Assessment of log-based fingerprinting system of Mobius3D with Elekta linear accelerators.

PURPOSE: The purpose of this study was to investigate the matching error that occurs when the Mobius3D fingerprinting system is applied in conjunction with an Elekta linear accelerator (LINAC) and to offer an acceptable and alternative method for circumventing this problem. MATERIAL AND METHODS: To avoid the multileaf collimator (MLC) conflicting error in the Mobius3D fingerprinting system, we developed an in-house program to move the MLC in the Digital Imaging and Communications in Medicine (DICOM) radiotherapy (RT)-Plan to pertinent positions, considering the relationship between log data and planned data. The re-delivered log files were calculated in the Mobius3D system, and the results were compared with those of corrected data (i.e., we analyzed a pair of re-collected log data and the previous DICOM RT-Plan data). The results were then evaluated by comparing several items, such as point dose errors, gamma index (GI) passing rates, and MLC root-mean-square (RMS) values. RESULTS: For the point dose error, the maximum difference found was below 2.0%. In the case of GI analysis of all plans, the maximum difference in the passing rates was below 1.4%. The statistical results obtained using a paired Student's t-test showed that there were no significant differences within the uncertainty. In the case of the RMS test, the maximum difference found was approximately 0.08 mm. CONCLUSIONS: Our results showed that all the mismatched log files were sufficiently acceptable within the uncertainty. We conclude that the matching error obtained when applying Mobius3D to an Elekta LINAC may be addressed using a simple modification of the fingerprinting system, and we expect that our study findings will help vendors resolve this issue in the near future.

Development of a novel program for conversion from tetrahedral-mesh-based phantoms to DICOM dataset for radiation treatment planning: TET2DICOM.

PURPOSE: Tetrahedral mesh (TM)-based computational human phantoms have recently been developed for evaluation of exposure dose with the merit of precisely representing human anatomy and the changing posture freely. However, conversion of recently developed TM phantoms to the Digital Imaging and Communications in Medicine (DICOM) file format, which can be utilized in the clinic, has not been attempted. The aim of this study was to develop a technique, called TET2DICOM, to convert the TM phantoms to DICOM datasets for accurate treatment planning. MATERIALS AND METHODS: The TM phantoms were sampled in voxel form to generate the DICOM computed tomography images. The DICOM-radiotherapy structure was defined based on the contour data. To evaluate TET2DICOM, the shape distortion of the TM phantoms during the conversion process was assessed, and the converted DICOM dataset was implemented in a commercial treatment planning system (TPS). RESULTS: The volume difference between the TM phantoms and the converted DICOM dataset was evaluated as less than about 0.1% in each organ. Subsequently, the converted DICOM dataset was successfully implemented in MIM (MIM Software Inc., Cleveland, USA, version 6.5.6) and RayStation (RaySearch Laboratories, Stockholm, Sweden, version 5.0). Additionally, the various possibilities of clinical application of the program were confirmed using a deformed TM phantom in various postures. CONCLUSION: In conclusion, the TM phantom, currently the most advanced computational phantom, can be implemented in a commercial TPS and this technique can enable various TM-based applications, such as evaluation of secondary cancer risk in radiotherapy.

TomoMQA: Automated analysis program for MVCT quality assurance of helical tomotherapy.

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.

New small-intestine modeling method for surface-based computational human phantoms.

When converting voxel phantoms to a surface format, the small intestine (SI), which is usually not accurately represented in a voxel phantom due to its complex and irregular shape on one hand and the limited voxel resolutions on the other, cannot be directly converted to a high-quality surface model. Currently, stylized pipe models are used instead, but they are strongly influenced by developer's subjectivity, resulting in unacceptable geometric and dosimetric inconsistencies. In this paper, we propose a new method for the construction of SI models based on the Monte Carlo approach. In the present study, the proposed method was tested by constructing the SI model for the polygon-mesh version of the ICRP reference male phantom currently under development. We believe that the new SI model is anatomically more realistic than the stylized SI models. Furthermore, our simulation results show that the new SI model, for both external and internal photon exposures, leads to dose values that are more similar to those of the original ICRP male voxel phantom than does the previously constructed stylized SI model.

Radiomics-based hybrid model for predicting radiation pneumonitis: A systematic review and meta-analysis.

PURPOSE: This study reviewed and meta-analyzed evidence on radiomics-based hybrid models for predicting radiation pneumonitis (RP). These models are crucial for improving thoracic radiotherapy plans and mitigating RP, a common complication of thoracic radiotherapy. We examined and compared the RP prediction models developed in these studies with the radiomics features employed in RP models. METHODS: We systematically searched Google Scholar, Embase, PubMed, and MEDLINE for studies published up to April 19, 2024. Sixteen studies met the inclusion criteria. We compared the RP prediction models developed in these studies and the radiomics features employed. RESULTS: Radiomics, as a single-factor evaluation, achieved an area under the receiver operating characteristic curve (AUROC) of 0.73, accuracy of 0.69, sensitivity of 0.64, and specificity of 0.74. Dosiomics achieved an AUROC of 0.70. Clinical and dosimetric factors showed lower performance, with AUROCs of 0.59 and 0.58. Combining clinical and radiomic factors yielded an AUROC of 0.78, while combining dosiomic and radiomics factors produced an AUROC of 0.81. Triple combinations, including clinical, dosimetric, and radiomics factors, achieved an AUROC of 0.81. The study identifies key radiomics features, such as the Gray Level Co-occurrence Matrix (GLCM) and Gray Level Size Zone Matrix (GLSZM), which enhance the predictive accuracy of RP models. CONCLUSIONS: Radiomics-based hybrid models are highly effective in predicting RP. These models, combining traditional predictive factors with radiomic features, particularly GLCM and GLSZM, offer a clinically feasible approach for identifying patients at higher RP risk. This approach enhances clinical outcomes and improves patient quality of life. PROTOCOL REGISTRATION: The protocol of this study was registered on PROSPERO (CRD42023426565).

Dosimetric analysis of six whole-breast irradiation techniques in supine and prone positions.

In breast cancer radiation therapy, minimizing radiation-related risks and toxicity is vital for improving life expectancy. Tailoring radiotherapy techniques and treatment positions can reduce radiation doses to normal organs and mitigate treatment-related toxicity. This study entailed a dosimetric comparison of six different external beam whole-breast irradiation techniques in both supine and prone positions. We selected fourteen breast cancer patients, generating six treatment plans in both positions per patient. We assessed target coverage and organs at risk (OAR) doses to evaluate the impact of treatment techniques and positions. Excess absolute risk was calculated to estimate potential secondary cancer risk in the contralateral breast, ipsilateral lung, and contralateral lung. Additionally, we analyzed the distance between the target volume and OARs (heart and ipsilateral lung) while considering the treatment position. The results indicate that prone positioning lowers lung exposure in X-ray radiotherapy. However, particle beam therapies (PBTs) significantly reduce the dose to the heart and ipsilateral lung regardless of the patient's position. Notably, negligible differences were observed between arc-delivery and static-delivery PBTs in terms of target conformity and OAR sparing. This study provides critical dosimetric evidence to facilitate informed decision-making regarding treatment techniques and positions.

Dose-toxicity surface histogram-based prediction of radiation dermatitis severity and shape.

Objective.This study aimed to develop a new approach to predict radiation dermatitis (RD) by using the skin dose distribution in the actual area of RD occurrence to determine the predictive dose by grade.Approach.Twenty-three patients with head and neck cancer treated with volumetric modulated arc therapy were prospectively and retrospectively enrolled. A framework was developed to segment the RD occurrence area in skin photography by matching the skin surface image obtained using a 3D camera with the skin dose distribution. RD predictive doses were generated using the dose-toxicity surface histogram (DTH) calculated from the skin dose distribution within the segmented RD regions classified by severity. We then evaluated whether the developed DTH-based framework could visually predict RD grades and their occurrence areas and shapes according to severity.Main results.The developed framework successfully generated the DTH for three different RD severities: faint erythema (grade 1), dry desquamation (grade 2), and moist desquamation (grade 3); 48 DTHs were obtained from 23 patients: 23, 22, and 3 DTHs for grades 1, 2, and 3, respectively. The RD predictive doses determined using DTHs were 28.9 Gy, 38.1 Gy, and 54.3 Gy for grades 1, 2, and 3, respectively. The estimated RD occurrence area visualized by the DTH-based RD predictive dose showed acceptable agreement for all grades compared with the actual RD region in the patient. The predicted RD grade was accurate, except in two patients.Significance. The developed DTH-based framework can classify and determine RD predictive doses according to severity and visually predict the occurrence area and shape of different RD severities. The proposed approach can be used to predict the severity and shape of potential RD in patients and thus aid physicians in decision making.

Evaluation of the deliverability of dynamic conformal arc therapy (DCAT) by gantry wobble and its influence on dose.

We aimed to investigate the deliverability of dynamic conformal arc therapy (DCAT) by gantry wobble owing to the intrinsic inter-segment break of the Elekta linear accelerator (LINAC) and its adverse influence on the dose to the patient. The deliverability of DCAT was evaluated according to the plan parameters, which affect the gantry rotation speed and resultant positional inaccuracies; the deliverability according to the number of control points and dose rates was investigated by using treatment machine log files and dosimetry devices, respectively. A non-negligible degradation in DCAT deliverability due to gantry wobble was observed in both the treatment machine log files and dosimetry devices. The resulting dose-delivery error occurred below a certain number of control points or above a certain dose rate. Dose simulations in the patient domain showed a similar impact on deteriorated deliverability. For targets located primarily in the isocenter, the dose differences were negligible, whereas for organs at risk located mainly off-isocenter, the dose differences were significant up to - 8.77%. To ensure safe and accurate radiotherapy, optimal plan parameters should be selected, and gantry angle-specific validations should be conducted before treatment.

Clinical feasibility of deep learning-based synthetic CT images from T2-weighted MR images for cervical cancer patients compared to MRCAT.

This work aims to investigate the clinical feasibility of deep learning-based synthetic CT images for cervix cancer, comparing them to MR for calculating attenuation (MRCAT). Patient cohort with 50 pairs of T2-weighted MR and CT images from cervical cancer patients was split into 40 for training and 10 for testing phases. We conducted deformable image registration and Nyul intensity normalization for MR images to maximize the similarity between MR and CT images as a preprocessing step. The processed images were plugged into a deep learning model, generative adversarial network. To prove clinical feasibility, we assessed the accuracy of synthetic CT images in image similarity using structural similarity (SSIM) and mean-absolute-error (MAE) and dosimetry similarity using gamma passing rate (GPR). Dose calculation was performed on the true and synthetic CT images with a commercial Monte Carlo algorithm. Synthetic CT images generated by deep learning outperformed MRCAT images in image similarity by 1.5% in SSIM, and 18.5 HU in MAE. In dosimetry, the DL-based synthetic CT images achieved 98.71% and 96.39% in the GPR at 1% and 1 mm criterion with 10% and 60% cut-off values of the prescription dose, which were 0.9% and 5.1% greater GPRs over MRCAT images.

Dosimetric comparison of robust angles in carbon-ion radiation therapy for prostate cancer.

The objective of this study is to compare the plan robustness at various beam angles. Hence, the influence of the beam angles on robustness and linear energy transfer (LET) was evaluated in gantry-based carbon-ion radiation therapy (CIRT) for prostate cancer. 10 patients with prostate cancer were considered, and a total dose of 51.6 Gy (Relative biological effectiveness (RBE) was prescribed for the target volume in 12 fractions. Five beam field plans comprising two opposed fields with different angle pairs were characterized. Further, dose parameters were extracted, and the RBE-weighted dose and LET values for all angle pairs were compared. All plans considering the setup uncertainty satisfied the dose regimen. When a parallel beam pair was used for perturbed scenarios to take into account set-up uncertainty in the anterior direction, the LET clinical treatment volume (CTV) D 95% standard deviation was 1.5 times higher, and the standard deviation of RBE-weighted CTV D 95% was 7.9 times higher compared to an oblique pair. The oblique beam fields were superior in terms of dose sparing for the rectum compared to the dose distribution using two conventional lateral opposed fields for prostate cancer.

Novel framework for determining TPS-calculated doses corresponding to detector locations using 3D camera inin vivosurface dosimetry.

Purpose. To address the shortcomings of current procedures for evaluating the measured-to-planned dose agreement inin vivodosimetry (IVD), this study aimed to develop an accurate and efficient novel framework to identify the detector location placed on a patient's skin surface using a 3D camera and determine the planned dose at the same anatomical position corresponding to the detector location.Methods. Breast cancer treatment was simulated using an anthropomorphic adult female phantom (ATOM 702D; CIRS, Norfolk, VA, USA). An optically stimulated luminescent dosimeter was used for surface dose measurements (MyOSLchip, RadPro International GmbH, Germany) at six IVD points. Three-dimensional surface imaging (3DSI) of the phantom with the detector was performed in the treatment position using a 3D camera. The developed framework, iSMART, was designed to import 3DSI and treatment planning data for determining the position of the IVD detectors in the 3D treatment planning DICOM image. The clinical usefulness of iSMART was evaluated in terms of accuracy and efficiency, for comparison with the results obtained using cone-beam computed tomography (CBCT) image guidance.Results. The relative dose difference between the planned doses determined using iSMART and CBCT images displayed similar accuracies (within approximately ±2.0%) at all detector locations. The relative dose differences between the planned and measured doses at the six detector locations ranged from -4.8% to 3.1% for the CBCT images and -3.5% to 2.1% for iSMART. The total time required to read the planned doses at six detector locations averaged at 8.1 and 0.8 min for the CBCT images and iSMART, respectively.Conclusions. The proposed framework can improve the robustness of IVD analyses and aid in accurate and efficient evaluations of the measured-to-planned dose agreement.

Cosmetic Outcome and Toxicity After Stereotactic Accelerated Partial Breast Irradiation in Early Breast Cancer: A Prospective Observational Cohort Study.

PURPOSE: The aim of this work was to prospectively evaluate the toxicity and cosmetic outcomes of 5-fraction, stereotactic, accelerated partial breast irradiation (APBI). METHODS AND MATERIALS: This prospective observational cohort study enrolled women who underwent APBI for invasive carcinoma or carcinoma in situ of the breast. APBI was delivered using a CyberKnife M6 robotic radiosurgery system at 30 Gy in 5 nonconsecutive, once-daily fractions. Women undergoing whole breast irradiation (WBI) were also enrolled for comparison. Patient-reported and physician-assessed adverse events were recorded. Breast fibrosis was measured using a tissue compliance meter, and breast cosmesis was assessed using BCCT.core (an automatic, computer-based software). Outcomes were collected until 24 months posttreatment according to the study protocol. RESULTS: In total, 204 patients (APBI, n = 103; WBI, n = 101) were enrolled. Regarding patient-reported outcomes, the APBI group reported significantly less skin dryness (6.9% vs 18.3%; P = .015), radiation skin reaction (9.9% vs 23.5%; P = .010), and breast hardness (8.0% vs 20.4%; P = .011) at 6 months than the WBI group. On physician assessment, the APBI group had significantly less dermatitis at 12 months (1.0% vs 7.2%; P = .027) than the WBI group. Any severe toxicities after APBI were rare in patient-reported outcomes (score ≥3, 3.0%) and physician assessments (grade ≥3, 2.0%). In the uninvolved quadrants, measured fibrosis in the APBI group was significantly lower than that in the WBI group at 6 (P = .001) and 12 (P = .029) months but not at 24 months. In the involved quadrant, measured fibrosis in the APBI group was not significantly different from that in the WBI group at any time. Cosmetic outcomes in the APBI group were mostly excellent or good (77.6%) at 24 months, and there was no significant cosmetic detriment from the baseline. CONCLUSIONS: Stereotactic APBI was associated with less fibrosis in the uninvolved breast quadrants than WBI. Patients showed minimal toxicity and no detrimental effects on cosmesis after APBI.

Comprehensive clinical evaluation of TomoEQA for patient-specific pre-treatment quality assurance in helical tomotherapy.

BACKGROUND: Based on a previous study on the feasibility of TomoEQA, an exit detector-based patient-specific pre-treatment quality assurance (QA) method for helical tomotherapy, an in-depth clinical evaluation was conducted. METHODS: Data of one hundred patients were analyzed to evaluate the clinical usefulness of TomoEQA for patient-specific pre-treatment QA in comparison with the conventional phantom-based method. Additional investigations were also performed under unusual measurement conditions to validate the off-axis region. In addition to the clinical evaluation of TomoEQA, a statistical analysis was conducted to determine the plan parameters that affect the pass/failure results of pre-treatment QA. RESULTS: The average and standard deviations of the gamma passing rate and point dose error for TomoEQA were comparable to those of the conventional QA method. For TomoEQA, the average values of the gamma passing rate and point dose error were 96.32% (standard deviation (1 sigma) = 3.94; 95% confidence interval (CI), 95.55 to 97.09) and - 1.12% (standard deviation (1 sigma) = 1.04; CI, - 1.32 to - 0.92), respectively. For the conventional QA method, the average values of the gamma passing rate and point dose error were 95.95% (standard deviation (1 sigma) = 4.35; 95% confidence interval (CI), 95.10 to 96.80) and - 1.20% (standard deviation (1 sigma) = 1.61; CI, - 1.52 to - 0.88), respectively. Further experiments on the off-axis region demonstrated that TomoEQA can provide accurate results for 3D dose analysis, which is inherently difficult in the conventional QA method. Through a statistical analysis based on the results of TomoEQA, it was validated that the total fraction (Total Fx), monitor units, beam-on-time, leaf-of-time below 100 ms, and planning target volume diameter were statistically significant for the pass/failure of the pre-treatment QA results. CONCLUSIONS: TomoEQA is a clinically beneficial alternative to the conventional phantom-based QA method.

Metal artifact reduction in kV CT images throughout two-step sequential deep convolutional neural networks by combining multi-modal imaging (MARTIAN).

This work attempted to construct a new metal artifact reduction (MAR) framework in kilo-voltage (kV) computed tomography (CT) images by combining (1) deep learning and (2) multi-modal imaging, defined as MARTIAN (Metal Artifact Reduction throughout Two-step sequentIAl deep convolutional neural Networks). Most CNNs under supervised learning require artifact-free images to artifact-contaminated images for artifact correction. Mega-voltage (MV) CT is insensitive to metal artifacts, unlike kV CT due to different physical characteristics, which can facilitate the generation of artifact-free synthetic kV CT images throughout the first network (Network 1). The pairs of true kV CT and artifact-free kV CT images after post-processing constructed a subsequent network (Network 2) to conduct the actual MAR process. The proposed framework was implemented by GAN from 90 scans for head-and-neck and brain radiotherapy and validated with 10 independent cases against commercial MAR software. The artifact-free kV CT images following Network 1 and post-processing led to structural similarity (SSIM) of 0.997, and mean-absolute-error (MAE) of 10.2 HU, relative to true kV CT. Network 2 in charge of actual MAR successfully suppressed metal artifacts, relative to commercial MAR, while retaining the detailed imaging information, yielding the SSIM of 0.995 against 0.997 from the commercial MAR.

Evaluating Mobius3D Dose Calculation Accuracy for Small-Field Flattening- Filter-Free Photon Beams.

Purpose: We aimed to investigate the dose calculation accuracy of Mobius3D for small-field flattening-filter-free x-rays, mainly utilized for stereotactic body radiation therapy (SBRT). The accuracy of beam modeling and multileaf collimator (MLC) modeling in Mobius3D, significantly affecting the dose calculation is investigated. Methods: The commissioning procedures of Mobius3D were performed for unflattened 6 MV and 10 MV x-ray beams of the linear accelerator, including beam model adjustment and dosimetric leaf gap (DLG) optimization. An experimental study with artificial plans was conducted to evaluate the accuracy of small-field modeling. The dose calculation accuracy of Mobius3D was also evaluated for retrospective SBRT plans with multiple targets. Results: Both studies evaluated the dose calculation accuracy through comparisons with the measured data. Relatively large differences were observed for off-axis distances over 5 cm and for small fields less than 1 cm field size. For the study with artificial plans, the maximum absolute error of 9.96% for unflattened 6 MV and 9.07% for unflattened 10 MV was observed when the field size was 1 cm. For the study with patient plans, the mean gamma passing rate with 3%/3 mm gamma criterion was 63.6% for unflattened 6 MV and 82.6% for unflattened 10 MV. The maximum of the average dose difference was -19.9% for unflattened 6MV and -10.1% for unflattened 10MV. Conclusions: The dose calculation accuracy uncertainties of Mobius3D for small-field flattening-filter-free photon beams were observed. The study results indicated that the beam and MLC modeling of Mobius3D must be improved for use in SBRT pretreatment QA in clinical practice.

Performance Evaluation of Deformable Image Registration Algorithms Using Computed Tomography of Multiple Lung Metastases.

Purpose: Various deformable image registration (DIR) methods have been used to evaluate organ deformations in 4-dimensional computed tomography (4D CT) images scanned during the respiratory motions of a patient. This study assesses the performance of 10 DIR algorithms using 4D CT images of 5 patients with fiducial markers (FMs) implanted during the postoperative radiosurgery of multiple lung metastases. Methods: To evaluate DIR algorithms, 4D CT images of 5 patients were used, and ground-truths of FMs and tumors were generated by physicians based on their medical expertise. The positions of FMs and tumors in each 4D CT phase image were determined using 10 DIR algorithms, and the deformed results were compared with ground-truth data. Results: The target registration errors (TREs) between the FM positions estimated by optical flow algorithms and the ground-truth ranged from 1.82 ± 1.05 to 1.98 ± 1.17 mm, which is within the uncertainty of the ground-truth position. Two algorithm groups, namely, optical flow and demons, were used to estimate tumor positions with TREs ranging from 1.29 ± 1.21 to 1.78 ± 1.75 mm. With respect to the deformed position for tumors, for the 2 DIR algorithm groups, the maximum differences of the deformed positions for gross tumor volume tracking were approximately 4.55 to 7.55 times higher than the mean differences. Errors caused by the aforementioned difference in the Hounsfield unit values were also observed. Conclusions: We quantitatively evaluated 10 DIR algorithms using 4D CT images of 5 patients and compared the results with ground-truth data. The optical flow algorithms showed reasonable FM-tracking results in patient 4D CT images. The iterative optical flow method delivered the best performance in this study. With respect to the tumor volume, the optical flow and demons algorithms delivered the best performance.

Physical and Biological Characteristics of Particle Therapy for Oncologists.

Particle therapy is a promising and evolving modality of radiotherapy that can be used to treat tumors that are radioresistant to conventional photon beam radiotherapy. It has unique biological and physical advantages compared with conventional radiotherapy. The characteristic feature of particle therapy is the "Bragg peak," a steep and localized peak of dose, that enables precise delivery of the radiation dose to the tumor while effectively sparing normal organs. Especially, the charged particles (e.g., proton, helium, carbon) cause a high rate of energy loss along the track, thereby leading to high biological effectiveness, which makes particle therapy attractive. Using this property, the particle beam induces more severe DNA double-strand breaks than the photon beam, which is less influenced by the oxygen level. This review describes the general biological and physical aspects of particle therapy for oncologists, including non-radiation oncologists and beginners in the field.

TomoEQA: Dose verification for patient-specific quality assurance in helical tomotherapy using an exit detector.

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.

Monitoring beam-quality constancy considering uncertainties associated with ionization chambers in Daily QA3 device.

This study evaluates the changes occurring in the X-ray energy of a linear accelerator (LINAC) using a Daily QA3 detector system. This is accomplished by comparing the Daily QA3 results against those obtained using a water phantom. The X-energy levels of a LINAC were monitored over a duration of 1 month using the Daily QA3 system. Moreover, to account for the uncertainty, the reproducibility of the Daily QA3 ionization-chamber results was assessed by performing repeated measurements (12 per day). Subsequently, the energy-monitoring results were compared with the energy-change results calculated using the water-phantom percentage depth dose (PDD) ratio. As observed, the 6- and 10-MV beams experienced average daily energy-level changes of (-0.30 ± 0.32)% and (0.05 ± 0.38)%, respectively, during repeated measurements. The corresponding energy changes equaled (-0.30 ± 0.55)% and (-0.05 ± 0.48)%, respectively, when considering the measurement uncertainty. The Daily QA3 measurements performed at 6 MV demonstrated a variation of (2.15 ± 0.81)% (i.e., up to 3%). Meanwhile, the corresponding measurements performed using a water phantom demonstrated an increase in the PDD ratio from 0.577 to 0.580 (i.e., approximately 0.5%). At 10 MV, the energy variation in the Daily QA3 measurements equaled (-0.41 ± 0.82)% (i.e., within 1.5%), whereas the corresponding water phantom PDD ratio remained constant at 0.626. These results reveal that the Daily QA3 system can be used to monitor small energy changes occurring within radiotherapy machines. This demonstrates its potential for use as a secondary system for monitoring energy changes as part of the daily quality-assurance workflow.

Dosimetric Comparison of Radiation Techniques for Comprehensive Regional Nodal Radiation Therapy for Left-Sided Breast Cancer: A Treatment Planning Study.

PURPOSE: How modern cardiac sparing techniques and beam delivery systems using advanced x-ray and proton beam therapy (PBT) can reduce incidental radiation exposure doses to cardiac and pulmonary organs individually or in any combination is poorly investigated. METHODS: Among 15 patients with left-sided breast cancer, partial wide tangential 3D-conformal radiotherapy (3DCRT) delivered in conventional fractionation (CF) or hypofractionated (HF) schedules; PBT delivered in a CF schedule; and volumetric modulated arc therapy (VMAT) delivered in an HF schedule, each under continuous positive airway pressure (CPAP) and free-breathing (FB) conditions, were examined. Target volume coverage and doses to organs-at-risk (OARs) were calculated for each technique. Outcomes were compared with one-way analysis of variance and the Bonferroni test, with p-values <0.05 considered significant. RESULTS: Target volume coverage was within acceptable levels in all interventions, except for the internal mammary lymph node D95 (99% in PBT, 90% in VMAT-CPAP, 84% in VMAT-FB, and 74% in 3DCRT). The mean heart dose (MHD) was the lowest in PBT (<1 Gy) and VMAT-CPAP (2.2 Gy) and the highest in 3DCRT with CF/FB (7.8 Gy), respectively. The mean lung dose (MLD) was the highest in 3DCRT-CF-FB (20 Gy) and the lowest in both VMAT-HF-CPAP and PBT (approximately 5-6 Gy). VMAT-HF-CPAP and PBT delivered a comparable maximum dose to the left ascending artery (7.2 and 6.13 Gy, respectively). CONCLUSIONS: Both proton and VMAT in combination with CPAP can minimize the radiation exposure to heart and lung with optimal target coverage in regional RT for left-sided breast cancer. The clinical relevance of these differences is yet to be elucidated. Continued efforts are needed to minimize radiation exposures during RT treatment to maximize its therapeutic index.