Gamma Index Research Articles

Characterizing Photon Beam Properties of a TrueBeam STx Linear Accelerator: An Evaluation of Geant4/GATE Monte Carlo Simulation Tool Performance

Purpose: This study aims to investigate the characteristics of photon beams from TrueBeam STx, comparing flattening filter (FF) and flattening filter free (FFF) configurations between measurements and Monte Carlo simulation. Instruments and methods: The Geant4/GATE simulation toolkit was utilized to simulate percentage depth dose (PDD), off-axis distance profiles (profiles), dmax, TPR20/10, surface dose, field size, penumbra, flatness, and symmetry. Subsequently, these simulated results were compared with experimental measurements and evaluated using the gamma index method. Results: There was a good agreement between simulation and experimental measurement results in modeling the PDD and profile of photon beams. All gamma passing rate indices exceeded 97 %, 94 %, and 90 % with criteria of 3 % and 3 mm, 2 % and 2 mm, and 1 % and 1 mm, respectively. The calculated results of beam characteristics (dmax, TPR20/10, surface dose, field size, penumbra, flatness, and symmetry) were highly compatible with experimental measurements, with discrepancies less than 3 %, except for the surface dose of the 6MV FF photon beam, which had an error of 3.83 %. Conclusion: The Geant4/GATE simulation toolkit provided accurate results for simulating and investigating photon beam characteristics, aligning closely with experimental measurements.

Assessing Surface Guided Radiation Therapy Benefits for Paediatric Cancer Patients: Dosimetric Implications of Intrafractional Motion - An Institutional Review

<i>Introduction/Background</i>: SGRT, a real-time imaging technique, offers continuous monitoring and motion control during <i>treatment</i>. The investigation aims to assess potential dosimetric alterations in target coverage due to intrafractional motion, considering its impact on patient safety and treatment efficiency. <i>Materials and Methods</i>: A retrospective chart review was conducted to assess intrafractional shifts in 18 paediatric cancer patients. Patient setup employed SGRT using AlignRT (Vision RT Ltd., UK), and the PTV was aligned with CBCT. The study introduced induced shifts of 3 mm, 5 mm, and 7 mm during treatment delivery, assessing their impact on portal dosimetry results for both treatment fields. The gamma index criteria (3%, 3 mm) were employed to evaluate dosimetric accuracy. <i>Results</i>: A total of 18 patients were included, and induced shifts were analyzed for their impact on the planned gamma index values. Significant differences were observed between the Planned Gamma Index and induced shifts of 3 mm, 5 mm, and 7 mm for both treatment fields, highlighting the dosimetric implications of intrafractional motion in paediatric cases. <i>Conclusion</i>: Surface Guided Radiation Therapy (SGRT) is concluded to offer a comprehensive array of benefits for paediatric cases. The dosimetric implications of induced shifts underscore the importance of SGRT in ensuring accurate and safe treatment for paediatric cancer patients.

Deep learning–based statistical robustness evaluation of intensity-modulated proton therapy for head and neck cancer

A dense, dilated 3D U-net was trained to predict the 5th and 95th percentile distributions of planning dose plan using the nominal dose and planning CT images. The data set comprised proton therapy plans for 582 H&N cancer patients. Ground truth percentile values were estimated for each patient through 600 dose recalculations, representing randomly sampled uncertainty scenarios. The comprehensive comparisons of different models were conducted for H&N cancer patients, considering those with and without a beam mask (BM) and diverse beam configurations, including varying beam angles, couch angles, and beam numbers. The performance of our model trained based on a mixture of patients with H&N and prostate cancer was also assessed in contrast with models trained based on data specific for patients with cancer at either site. The DL-based model's predictions of percentile dose distributions exhibited excellent agreement with the ground truth dose distributions. The average gamma index with 2 mm/2%, consistently exceeded 97% for both 5th and 95th percentile dose volumes. Mean dose-volume histogram error analysis revealed that predictions from the combined training set yielded mean errors and standard deviations that were generally similar to those in the specific patient training data sets. Our proposed DL-based method for evaluation of the robustness of proton therapy plans provides precise, rapid predictions of percentile dose for a given confidence level regardless of the beam arrangement and cancer site. This versatility positions our model as a valuable tool for evaluating the robustness of proton therapy across various cancer sites.

Real-time tracking of the Bragg peak during proton therapy via 3D protoacoustic Imaging in a clinical scenario

Proton radiotherapy favored over X-ray photon therapy due to its reduced radiation exposure to surrounding healthy tissues, is highly dependent on the accurate positioning of the Bragg peak. Existing methods like PET and prompt gamma imaging to localize Bragg peak face challenges of low precision and high complexity. Here we introduce a 3D protoacoustic imaging with a 2D matrix array of 256 ultrasound transducers compatible with 256 parallel data acquisition channels provides real-time imaging capability (up to 75 frames per second with 10 averages), achieving high precision (5 mm/5% Gamma index shows accuracy better than 95.73%) at depths of tens of centimeters. We have successfully implemented this method in liver treatment with 5 pencil beam scanning and in prostate cancer treatment on a human torso phantom using a clinical proton machine. This demonstrates its capability to accurately identify the Bragg peak in practical clinical scenarios. It paves the way for adaptive radiotherapy with real-time feedback, potentially revolutionizing radiotherapy by enabling closed-loop treatment for improved patient outcomes.

Comparative assessment and QA measurement array validation of Monte Carlo and Collapsed Cone dose algorithms for small fields and clinical treatment plans.

Many studies have demonstrated superior performance of Monte Carlo (MC) over type B algorithms in heterogeneous structures. However, even in homogeneous media, MC dose simulations should outperform type B algorithms in situations of electronic disequilibrium, such as small and highly modulated fields. Our study compares MC and Collapsed Cone (CC) dose algorithms in RayStation 12A. Under consideration are 6 MV and 6 MV flattening filter-free (FFF) photon beams, relevant for VMAT plans such as head-and-neck and stereotactic lung treatments with heterogeneities, as well as plans for multiple brain metastases in one isocenter, involving highly modulated small fields. We aim to investigate collimator angle dependence of small fields and performance differences between different combinations of ArcCHECK configuration and dose algorithm. Several verification tests were performed, ranging from simple rectangular fields to highly modulated clinical plans. To evaluate and compare the performance of the models, the agreements between calculation and measurement are compared between MC and CC. Measurements include water tank measurements for test fields, ArcCHECK measurements for test fields and VMAT plans, and film dosimetry for small fields. In very small or narrow fields, our measurements reveal a strong dependency of dose output to collimator angle for VersaHD with Agility MLC, reproduced by both dose algorithms. ArcCHECK results highlight a suboptimal agreement between measurements and MC calculations for simple rectangular fields when using inhomogeneous ArcCHECK images. Therefore, we advocate for the use of homogeneous phantom images, particularly for static fields, in ArcCHECK verification with MC. MC might offer performance benefits for more modulated treatment fields. In ArcCHECK results for clinical plans, MC performed comparable to CC for 6 MV. For 6 MV FFF and the preferred homogeneous phantom image, MC resulted in consistently better results (13%-64% lower mean gamma index) compared to CC.

Evaluation of the geometric and dosimetric accuracies of deformable image registration of targets and critical organs in prostate CBCT-guided adaptive radiotherapy.

Kilovoltage cone beam computed tomography (kVCBCT)-guided adaptive radiation therapy (ART) uses daily deformed CT (dCT), which is generated automatically through deformable registration methods. These registration methods may perform poorly in reproducing volumes of the target organ, rectum, and bladder during treatment. We analyzed the registration errors between the daily kVCBCTs and corresponding dCTs for these organs using the default optical flow algorithm and two registration procedures. We validated the effectiveness of these registration methods in replicating the geometry for dose calculation on kVCBCT for ART. We evaluated three deformable image registration (DIR) methods to assess their registration accuracy and dose calculation effeciency in mapping target and critical organs. The DIR methods include (1) default intensity-based deformable registration, (2) hybrid deformable registration, and (3) a two-step deformable registration process. Each technique was applied to a computerized imaging reference system (CIRS) phantom (Model 062M) and to five patients who received volumetric modulated arc therapy to the prostate. Registration accuracy was assessed using the 95% Hausdorff distance (HD95) and Dice similarity coefficient (DSC), and each method was compared with the intensity-based registration method. The improvement in the dCT image quality of the CIRS phantom and five patients was assessed by comparing dCT with kVCBCT. Image quality quantitative metrics for the phantom included the signal-to-noise ratio (SNR), uniformity, and contrast-to-noise ratio (CNR), whereas those for the patients included the mean absolute error (MAE), mean error, peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). To determine dose metric differences, we used a dose-volume histogram (DVH) and 3.0%/0.3mm gamma analysis to compare planning computed tomography (pCT) and kVCBCT recalculations with restimulated CT images used as a reference. The dCT images generated by the hybrid (dCTH) and two-step (dCTC) registration methods resulted in significant improvements compared to kVCBCT in the phantom model. Specifically, the SNR improved by 107% and 107.2%, the uniformity improved by 90% and 75%, and the CNR improved by 212.2% and 225.6 for dCTH and dCTC methods, respectively. For the patient images, the MAEs improved by 98% and 94%, the PSNRs improved by 16.3% and 22.9%, and the SSIMs improved by 1% and 1% in the dCTH and dCTC methods, respectively. For the geometric evaluation, only the two-step registration method improved registration accuracy. The dCTH method yielded an average HD95 of 12mm and average DSC of 0.73, whereas dCTC yielded an average HD95 of 2.9mm and average DSC of 0.902. The DVH showed that the dCTC-based dose calculations differed by <2% from the expected results for treatment targets and volumes of organs at risk. Additionally, gamma indices for dCTC-based treatment plans were >95% at all points, whereas they were <95% for kVCBCT-based treatment plans. The two-step registration method outperforms the intensity-based and hybrid registration methods. While the hybrid and two-step-based methods improved the image quality of kVCBCT in a linear accelerator, only the two-step method improved the registration accuracy of the corresponding structures among the pCT and kVCBCT datasets. A two-step registration process is recommended for applying kVCBCT to ART, which achieves better registration accuracy for local and global image structures. This method appears to be beneficial for radiotherapy dose calculation in patients with pelvic cancer.

Exploring the impact of field shape on predicted dose distribution in breast cancer patients using deep learning in radiation therapy

BackgroundGeometrical information such as field shape is essential for dose calculation in radiation therapy. However, new methods of dose prediction based on deep learning only use CT images and contouring of patients. The aim of this study is to develop a deep learning method for three-dimensional dose prediction for breast cancer radiotherapy using field shape as well as CT and contouring images of patients. MethodsA total of 150 breast cancer patients' data treated with 3D conformal radiation therapy (CRT) technique were used to train and test 3D-U-Res-F-Net model. The model inputs were CT images, patients' contouring and field shape. The network output was the corresponding the patients’ dose distribution. Then, the dosimetric parameters extracted from the dose volume histograms related to the planned and predicted dose distributions were compared and were statistically analysed with the paired-samples t-test. These parameters include Dmean and Dmax for planning target volume and organs at risk, D95%, D50%, V47.5Gy for PTV, V30Gy and V25Gy for heart and V20Gy for left lung. The gamma index with 3%/3 mm criteria was calculated for PTV and OARs. ResultsThe average absolute difference of the Dmean relative to the prescribed dose for the PTV, heart, left lung, right lung and spinal cord were 1.37 ± 0.4%, 2.02 ± 2%, 2.12 ± 1%, 0.37 ± 0.3% and 0.41 ± 0.3%, respectively. The average absolute difference of the Dmax relative to the prescribed dose for the PTV and OARs varied from 0.23 ± 0.2% to 2.04 ± 2%. The 3D gamma pass rate with 3mm/3% criteria for planning target volume, heart, left lung, right lung, spinal cord and body were 89 ± 3%, 91 ± 5%, 93 ± 5%, 99 ± 3%, 99 ± 1% and 96 ± 2% respectively. ConclusionsThe results of the proposed model demonstrate that there is no significant difference between the predicted and planned dose distributions. The deep learning model can directly predict the 3D dose distribution faster than treatment planning systems. Further studies with more patients and on other cancer sites are essential to fully validate the proposed method.

Estimating the Toxicity of Radionuclides in Soil Stored in Drums in the Tuwaitha Area for Determining the Harmful Effects on Humans and Environment

Radioactive waste management is a fundamental issue when using nuclear energy. Therefore, it is necessary to study the health and biological effects on human and environment that these radionuclides cause. The aim of the present study is to estimate the radiotoxicity for radioactive waste in stocked soil in Al-Twaitha city. The radiotoxicity was calculated for each radionuclide, present in the waste, using their dose factor due to ingestion, which is given by the International Commission on Radiological Protection (ICRP) compendium. For the purpose of calculating radiation toxicity, a scenario was built that 20% of the radioactivity during radioactive waste handling processes is in the form of dust that can be inhaled or entered through the mouth or eyes. Drums Characterization System (DCS) provided with portable HPGe hand-held radioisotope identifier was used for the characterization and identification of the radionuclides in the drums and the dose rate was measured by Ludlum radiation detector. The absorbed dose rate ranged from 134.904nGy h-1 to 788400 nGy.h-1, the internal hazard index from 0 to 0.035, representative gamma index from 0 to 0.068, representative alpha index ( from 0 to 0.017, excess lifetime cancer risk (ELCR) value ranged from 0.66× 10-6 to 3.86×10-3 and the range of AEDE from 0.19 mSv to 1103.76 mSv.

Indicators of Radioactive Contamination by Radionuclides for Samples of Plant Fertilizers and Pesticides

Abstract: This study aims to evaluate the radiation levels resulting from plant fertilizers and pesticides in Babylon City, Iraq. The specific activity of the studied radionuclides (e.g. 238U, 232Th, and 40K) was identified using the spectroscopy approach of the sodium-activated iodide thallium (NaI (Tl)) with dimensions of 3" × 3". The resulting data revealed that the specific activities for the aforementioned nuclides were 6.254 Bq/kg, 4.3694 Bq/kg, and 112.751 Bq/kg, respectively. The results indicated that the average radiation hazard metrics for fertilizers (i.e., gamma index, alpha index, absorbed dose rate, ambient dose equivalent rate, annual gonadal dose equivalent, and excess lifetime cancer risk) were lower than the reference levels. Keywords: Radiation hazard, Fertilizer, Pesticides, Risk parameters, Gamma activity.

Analysis of the gamma index using an indigenously developed anthropomorphic heterogeneous female pelvis (AHFP) phantom.

It is essential in modern radiotherapy treatment practices to evaluate the quality assurance (QA) of the treatment plan prior to the exclusion of patient from treatment. The typical suitable tools used for patient pretreatment QA are phantoms representing the human anatomy. An anthropomorphic heterogeneous female pelvic (AHFP) phantom has been developed to represent the real female pelvic structure. The objective of the current study is to assess the findings of relative dosimetry carried out utilizing an electronic portal imaging device (EPID) on the AHFP phantom fabricated. The planning target volume (PTV) was created on CT slices of an AHFP phantom to confirm the tool's ability to represent female pelvic anatomy and serve as a QA tool. In order to assess the dose received by healthy organs during radiotherapy, organs at risk such as the bladder and rectum were additionally drawn alongside the PTV. Rapid Arc and Intensity modulated radiation therapy (IMRT) were both used to create the treatment plan on treatment planning system, and the Anisotropic Analytical Algorithm Version 11.0.31 was used to calculate the dose. The results obtained for the average gamma value in RapidArc plans are 0.26, 0.27, and 0.28 (g ≤1) and IMRT plans are 0.39, 0.40, and 0.46 (g ≤1) for target 1, target 2, and target 3, respectively. According to the findings of the current study, the AHFP phantom was used to explore the potential of relative dosimetry using EPID as a QA tool, which was found to be suitable.

Commissioning an ultra-high-dose-rate electron linac with end-to-end tests

Objective. The FLASH effect can potentially be used to improve the therapeutic ratio of radiotherapy (RT) through delivery of Ultra-high-dose-rate (UHDR) irradiation. Research is actively being conducted to translate UHDR-RT and for this purpose the Mobetron is capable of producing electron beams at both UHDR and conventional dose rates for FLASH research and translation. This work presents commissioning of an UHDR Mobetron with end-to-end tests developed for preclinical research. Approach. UHDR electron beams were commissioned with an efficient approach utilizing a 3D-printed water tank and film to fully characterize beam characteristics and dependences on field size, pulse width (PW) and pulse repetition frequency (PRF). This commissioning data was used to implement a beam model using the GAMOS Monte Carlo toolkit for the preclinical research. Then, the workflow for preclinical FLASH irradiation was validated with end-to-end tests delivered to a 3D-printed mouse phantom with internal inhomogeneities. Main results. PDDs, profiles and output factors acquired with radiochromic films were precisely measured, with a PRF that showed little effect on the UHDR beam energy and spatial characteristics. Increasing PW reduced the D max and R50 by 2.08 mm µs−1 and 1.28 mm µs−1 respectively. An end-to-end test of the preclinical research workflow showed that both profiles in head-foot and lateral directions were in good agreement with the MC calculations for the heterogeneous 3D printed mouse phantom with Gamma index above 93% for 2 mm/2% criteria, and 99% for 3 mm/3%. Significance. The UHDR Mobetron is a versatile tool for FLASH preclinical research and this comprehensive beam model and workflow was validated to meet the requirements for conducting translational FLASH research.

Yet anOther Dose Algorithm (YODA) for independent computations of dose and dose changes due to anatomical changes

Objective. To assess the viability of a physics-based, deterministic and adjoint-capable algorithm for performing treatment planning system independent dose calculations and for computing dosimetric differences caused by anatomical changes. Approach. A semi-numerical approach is employed to solve two partial differential equations for the proton phase-space density which determines the deposited dose. Lateral hetereogeneities are accounted for by an optimized (Gaussian) beam splitting scheme. Adjoint theory is applied to approximate the change in the deposited dose caused by a new underlying patient anatomy. Main results. The dose engine’s accuracy was benchmarked through three-dimensional gamma index comparisons against Monte Carlo simulations done in TOPAS. For a lung test case, the worst passing rate with (1 mm, 1%, 10% dose cut-off) criteria is 94.55%. The effect of delivering treatment plans on repeat CTs was also tested. For non-robustly optimized plans the adjoint component was accurate to 5.7% while for a robustly optimized plan it was accurate to 4.8%. Significance. Yet anOther Dose Algorithm is capable of accurate dose computations in both single and multi spot irradiations when compared to TOPAS. Moreover, it is able to compute dosimetric differences due to anatomical changes with small to moderate errors thereby facilitating its use for patient-specific quality assurance in online adaptive proton therapy.

Toward real-time, volumetric dosimetry for FLASH-capable clinical synchrocyclotrons using protoacoustic imaging.

Radiation delivery with ultra-high dose rate (FLASH) radiotherapy (RT) holds promise for improving treatment outcomes and reducing side effects but poses challenges in radiation delivery accuracy due to its ultra-high dose rates. This necessitates the development of novel imaging and verification technologies tailored to these conditions. Our study explores the effectiveness of proton-induced acoustic imaging (PAI) in tracking the Bragg peak in three dimensions and in real time during FLASH proton irradiations, offering a method for volumetric beam imaging at both conventional and FLASH dose rates. We developed a three-dimensional (3D) PAI technique using a 256-element ultrasound detector array for FLASH dose rate proton beams. In the study, we tested protoacoustic signal with a beamline of a FLASH-capable synchrocyclotron, setting the distal 90% of the Bragg peak around 35mm away from the ultrasound array. This configuration allowed us to assess various total proton radiation doses, maintaining a consistent beam output of 21 pC/pulse. We also explored a spectrum of dose rates, from 15 Gy/s up to a FLASH rate of 48 Gy/s, by administering a set number of pulses. Furthermore, we implemented a three-dot scanning beam approach to observe the distinct movements of individual Bragg peaks using PAI. All these procedures utilized a proton beam energy of 180 MeV to achieve the maximum possible dose rate. Our findings indicate a strong linear relationship between protoacoustic signal amplitudes and delivered doses (R2=0.9997), with a consistent fit across different dose rates. The technique successfully provided 3D renderings of Bragg peaks at FLASH rates, validated through absolute Gamma index values. The protoacoustic system demonstrates effectiveness in 3D visualization and tracking of the Bragg peak during FLASH proton therapy, representing a notable advancement in proton therapy quality assurance. This method promises enhancements in protoacoustic image guidance and real-time dosimetry, paving the way for more accurate and effective treatments in ultra-high dose rate therapy environments.

Patient-specific deep learning for 3D protoacoustic image reconstruction and dose verification in proton therapy.

Protoacoustic (PA) imaging has the potential to provide real-time 3D dose verification of proton therapy. However, PA images are susceptible to severe distortion due to limited angle acquisition. Our previous studies showed the potential of using deep learning to enhance PA images. As the model was trained using a limited number of patients' data, its efficacy was limited when applied to individualpatients. In this study, we developed a patient-specific deep learning method for protoacoustic imaging to improve the reconstruction quality of protoacoustic imaging and the accuracy of dose verification for individualpatients. Our method consists of two stages: in the first stage, a group model is trained from a diverse training set containing all patients, where a novel deep learning network is employed to directly reconstruct the initial pressure maps from the radiofrequency (RF) signals; in the second stage, we apply transfer learning on the pre-trained group model using patient-specific dataset derived from a novel data augmentation method to tune it into a patient-specific model. Raw PA signals were simulated based on computed tomography (CT) images and the pressure map derived from the planned dose. The reconstructed PA images were evaluated against the ground truth by using the root mean squared errors (RMSE), structural similarity index measure (SSIM) and gamma index on 10 specific prostate cancer patients. The significance level was evaluated by t-test with the p-value threshold of 0.05 compared with the results from the groupmodel. The patient-specific model achieved an average RMSE of 0.014 ( ), and an average SSIM of 0.981 ( ), out-performing the group model. Qualitative results also demonstrated that our patient-specific approach acquired better imaging quality with more details reconstructed when comparing with the group model. Dose verification achieved an average RMSE of 0.011 ( ), and an average SSIM of 0.995 ( ). Gamma index evaluation demonstrated a high agreement (97.4% [ ] and 97.9% [ ] for 1%/3 and 1%/5mm) between the predicted and the ground truth dose maps. Our approach approximately took 6 s to reconstruct PA images for each patient, demonstrating its feasibility for online 3D dose verification for prostate protontherapy. Our method demonstrated the feasibility of achieving 3D high-precision PA-based dose verification using patient-specific deep-learning approaches, which can potentially be used to guide the treatment to mitigate the impact of range uncertainty and improve the precision. Further studies are needed to validate the clinical impact of thetechnique.

Examining Beam Matching in the Commissioning of a Halcyon Accelerator

This study aims to describe the steps needed to be made in developing a commissioning report of a Halcyon linear accelerator utilizing the manufacturer’s golden beam data (GBD) as a reference in making the evaluation. The platform herein has determined the performance alignment of our local machine with the GBD obtained through comprehensive analyses. This made use of the gamma index and relative dose difference. This paper details the methodologies and outcomes of comparing local measurements against GBD during commissioning. For the Halcyon linear accelerator, dosimetric data, including percentage depth doses, dose profiles, and output factors, were acquired using a three-dimensional scanning water tank and various ionization chambers. The GBD were exported from the treatment planning system and compared to the measurements. To evaluate the agreement between the GBD and measurements, gamma index and relative dose difference analyses were conducted. For field sizes greater than 4 × 4 cm2, percentage depth doses and beam profiles, the gamma indices between GBD and measurements were less than 1%/1 mm. The gamma indices were found to be slightly greater for field sizes 2 × 2 cm2 and 4 × 4 cm2, remaining within 2%/2 mm, satisfying the American Association of Physicists in Medicine Medical Physics Practice Guideline 5 for commissioning and quality assurance of mega-volt photon beams. Deviations in the output factor between the GBD and measurements were not significant, remaining within 1%. The GBD data were evaluated in the commissioning of a Halcyon linear accelerator, with analyses being made of the gamma index and relative dose difference. The gamma index analysis is shown to be an effective method for comprehensively evaluating deviations between the GBD and measurements in the beam matching process.

Assessment of radiological hazards of soils from the city of Bitola (Macedonia) and its environs

ABSTRACT To establish the radioactivity level of soils and assess the associated radiological impact on residents, 58 samples from the town of Bitola and its environs were collected. After conducting gross alpha and gross beta measurements with a gas-flow proportional counter as a preliminary screening test, subsequent gamma-spectrometry measurements reveal the presence of 40K, 226Ra, 232Th, and 137Cs in the soil samples as radionuclides with the highest impact. The absorbed gamma dose rate, the annual effective dose, radium equivalent activity, external hazard index, gamma index, excess lifetime cancer risk, and annual gonadal dose were calculated using the obtained activity concentrations of the radionuclides. Upon comparison with similar studies conducted in the Balkan countries, the obtained results for radiation hazard indices were found to be the highest in the region. Coloured maps were generated to visually represent the spatial distribution of the absorbed gamma dose rate in air and annual effective dose, clearly indicating the combined influence of geology and human activities, including the nearby thermoelectric power plant operation.

Assessment of the level and risk of radioactive hazards in coastal sediments in northern Vietnam

ABSTRACT Radioactivity in coastal sediments in northern Vietnam was examined using data from five sediment cores to assess radioactivity concentrations and radiation risk indices. Radiation risk indices included radium equivalent activity (Raeq), the absorbed dose rate (ADR), the annual effective dose equivalent (AEDE), the activity utilization index (AUI), the external hazard index (Hex), the representative level gamma index (Iγr), and the annual gonadal effective dose rate (AGDE). The radioactivity concentrations of 40K, 232Th, 226Ra, 238U, and 137Cs were 567, 56.1, 35.1, 37.9, and 1.18 Bq/kg, respectively. The average concentrations of 40K, 232Th, 226Ra, and 238U were above the global average at five sites, except for 137Cs, which was low. The Raeq, Hex, and AUI indices were below the recommended values, while the AEDE, ADR, AGDE, and Iγr indices were above the recommended values. Moreover, 40K, 232Th, 226Ra, and 238U had significant impacts on the radiation hazard indices Raeq, ADR, AEDE, Iγr, AUI, Hex, and AGDE. There are three coastal sediment groups on the northern coast of Vietnam: Group 1 has a higher radioactivity and radiation risk index than Group 2 but a lower value than Group 3. Group 3 had the highest radioactivity and radiation risk index. The values of 40K, 232Th, 226Ra, and 238U and the ADR, AUI, Iγr, and AGDE indices in the sediment threaten the living environment.

Monte Carlo Simulation for the Radixact™ Tomotherapy Linac Using EGSnrc.

When exact information regarding the treatment head and initial electron beam is available, the Monte Carlo (MC) approach can properly simulate any linear accelerator. However, manufacturers seldom offer information such as the incident electron beam's energy, radial intensity (spot size), or angular spread. This research aims to forecast these features and verify an MC-simulated linear accelerator model using measurements. The BEAMnrc code simulated a 6 MV photon beam from a Radixact™ Tomotherapy Linac. Percentage depth dose and beam profile calculations were conducted using DOSYXZnrc by various electron energies and spot sizes and compared to measurements using a Gamma index with two distinct criterion sets. Furthermore, the fine-tuned electron energy and spot size profiles were created to minimize any disparities using distinct angle spreads. Finally, the output factors (OFs) for various field sizes were compared. The MC model's fine-tuned electron energy was determined to be 5.8 MeV, with 88.6% of the calculation points passing the 1%/1 mm γ test. A circular radial intensity of 1.4 mm best represented the 6 MV photon beam regarding spot size. Furthermore, a mean angular spread of 0.05 reduced the disparity in cross-field profile between computation and measurement. The most considerable disparities between the MC model OFs and observations were 1.5%. Using the BEAMnrc code, a reliable MC model of the Radixact™ Tomotherapy Linac can be created, as shown in this paper. This model can be used to compute dose distributions with confidence.

Evaluation of Ethos intelligent optimization engine for left locally advanced breast cancer.

To evaluate the feasibility to use a standard Ethos planning template to treat left-sided breast cancer with regional lymph nodes. The tuning cohort of 5 patients was used to create a planning template. The validation cohort included 15 patients treated for a locally advanced left breast cancer randomly enrolled. The Ethos planning template was tuned using standard 3 partial arc VMAT and two collimator rotation configurations: 45/285/345° and 30/60/330°. Re-planning was performed automatically using the template without editing. The study was conducted with a schedule of 42.3 Gy in 18 fractions to the breast/chestwall, internal mammary chain (IMC) and regional lymph nodes ("Nodes"). The PTV was defined as a 3D extension of the CTV with a margin of 7mm, excluding the 5mm below the skin. The manual treatment plans were performed using Eclipse treatment planning system with AAA and PO algorithms (v15.6) and a manual arc VMAT configuration and imported in Ethos TPS (v1.1) for a dose calculation with Ethos Acuros algorithm. The automated plans were compared with the manual plans using PTV and CTV coverage, homogeneity and conformity indices (HI and CN) and doses to organs at risk (OAR) via DVH metrics. For each plan, the patient quality assurance (QA) were performed using Mobius3D and gamma index. Finally, two breast radiation oncologists performed a blinded assessment of the clinical acceptability of each of the three plans (manual and automated) for each patient. The manual and automated plans provided suitable treatment planning as regards dose constraints. The dosimetric comparison showed the CTV_breast D99% were significantly improved with both automated plans (p< 0,002) while PTV coverage was comparable. The doses to the organs at risk were equivalent for the three plans. Concerning treatment delivery, the Ethos-45° and Ethos-30° plans led to an increase in MUs compared to the manual plans, without affecting the beam on time. The average gamma index pass rates remained consistently above 98% regardless of the type of plan utilized. In the blinded evaluation, clinicians 1 and 2 assessed 13 out of 15 plans for Ethos 45° and 11 out of 15 plans for Ethos 30° as clinically acceptable. Using a standard planning template for locally advanced breast cancer, the Ethos TPS provided automated plans that were clinically acceptable and comparable in quality to manually generated plans. Automated plans also dramatically reduce workflow and operator variability.

Motion-induced dose perturbations in photon radiotherapy and proton therapy measured by deformable liver-shaped 3D dosimeters in an anthropomorphic phantom

Background and purposeThe impact of intrafractional motion and deformations on clinical radiotherapy delivery has so far only been investigated by simulations as well as point and planar dose measurements. The aim of this study was to combine anthropomorphic 3D dosimetry with a deformable abdominal phantom to measure the influence of intra-fractional motion and gating in photon radiotherapy and evaluate the applicability in proton therapy. Material and methodsAn abdominal phantom was modified to hold a deformable anthropomorphic 3D dosimeter shaped as a human liver. A liver-specific photon radiotherapy and a proton pencil beam scanning therapy plan were delivered to the phantom without motion as well as with 12 mm sinusoidal motion while using either no respiratory gating or respiratory gating. ResultsUsing the stationary irradiation as reference the local 3 %/2 mm 3D gamma index pass rate of the motion experiments in the planning target volume (PTV) was above 97 % (photon) and 78 % (proton) with gating whereas it was below 74 % (photon) and 45 % (proton) without gating. ConclusionsFor the first time a high-resolution deformable anthropomorphic 3D dosimeter embedded in a deformable abdominal phantom was applied for experimental validation of both photon and proton treatments of targets exhibiting respiratory motion. It was experimentally shown that gating improves dose coverage and the geometrical accuracy for both photon radiotherapy and proton therapy.