependence of the LCV gel dosimeter, we irradiated it at 20 Gy by using 6 MV and 10 MV beams. At the high doserate, the difference in the dose energy dependence was relatively small at approximately 1%, but the difference increased to 4.6% at the low doserate. With respect to the radiation absorbance at a photon energy of 6 MV, the absorbance at an electron energy of 6 MeV decreased by 5.4%, and the absorbances at 9, 12, and 15 MeV increased by 3, 18.7, and 12.2%, respectively. Furthermore, the aging effect was larger in the low-dose group then in the high-dose group. Moreover, we observed that the absorbance between 24 and 48 h after irradiation increased by approximately 5% at 5 Gy. For gel groups tested at high doses, the aging effect was reduced by approximately 1%.

This study demonstrates the feasibility of the proposed intensity-modulated radiotherapy (IMRT) techniques for minimizing the dose to the lungs and organs at risk (OARs) for variations in the number of beams, the orientations of the beams, the virtual organ delineation (VOD) position, the VOD size and the dose constraints in order to optimize the treatment plan for lung cancer. We used 5, 7, 9 and 14 equiangularly-spaced beams and 7 and 9 non-equiangularly-spaced beams. We measured the volume of the lungs receiving at least 20 Gy and 25 Gy (V20 and V25) for variations in the orientations of the beams, the VOD position, and the size of the tumor and the contra-lateral lung. For the tumor and the contra-lateral lung, the V20 and the V25 values of 14 equiangularlyspaced ports were slightly lower than those of other equiangularly-spaced beam orientations. For non-equiangularly-spaced beam orientations, the lowest V20 and V25 values in the tumor and the contral-lateral lung were recorded in ports 7, and 9, respectively. For tumors of the lung, the average values of 7 non-equiangularly-spaced ports were lower than those for 14 equiangularly-spaced ports.

We compared the basic characteristics of two commercially-available scattering gel (BANGkit™) and non-scattering gel (PRESAGE™) dosimeters with a spectrophotometer to investigate each device’s dosimetric properties. The two types of gel dosimeters were spectrophotometrically analyzed. For each gel dosimeter, the absorbance, dose linearity, reproducibility, dose rate dependency, and oxygen effect were evaluated at various wavelengths and doses. The best dose linearities of the BANGkit™ and the PRESAGE™ gel dosimeters gave R2 values of 0.97 and 0.98 at wavelengths of 485 nm and 600 nm, respectively, over the range of doses. The BANGkit™ gel showed no peak sensitivity within the studied range of wavelengths whereas the PRESAGE™ gel demonstrated peak sensitivity at a wavelength of 630 nm. The reproducibilities and the dose-rate dependences of the two gel dosimeters were within the range of ± 2% and ± 3%, respectively. We have shown that the peak sensitivities of the two gel dosimeters were significantly different; the BANGkit™ gel showed no peak sensitivity within the studied range of wavelengths whereas the PRESAGE™ gel demonstrated a peak sensitivity at a wavelength of 630 nm. We have confirmed that the radiochromic gel dosimeter was appropriate for use with a CCD-based optical CT scanner.

The purpose of this study was to determine the optimal wavelength for a polymer-gel dosimeter previously developed by our research groups; this was done through a spectrophotometric characterization of its dosimetric properties. A gel sample was irradiated with a 6-MV photon beam from a linear accelerator, and its response was spectrophotometrically analyzed. The absorbance, dose linearity, reproducibility, and dose-rate dependence of the dosimeter were evaluated at various wavelengths and doses. The absorbance of the polymer-gel dosimeter did not show any peak sensitivity within the studied range of wavelengths. For the range of doses studied, the best dose linearity was recorded, with an R2 of 0.9701 at a wavelength of 400 nm. The reproducibility of the results was excellent, and the error in the dose-rate dependence was within the range of ± 3%. The gel dosimeter displayed a very stable response, thus confirming the efficiency of this 3D dosimeter.

The purpose of our study is to find the potential best options for the registration selection parameters when performing automatic registration between kilovoltage computed tomography (KVCT) and megavoltage computed tomography (MVCT) images in helical tomotherapy. We compared nine different combinations of automatic registration parameters, including technique and resolution in automatic registration control and tomoimage filtering in scan image control. In the phantom study, we compared the translational and the rotational adjustments between the original position (lateral 0 cm; longitudinal 0 cm; vertical 0 cm) and the manually moved position (lateral 1 cm; longitudinal 1 cm; vertical 1 cm). In the patient study, we compared translational (lateral, longitudinal, vertical) and rotational (pitch, roll, yaw) adjustments between the KVCT and the MVCT images for different anatomic treatment sites. The ranges of translational and rotational displacements in the phantom study were 14.87 ± 0.12 ∼ 15.70 ± 0.04 mm and 0° ∼ 1.03 ± 0.58°, respectively. In cranial cases, the ranges of translational and rotational root-mean-square values were 4.3 ± 0.4 mm ∼ 5.3 ± 0.6 mm, and 0.3 ± 0.3° ∼ 0.7 ± 0.4°, respectively. In the extra cranial cases, the ranges of translational and rotational root-mean-square values were 14.1 ± 3.6 mm − 16.1 ± 2.5 mm, and 0.5 ± 0.3° ∼ 1.0 ± 0.5°, respectively. We found that the combination of “full image - super fine” could minimize the mechanical deviations in the cranial case, and that both the combinations of “bone tissue - super fine” and “full image - super fine” were the best options in extra cranial cases.

This study examined the characteristics of the dental X-ray fluoroscopic equipment, 'DreamRay 60F', which was recently developed in Korea. The output linearity, output reproducibility, half-value layer (HVL), leakage radiation and scattered radiation were measured using an ionisation chamber. The surface dose equivalent rate and estimated dose equivalent of the operator were also calculated. The output linearity was 0.0015-0.0175 and the coefficient of variation for the output reproducibility was 0.0013-0.0074. The experimental HVL was 2.1 mm Al, and the leakage dose rate at 100 cm from the X-ray focus ranged from 2.70 to 19.66 microGy h (-1) depending on the direction. The scattered radiation doses differed significantly (1.7-16.8 times) depending on the distance and direction. If an operator is exposed for 10 min per procedure, 5 procedures a day at 5 days a week, he/she sitting at a 90 degrees direction will receive an annual dose equivalent of 13.0 mSv (at 30 cm) and 63.7 mSv (at 50 cm) in the trunk and face surface, respectively.

The purpose of this study is to evaluate the influence of treatment-planning parameters on the quality of treatment plans in tomotherapy and to find the optimized planning parameter combinations when treating patients with prostate cancer under different performances. A total of 3 patients with prostate cancer with Eastern Cooperative Oncology Group (ECOG) performance status of 2 or 3 were included in this study. For each patient, 27 treatment plans were created using a combination of planning parameters (field width of 1, 2.5, and 5cm; pitch of 0.172, 0.287, and 0.43; and modulation factor of 1.8, 3, and 3.5). Then, plans were analyzed using several dosimetrical indices: the prescription isodose to target volume (PITV) ratio, homogeneity index (HI), conformity index (CI), target coverage index (TCI), modified dose HI (MHI), conformity number (CN), and quality factor (QF). Furthermore, dose-volume histogram of critical structures and critical organ scoring index (COSI) were used to analyze organs at risk (OAR) sparing. Interestingly, treatment plans with a field width of 1cm showed more favorable results than others in the planning target volume (PTV) and OAR indices. However, the treatment time of the 1-cm field width was 3 times longer than that of plans with a field width of 5cm. There was no substantial decrease in treatment time when the pitch was increased from 0.172 to 0.43, but the PTV indices were slightly compromised. As expected, field width had the most significant influence on all of the indices including PTV, OAR, and treatment time. For the patients with good performance who can tolerate a longer treatment time, we suggest a field width of 1cm, pitch of 0.172, and modulation factor of 1.8; for the patients with poor performance status, field width of 5cm, pitch of 0.287, and a modulation factor of 3.5 should be considered.

This study evaluated the mechanical accuracy of an in‐house–developed couch‐based tracking system (CBTS) according to respiration data. The overall delay time of the CBTS was calculated, and the accuracy, reproducibility, and loading effect of the CBTS were evaluated according to the sinusoidal waveform and various respiratory motion data of real patients with and without a volunteer weighing 75 kg. The root mean square (rms) error of the accuracy, the reproducibility, and the sagging measurements were calculated for the three axes (X, Y, and Z directions) of the CBTS. The overall delay time of the CBTS was 0.251 sec. The accuracy and reproducibility in the Z direction in real patient data were poor, as indicated by high rms errors. The results of the loading effect were within 1.0 mm in all directions. This novel CBTS has the potential for clinical application for tumor tracking in radiation therapy. PACS number: 87.55.ne

In this research, using direct measurements and Monte Carlo calculations, the potential dose reduction achieved by bismuth shielding in computed tomography was evaluated. The patient dose was measured using an ionisation chamber in a polymethylmethacrylate (PMMA) phantom that had five measurement points at the centre and periphery. Simulations were performed using the MCNPX code. For both the bare and the bismuth-shielded phantom, the differences of dose values between experiment and simulation were within 9 %. The dose reductions due to the bismuth shielding were 1.2–55 % depending on the measurement points, X-ray tube voltage and the type of shielding. The amount of dose reduction was significant for the positions covered by the bismuth shielding (34 − 46 % for head and 41 − 55 % for body phantom on average) and negligible for other peripheral positions. The artefact on the reconstructed images were minimal when the distance between the shielding and the organs was >1 cm, and hence the shielding should be selectively located to protect critical organs such as the eye lens, thyroid and breast. The simulation results using the PMMA phantom was compared with those using a realistically voxelised phantom (KTMAN-2). For eye and breast, the simulation results using the PMMA and KTMAN-2 phantoms were similar with each other, while for thyroid the simulation results were different due to the discrepancy of locations and the sizes of the phantoms. The dose reductions achieved by bismuth and lead shielding were compared with each other and the results showed that the difference of the dose reductions achieved by the two materials was less than 2–3 %.

The purpose of this study was to evaluate the set up accuracy using stereotactic body frame and frameless immobilizer for lung stereotactic body radiation therapy (SBRT). For total 40 lung cancer patients treated by SBRT, 20 patients using stereotactic body frame and other 20 patients using frameless immobilizer were separately enrolled in each group. The setup errors of each group depending on the immobilization methods were compared and analyzed. All patients received the dose of 48∼60 Gy for 4 or 5 fractions. Before each treatment, a patient was first localized to the treatment isocenter using room laser s, and further aligned with a series of image guidance procedures; orthogonal kV radiographs, cone-beam CT, o rthogonal fluoroscopy. The couch shifts during these procedures were recorded and analyzed for systematic and random errors of each group. Student t-test was performed to evaluate significant difference depending on the immobilization methods. The setup reproducibility was further analyzed using F-test with the random errors excluding the systematic setup errors. In addition, the ITV-PTV margin for each group was calculated. The setup errors for SBF were 0.05±0.25 cm in vertical direction, 0.20±0.38 cm in longitudinal direction, and 0.02±0.30 cm in lateral direction, respectively. However the setup errors for frameless immobilizer showed a significant increase of -0.24±0.25 cm in vertical direction while similar results of 0.06±0.34 cm, −0.02±0.25 cm in longitudinal and lateral directions. ITV-PTV margins for SBF were 0.67 cm (vertical), 0.99 cm (longitudinal), and 0.83 cm (lateral), respectively. On the other hand, ITV-PTV margins for Frameless immobilizer were 0.75 cm (vertical), 0.96 cm (longitudinal), and 0.72 cm (lateral), indicating less than 1 mm difference for all directions. In conclusion, stereotactic body frame improves reproducibility of patient setup, resulted in 0.1∼0.2 cm in both vertical and longitudinal directions. However the improvements are not substantial in clinic considering the effort and time consumption required for SBF setup.

Future researchwill enable thismethod to be combinedwith other techniques using surrogates or prior knowledge of the target trajectory in caseswhere the tumor is indistinguishable. Author Disclosure: A. Nakamura: None. Y. Matsuo: None. M. Yamada: A. Employee;MitsubishiHeavy Industries, LTD.N.Ueki:None.M.Nakamura: None. T. Shiinoki: None. A. Sawada: None. T.Mizowaki: None.M. Kokubo: None. M. Hiraoka: None.

The aims of this study, we present the preliminary results of 3 dimensional dose evaluation software (PDRESS, patient specific dose real evaluation systems). In this work, we compared planned 3D dose distribution with measured 3D dose distribution using a novel normoxic polymer gel dosimeter (TENOMAG) and a commercial cone-beam optical CT scanner (VISTATM, Modus Medical Devices, Inc., London, ON, Canada) to verify the 3D dose distribution in intensity-modulated radiation therapy (IMRT) prostate case. And we developed PDRESS using the Xelis Flatform which is developed by INFINITT Corporation is used to display the 3D dose distribution by loading the DICOM RT Data which is exported from RTP and optical-CT reconstructed VFF file. Data analysis is achieved by comparing the RTP data with the VFF data using profile, gamma map, and DTA. The profiles showed good agreement between RTP data, gel dosimeter, and gamma distribution and the precision of the dose distribution is within ± 5%. The results from this study show that there are no significantly discrepancies between the calculated dose distribution from treatment plan and the measured dose distribution from a TENOMAG gel scanned with an optical CT scanner. The 3D dose evaluation software (PDRESS) which is developed in this study evaluates the accuracy of the three dimensional dose distributions.