Dose Calculation Accuracy Research Articles

Improved heterogeneity handling in the collapsed cone dose engine for brachytherapy.

Model-based dose calculation algorithms (MBDCA), such as the Advanced Collapsed cone Engine (ACE) in Oncentra Brachy® can be used to overcome the limitations of the TG-43 formalism. ACE is a point kernel superposition algorithm that calculates the total dose separated into primary, first-scatter, and multiple-scatter dose. Albeit ACE yields accurate results under most circumstances, several studies have reported underestimations of the dose to cortical bone. These underestimations are likely caused by approximations in the handling of multiple-scatter dose for non-water media. Such would result in noticeable deviations where the multiple-scatter is a considerable fraction of the total dose, that is, at greater distances from the source. To improve and test the accuracy of the multiple-scatter dose component in the ACE algorithm to remedy its inaccuracy for non-water geometries. A careful analysis of the transport and absorption of the multiple-scatter energy fluence revealed an inconsistency in the scaling of energy absorption ratios for non-water media of the multiple-scatter kernel. We implemented an updated algorithm version, ACEcorr, and tested it for three different geometries. All had a single 192Ir-source at the center of a cubic water phantom with a box-shaped heterogeneity of either cortical bone or air, positioned at different distances from the source. Dose distributions for the three cases were calculated with ACE and ACEcorr and compared to Monte Carlo simulations, using the percentage dose difference ratio as figure-of-merit. All dose calculation methods scored separately the dose deposited by primary, first-scattered, and multiple-scattered photons. The accuracy of the updated algorithm ACEcorr was superior to ACE. In the cortical bone heterogeneity, the mean percentage dose difference ratio for the total dose improved from to (in the worst case) by our update. Less impact was seen in the air heterogeneity, where both ACE and ACEcorr deviated less than 2% from the Monte Carlo results. The algorithm update mainly concerns the multiple-scattered dose component, but an accompanying data processing update also had a small effect ( 0.5% difference) on the primary and first-scattered dose. The calculation times were not affected. The updates to ACE improved the accuracy of multiple-scatter dose calculation for non-water media, without increasing calculation times.

In silicodosimetry for a prostate cancer treatment using198Au nanoparticles.


To estimate dose rates delivered by using radioactive198Au nanoparticles for prostate cancer nanobrachytherapy, identifying contribution by photons and electrons emmited from the source.
Approach:
Utilizingin silicomodels, two different anatomical representations were compared: a mathematical model and a unstructured mesh model based on the International Commission on Radiological Protection (ICRP) Publication 145 phantom. Dose rates by activity were calculated to the tumor, and nearby healthy tissues, including healthy prostate tissue, urinary bladder wall and rectum, using Monte Carlo code MCNP6.2.
Main results:
Results indicate that both models provide dose rate estimates within the same order of magnitude, with the mathematical model overestimating doses to the prostate and bladder by approximately 20% compared to the unstructured mesh model. The discrepancies for the tumor and rectum were below 4%. Photons emmited from the source were defined as the primary contributors to dose to other organs, while 97.9% of the dose to the tumor was due to electrons emmited from the source.
Significance:
Our findings emphasize the importance of model selection in dosimetry, particularly the advantages of using realistic anatomical phantoms for accurate dose calculations. The study demonstrates the feasibility and effectiveness of198Au nanoparticles in achieving high dose concentrations in tumor regions while minimizing exposure to surrounding healthy tissues. Beta emissions were found to be predominantly responsible for tumor dose delivery, reinforcing the potential of198Au nanoparticles in localized radiation therapy. We advocate for using realistic body phantoms in further research to enhance reliability in dosimetry for nanobrachytherapy, as the field still lacks dedicated protocols.&#xD.

The dosimetric accuracy of a commercial model-based dose calculation algorithm in modeling a six-groove direction modulated brachytherapy tandem applicator

Objective.With advancements in high-dose rate brachytherapy, the clinical translation of intensity modulated brachytherapy (IMBT) innovations necessitates utilization of model-based dose calculation algorithms (MBDCA) for accurate and rapid dose calculations. This study uniquely benchmarks a commercial MBDCA, BrachyVision ACUROSTM(BVA), against Monte Carlo (MC) simulations, evaluating dose distributions for a novel IMBT applicator, termed as thesix-grooveDirection Modulated Brachytherapy (DMBT) tandem, expanding beyond previous focus on partially shielded vaginal cylinder applicators, through a novel methodology.Approach.The DMBT tandem applicator, made of a tungsten alloy with six evenly spaced grooves, was simulated using the GEANT4 MC code. Subsequently, two main scenarios were created using the BVA and reproduced by the MC simulations: 'Source at the Center of the Water Phantom (SACWP)' and 'Source at the Middle of the Applicator (SAMA)' for three cubical virtual water phantoms (20 cm)3, (30 cm)3, and (40 cm)3. A track length estimator was utilized for dose calculation and 2D/3D scoring were performed. The difference in isodose surfaces/lines (i.e. coverage) at each voxel,ΔDIsodose Levels/Lines, was thus calculated for relevant normalization points (rref).Results.The coverage was comparable, based on 2D scoring, between the BVA and MC isodose surfaces/lines for the region of clinical relevance, (i.e. within 5 cm radius from the source) withΔDIsodose Lines(rref: 1 cm from the source) falling within 2% for the two scenarios for all phantom sizes. For the phantom (20 cm)3,ΔDIsodose Levels(3D scoring) recorded the range [-3.0% +6.5%] ([-7.4% +7.3%]) for 95% of the voxels of the same scoring volume for the SACWP (SAMA) scenario.Significance.The results indicated that the BVA could render comparable coverage as compared to the MC simulations in the region of clinical relevance for different phantom sizes.ΔDIsodose Linesmay offer an advantageous metric for evaluation of MBDCAs in clinical setting.

Assessing the robustness of dose distributions in carbon ion prostate radiotherapy using a fast dose evaluation system.

We developed a software program for swiftly calculating dose distributions for carbon ion beams. This study aims to evaluate the accuracy of dose calculations using this software and assess the robustness of dose distribution in treating prostate cancer. At the Osaka Heavy Ion Therapy Center, markers are inserted into the prostate gland and used for position verification. To account for geometric changes along the beam path due to marker translation, a beam-specific planning target volume (bsPTV) is set for each beam. To validate the accuracy of the dose calculations using the developed software, dose distributions for prostate and sarcoma cases were calculated and compared with the treatment planning system. To assess the robustness of the dose distribution, position verification data from 346 cases were utilized to reproduce dose distributions for three matching methods: bone matching, widely adopted in most particle therapy centers; marker translation, which involves direct translation to markers without bone matching; and marker translation after bone matching. The coverage of the target (D99 of clinical target volume (CTV)) was assessed to evaluate the robustness of the dose distribution. Additionally, statistical analyses were conducted for the dose distributions of each matching method. The dose calculation for a single condition can be completed very quickly. Statistical analysis revealed significant differences among dose distributions considering the three matching methods. When irradiation was performed with bone matching only, the D99 was reduced by more than 10% in approximately 7.5% of cases, making it as the poorest among the three matching methods. However, there was no significant reduction in target coverage with the other two methods. We have demonstrated the accuracy of the developed software for rapidly calculating dose distributions for carbon ion beams and confirmed the robustness of the dose distributions based on the bsPTV.

Exploring dual energy CT synthesis in CBCT-based adaptive radiotherapy and proton therapy: application of denoising diffusion probabilistic models

Background.Adaptive radiotherapy (ART) requires precise tissue characterization to optimize treatment plans and enhance the efficacy of radiation delivery while minimizing exposure to organs at risk. Traditional imaging techniques such as cone beam computed tomography (CBCT) used in ART settings often lack the resolution and detail necessary for accurate dosimetry, especially in proton therapy.Purpose.This study aims to enhance ART by introducing an innovative approach that synthesizes dual-energy computed tomography (DECT) images from CBCT scans using a novel 3D conditional denoising diffusion probabilistic model (DDPM) multi-decoder. This method seeks to improve dose calculations in ART planning, enhancing tissue characterization.Methods.We utilized a paired CBCT-DECT dataset from 54 head and neck cancer patients to train and validate our DDPM model. The model employs a multi-decoder Swin-UNET architecture that synthesizes high-resolution DECT images by progressively reducing noise and artifacts in CBCT scans through a controlled diffusion process.Results.The proposed method demonstrated superior performance in synthesizing DECT images (High DECT MAE 39.582 ± 0.855 and Low DECT MAE 48.540± 1.833) with significantly enhanced signal-to-noise ratio and reduced artifacts compared to traditional GAN-based methods. It showed marked improvements in tissue characterization and anatomical structure similarity, critical for precise proton and radiation therapy planning.Conclusions.This research has opened a new avenue in CBCT-CT synthesis for ART/APT by generating DECT images using an enhanced DDPM approach. The demonstrated similarity between the synthesized DECT images and ground truth images suggests that these synthetic volumes can be used for accurate dose calculations, leading to better adaptation in treatment planning.

A deep learning-based dose calculation method for volumetric modulated arc therapy

BackgroundVolumetric modulated arc therapy (VMAT) planning optimization involves iterative adjustment of numerous parameters, and hence requires repeatedly dose recalculation. In this study, we used the deep learning method to develop a fast and accurate dose calculation method for VMAT.MethodsThe classical 3D UNet was adopted and trained to learn the physics principle of dose calculation. The inputs included the projected fluence map (FM), computed tomography (CT) images, the radiological depth and the source-to-voxel distance (SVD). The projected FM was generated by projecting the accumulated FM between two consecutive control points (CPs) onto the patient’s anatomy. The accumulated FM was calculated by simulating the movement of the multi-leaf collimator (MLC) from one CP to the next. The dose, calculated by the treatment planning system (TPS), was used as ground truth. 51 head and neck VMAT plans were used, with 43, 1 and 7 cases as training, validation, and testing datasets, respectively. Correspondingly, 7182, 180 and 1260 CP samples were included in the training, validation, and testing datasets.ResultsThis presented method was evaluated by comparing the derived dose distribution to the TPS calculated dose distribution. The dose profiles coincided for both the single CP and the entire plan (summation of all CPs). But the network derived dose was smoother than the TPS calculated dose. Gamma analysis was performed between the network derived dose and the TPS calculated dose. The average gamma pass rate was 96.56%, 98.75%, 98.03% and 99.30% under the criteria of 2% (tolerance) -2 mm (distance to agreement, DTA). 2%-3 mm, 3%-2 mm and 3%-3 mm. No significant difference was observed on the critical indices including the max, mean dose, and the relative volume covered by the 2000 cGy, 4000 cGy and the prescription dose. For one CP, the average computational time of the network and TPS was 0.09s and 0.53s. And for one patient, the average time was 16.51s and 95.60s.ConclusionThe dose distribution derived by the network showed good agreement with the TPS calculated dose distribution. The computational time was reduced to approximate one-sixth of its original duration. Therefore the presented deep learning-based dose calculation method has the potential to be used for planning optimization.

Development of an algorithm for proton dose calculation in magnetic fields.

The advantages of proton therapy can be further enhanced with online magnetic resonance imaging (MRI) guidance. One of the challenges in the realization of MRI-guided proton therapy (MRPT) is accurately calculating the radiation dose in the presence of magnetic fields. This study aims to develop an efficient and accurate proton dose calculation algorithm adapted to the presence of magnetic fields. An analytical-numerical radiation dose calculation algorithm, Proton and Ion Dose Engine (PRIDE), was developed. The algorithm combines the pencil beam algorithm (PBA) with a novel iterative voxel-based ray-tracing algorithm. The new ray-tracing method uses fewer assumptions and ensures broader applicability for proton beam trajectory prediction in magnetic fields, and has been compared to Wolf's method and Schellhammer's method. The accuracy of PRIDE algorithm was validated on three phantoms and two practical plans (one single-field water plan and one prostate tumor plan) in different magnetic field strengths up to 3.0 T. The validation was performed by comparing the results against the Monte Carlo (MC) simulations, using the global gamma index criteria of 2%/2mm and 3%/3mm with a 10% threshold. PRIDE showed good agreement with MC in homogeneous and slab heterogeneous phantom, achieving gamma passing rates (%GPs) above 99% for 2%/2mm criteria when magnetic field strength is not greater than 1.5 T. Although the agreement decreased for scenarios involving high proton energy (240 MeV) and strong magnetic field (3.0 T), the 2%/2mm %GPs still remained above 98%. In lateral heterogeneous phantom, the accuracy of PRIDE decreased due to the PBA's limitation. For the two practical plans in different magnetic fields, %GPs exceeded 98% and 99% for 2%/2mm and 3%/3mm criteria, respectively. PRIDE can perform efficient and accurate proton dose calculation in magnetic fields up to 3.0 T, and is expected to work as a useful tool for proton dose calculation in MRPT.

Dose calculation accuracy of a new high-performance ring-gantry CBCT imaging system for prostate and lung cancer patients

Background and purposeThe recently introduced high-performance CBCT imaging system called HyperSight offers improved Hounsfield units (HU) accuracy, a larger CBCT field-of-view and improved image quality compared to conventional ring gantry CBCT, possibly enabling treatment planning on CBCT imaging directly. In this study, we evaluated whether the dose calculation accuracy on HyperSight CBCT was sufficient for treatment planning in prostate and lung cancer patients. Materials and methodsHyperSight CBCT was compared to planning CT in terms of HU-to-mass density (MD) calibration curves. For twenty prostate patients and twenty lung patients, differences in DVH parameters, and 3D global gamma between dose distributions calculated on planning CT and free breathing HyperSight CBCT were evaluated. For this purpose, HyperSight CBCT acquired at the first fraction was rigidly registered to the pCT, delineations from the CT were propagated and the dose was recalculated on the HyperSight CBCT. ResultsFor each insert of the HU-to-MD calibration phantom, the HU values of HyperSight CBCT and pCT agreed within 35 HU. For prostate maximum deviations in PTV Dmean, V95% and V107% were 1.8 %, −1.1 % and < 0.1 % respectively. For lung PTV V95% was generally lower (median −1.1 %) and PTV V107% was generally higher (median 1.1 %) on HyperSight CBCT due to breathing motion artifacts. The average (±SD) 2 %/2mm gamma pass rate was 98.7 %±1.2 % for prostate cancer patients and 96.2 %±2.1 % for lung cancer patients. ConclusionHyperSight CBCT enabled accurate dose calculation for prostate cancer patients, without implementation of a specific HyperSight CBCT-to-MD curve. For lung cancer patients, breathing motion hampered accurate dose calculations.

Proton dose calculation on cone-beam computed tomography using unsupervised 3D deep learning networks

Background and PurposePoor image quality of cone-beam computed tomography (CBCT) images can hinder proton dose calculation to assess the influence of anatomy changes. The aim of this study was to evaluate image quality and proton dose calculation accuracy of synthetic CTs generated from CBCT using unsupervised 3D deep-learning networks. Materials and methodsA total of 102 head-and-neck cancer patients were used to train (N=82) and test (N=20) i) a cycle-consistent generative adversarial network, ii) a contrastive unpaired translation, and iii) a fusion of the two (CycleCUT). For patients in the test set, a repeat CT was deformably registered to a same-day CBCT to create a ground-truth CT for comparison. The proton plan was re-calculated on the ground-truth CT and synthetic CTs. The image quality of the synthetic CTs was evaluated using peak signal-to-noise ratio, structural similarity index measure, mean error, and mean absolute error (MAE). Proton dose calculation accuracy was assessed through 3D gamma analysis and dose-volume-histogram parameters. ResultsAll synthetic CTs accurately preserved the CBCT anatomy (verified by visual inspection) while improving the image quality. The CycleCUT network had slightly improved image quality compared to the other networks (MAE in body: 53 Hounsfield units (HU) vs. 54/55 HU). All networks had similar proton dose calculation accuracy with gamma passing rate above 97%. ConclusionsAll three evaluated networks generated synthetic CT images with dose distributions comparable to those of conventional fan-beam CT. The synthetic CT generation was fast, making all networks feasible for adaptive proton therapy.

Heavy metal in radiation therapy: A simple method to differentiate hip prosthesis materials.

In recent years, the number of hip replacement patients receiving radiation therapy has steadily increased. In parallel, strategies have been developed to reduce metal artifacts in computed tomography (CT) images and improve the accuracy of dose calculation algorithms. However, in certain situations, knowledge of the type of prosthesis material is required to accurately determine the dose distribution. This study aims to identify physical materials in hip prostheses to correctly assign them in the treatment planning system and improve dose calculation accuracy. We first verified the validity of the extended CT mass density calibration curve measured on titanium (Ti) and stainless steel (SS) metal inserts of two different diameters. Then using dedicated reference objects of various circular diameters, we developed a method based on interpolation functions to differentiate between Ti and SS material groups. Forty data sets from 18 patients were used to validate our method on two different reconstruction kernels: a standard Br44f and the electron DirectDensity (Sd40f) kernels from Siemens. Hounsfield units (HU) of Ti and SS inserts were found to vary widely depending on insert diameter, CT spectrum, and reconstruction kernels due to cupping artifacts. The largest HU difference (-79%) was obtained for SS at 70kV with Br44f when the diameter increased from 8 to 30mm. Therefore, under these conditions, the extended CT-density calibration curve is not recommended for heavy metal density determination. Using our interpolation-based method, we achieved excellent detection (100%) and material differentiation (100%) results for stems in both reconstruction kernels. At CT energies between 110 and 140kV, the detection and material differentiation rates were 93.3% and 92.9% for the heads and 93.3% and 92.9% for the acetabular cups, respectively, with the Br44f. Similarly, the use of Sd40f resulted in detection and differentiation rates of 94.7% and 100% for the heads and 100% and 95.0% for the acetabular cups, respectively. This method makes it possible to differentiate between hip prosthesis materials and correctly assign them to the Ti or SS group without prior knowledge of the prosthesis type, regardless of the reconstruction kernels. In combination with the Acuros XB (Varian) or Monte Carlo dose algorithms, excellent dosimetric accuracy can be achieved even in the vicinity of hip prostheses. By performing basic measurements, the method can be adapted to other CT units and reconstruction kernels, replacing the use of an extended CT-density calibration curve.

An international film dosimetry intercomparison to establish a multi-center audit framework.

In 2021, a Technical Meeting was hosted by the International Atomic Energy Agency (IAEA) where it was recommended that a standardized method for assessing the accuracy of film dose calculations should be established. To design an audit that evaluates the accuracy of film dosimetry processes. To propose a framework for identifying out-of-tolerance results and to perform an international pilot study to test the audit design. Six members of an international Dosimetry Audit Network (DAN) developed an audit for radiochromic film dosimetry. A single host center provided the materials to each participating DAN member to conduct the audits. Materials included: (1) a set of two irradiated audit films (10 Sq: 10cm × 10cm, 15 Sq: 15cm × 15cm), (2) a reference calibration film set, and (3) a blank sheet of film. The participants were blinded to the dose and tasked with producing dose maps using their standard film dosimetry process. Average Region-Of-Interest (ROI: 2cm × 2cm) dose was measured from the dose maps and compared to the known dose. In the audit, all participants used their local scanning and software protocols. Film calibration was performed in two distinct ways: (1) using a calibration film set which was provided by the host center and (2) using a calibration film set which was locally irradiated. Several variations of the audit were also performed to examine how scanning and software processing can affect film dosimetry results. In the first variation of the audit (VariantA), a set of film scans was processed using five different software solutions. In the second variation of the audit (VariantB), all films were scanned on the same scanner and processed using two in-house software solutions. Taking one film scan from each participant, the standard deviations (1σ) (SD) in the dose returned from the host calibration and returned from the local calibration were±7.2% and±6.5% respectively, with variations from -12.4% to 12.9% of the known dose. The larger dose variations in the data set were attributed to the corrections applied for variations in scanner brightness during processing and incorrectly assigned calibration doses. When the raw image data set was processed by an expert user of each software solution (VariantA) the SDs were±2.7% and±3.7% for in-house and vendor-based software, respectively. When the films were scanned on a single scanner and processed with the two in-house software solutions (VariantB) the results had a SD of±2.3%. An audit has been designed and tested for radiotherapy film dosimetry at an international level. A framework for diagnosing issues within a film dosimetry process has been proposed that could be used to audit centers that use film as a dosimeter. Incorporating quality assurance throughout the film process is important in obtaining accurate and consistent film dosimetry. A better understanding of vendor-based software systems is necessary for users to process accurate and consistent film dosimetry.

Technical Note: Investigating of dosimetric leaf gap and leaf transmission factor variations across gantry and collimator angles in volumetric modulation arc therapy.

This study investigates the influence of gantry and collimator angles on the dosimetric leaf gap (DLG) and leaf transmission factor (LTF) in a Varian LINAC equipped with rounded-end multi-leaf collimators (MLCs). While Varian guidelines recommend DLG measurements at zero degrees for both gantry and collimator, this research aims to address the knowledge gap by assessing DLG and LTF variations at different gantry and collimator angles. Measurements were conducted using a Varian TrueBeam LINAC with a Millennium 120-leaf MLC and Eclipse TPS version 16.1. The beams utilized in this study had energies of 6 MV, 10 MV, 6 FFF, and 10 FFF. LTF and DLG were determined using ionization chambers in solid water phantoms at various gantry angles (0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315°). For each gantry angle, measurements were also taken at various collimator angles (0°, 45°, 90°, and 315°). Dosimetric impacts were evaluated through VMAT Picket Fence tests and patient-specific verification using portal dosimetry for 10 clinical VMAT plans. LTF values showed no significant variation across gantry and collimator angles. However, DLG values exhibited notable differences depending on the gantry angle and were independent of the collimator angle. The highest DLG value was observed at a gantry angle of 270 degrees, while the lowest was at 90 degrees. The AXB DLGAverage (averaging seven measurements of DLGs at different gantry angles) model demonstrated the best agreement between measured and calculated dose distributions, indicating the importance of considering averaged DLG values across multiple gantry angles for accurate dose calculations. Our study highlights the variability of DLG with gantry angle alterations, contrary to Varian guidelines recommending DLG measurements at zero gantry angle only. We advocate for utilizing an averaged DLG value from measurements across multiple gantry angles, as outlined in our methodology.

Development of a proton CT imaging system using scintillator-based range detection.

The accuracy of proton therapy and preclinical proton irradiation experiments is susceptible to proton range uncertainties, which partly stem from the inaccurate conversion between CT numbers and relative stopping power (RSP). Proton computed tomography (PCT) can reduce these uncertainties by directly acquiring RSP maps. This study aims to develop a novel PCT imaging system based on scintillator-based proton range detection for accurate RSP reconstruction. The proposed PCT system consists of a pencil-beam brass collimator with a 1mm aperture, an object stage capable of translation and 360° rotation, a plastic scintillator for dose-to-light conversion, and a complementary metal oxide semiconductor (CMOS) camera for light distribution acquisition. A calibration procedure based on Monte Carlo (MC) simulation was implemented to convert the obtained light ranges into water equivalent ranges. The water equivalent path lengths (WEPLs) of the imaged object were determined by calculating the differences in proton ranges obtained with and without the object in the beam path. To validate the WEPL calculation, measurements of WEPLs for eight tissue-equivalent inserts were conducted. PCT imaging was performed on a custom-designed phantom and a mouse, utilizing both 60 and 360 projections. The filtered back projection (FBP) algorithm was employed to reconstruct the RSP from WEPLs. Image quality was assessed based on the reconstructed RSP maps and compared to reference and simulation-based reconstructions. The differences between the calibrated and reference ranges of 110-150 MeV proton beams were within 0.18mm. The WEPLs of eight tissue-equivalent inserts were measured with accuracies better than 1%. Phantom experiments exhibited good agreement with reference and simulation-based reconstructions, demonstrating average RSP errors of 1.26%, 1.38%, and 0.38% for images reconstructed with 60 projections, 60 projections after penalized weighted least-squares algorithm denoising, and 360 projections, respectively. Mouse experiments provided clear observations of mouse contours and major tissue types. MC simulation estimated an imaging dose of 3.44 cGy for decent RSP reconstruction. The proposed PCT imaging system enables RSP map acquisition with high accuracy and has the potential to improve dose calculation accuracy in proton therapy and preclinical proton irradiation experiments.

1651: The impact of ground-glass opacities on dose calculation accuracy for lung SBRT

1651: The impact of ground-glass opacities on dose calculation accuracy for lung SBRT

Development and validation of a comprehensive S-value database for small animal internal dosimetry in nuclear medicine using the DM_Bra mouse phantom

Animal models are essential in the development of new radiopharmaceuticals in nuclear medicine, particularly for accurate dose calculation in small animal internal dosimetry. This study presents a comprehensive dataset of S-values for eleven commonly used radionuclides, calculated using the DM_Bra mouse phantom with the GATE Monte Carlo simulation code. To validate our approach, we first compared S-values obtained from the DM_Bra phantom with published values derived from the Digimouse phantom using a Tc-99 m source. The differences between the two phantoms range from 0.68% to 12.45% for self-irradiation and from 0.15% to 4.19% for cross-irradiation when the source is the stomach. These results demonstrate good agreement with reference data, supporting the reliability of our dataset. We then expanded our analysis by generating S-values for additional radionuclides, reflecting their usage in both diagnostic and therapeutic applications. Furthermore, to assess the impact of varying mouse geometries on S-values, the DM_Bra phantom (26.9 g) was rescaled to represent two other mouse sizes (19.6 g and 35.9 g). The statistical uncertainty associated with all these S-values remains below 2%. This study offers a valuable resource for internal dosimetry in mice, providing detailed S-values for a wide range of radionuclides and organ geometries, which can be used in small animal PET and SPECT studies.

Technical note: MR image-based synthesis CT for CyberKnife robotic stereotactic radiosurgery

The purpose of this study is to investigate whether deep learning-based sCT images enable accurate dose calculation in CK robotic stereotactic radiosurgery. A U-net convolutional neural network was trained using 2446 MR-CT pairs and used it to translate 551 MR images to sCT images for testing. The sCT of CK patient was encapsulated into a quality assurance (QA) validation phantom for dose verification. The CT value difference between CT and sCT was evaluated using mean absolute error (MAE) and the statistical significance of dose differences between CT and sCT was tested using the Wilcoxon signed rank test. For all CK patients, the MAE value of the whole brain region did not exceed 25 HU. The percentage dose difference between CT and sCT was less than ±0.4% on GTV (D2(Gy), −0.29%, D95(Gy), −0.09%), PTV (D2(Gy), −0.25%, D95(Gy), −0.10%), and brainstem (max dose(Gy), 0.31%). The percentage dose difference between CT and sCT for most regions of interest (ROIs) was no more than ±0.04%. This study extended MR-based sCT prediction to CK robotic stereotactic radiosurgery, expanding the application scenarios of MR-only radiation therapy. The results demonstrated the remarkable accuracy of dose calculation on sCT for patients treated with CK robotic stereotactic radiosurgery.

Technical note: Phantom-based evaluation of CBCT dose calculation accuracy for use in adaptive radiotherapy.

High-quality 3D-anatomy of the day is needed for treatment plan adaptation in radiotherapy. For online x-ray-based CBCT workflows, one approach is to create a synthetic CT or to utilize a fan-beam CT with corresponding registrations. The former potentially introduces uncertainties in the dose calculation if deformable image registration is used. The latter can introduce burden and complexity to the process, the facility, and thepatient. Using the CBCT of the day, acquired on the treatment device, for direct dose calculation and plan adaptation can overcome these limitations. This study aims to assess the accuracy of the calculated dose on the CBCT scans acquired on a Halcyon linear accelerator equipped withHyperSight. HyperSight's new CBCT reconstruction algorithm includes improvements in scatter correction, HU calibration of the imager, and beam shape adaptation. Furthermore, HyperSight introduced a new x-ray detector. To show the effect of the implemented improvements, gamma comparisons of 2%/2mm, 2%/1mm, and 1%/1mm were made between the dose distribution in phantoms calculated on the CBCT reconstructions and the simulation CT scans, considering this the standard of care. The resulting gamma passing rates were compared to those obtained with the Halcyon 3.0 reconstruction and hardware without HyperSight's technologies. Various anatomical phantoms for dosimetric evaluations on brain, head and neck, lung, breast, and prostate cases have been used in thisstudy. The overall results demonstrated that HyperSight outperformed the Halcyon 3.0 version. Based on the gamma analysis, the calculated dose using HyperSight was closer to the CT scan-based doses than the calculated dose using iCBCT Halcyon 3.0 for most cases. Over all plans and gamma criteria, Halcyon 3.0 achieved an average passing rate of 92.9%, whereas HyperSight achieved 98.1%. Using HyperSight CBCT images for direct dose calculation, for example, in (online) plan adaptation, seems feasible for the investigatedcases.

A methodology for computationally generating phase space files for Monte Carlo simulations applied to treatment plans for medical linear accelerators

The application of Monte Carlo (MC) simulation in the context of Medical Linear Accelerator (LinAc) treatment planning has increased in recent decades owing to its accuracy in dose calculations. The Multileaf Collimator (MLC), a component of the LinAc heads, plays an essential role by allowing the precise customization of the treatment beam's shape, effectively targeting the tumor area while minimizing radiation exposure to surrounding healthy structures. During a jaws static treatment, this MLC configuration varies for each angular position of the accelerator gantry, while the rest of the LinAc geometry remains static. To address the operation of the accelerator during the treatment planning avoiding the need of computationally intensive and repetitive simulations, phase-space files (PSF) are widely employed in LinAc MC calculations. This study aims to introduce and validate a methodology for the computational generation of PSFs specifically defined just below the MLC. These PSFs will assume the appropriate shape corresponding to the angle at which the accelerator gantry is positioned during treatment. The core of this methodology involves the creation of a comprehensive database containing precalculated probability functions derived from MC. In order to validate the methodology, simulated dose values of a LinAc emitting a 6 MV photon beam have been employed. The results have been tested against experimental data, and compared with the results from complete simulations, yielding PSFs of varying shapes. Finally, this study reveals that the results obtained by comparing organ dose values computed from the generated PSFs to those from the reference PSF are statistically compatible. This innovative method not only offers a valuable tool for optimizing LinAc treatment planning but also underscores the importance of accurate dose calculations in the field of radiation therapy.

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.

Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report

Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomography (CT) is integral for treatment planning, offering electron density data crucial for accurate dose calculations. However, accurately representing patient anatomy is challenging, especially in adaptive radiotherapy, where CT is not acquired daily. Magnetic resonance imaging (MRI) provides superior soft-tissue contrast. Still, it lacks electron density information, while cone beam CT (CBCT) lacks direct electron density calibration and is mainly used for patient positioning.Adopting MRI-only or CBCT-based adaptive radiotherapy eliminates the need for CT planning but presents challenges. Synthetic CT (sCT) generation techniques aim to address these challenges by using image synthesis to bridge the gap between MRI, CBCT, and CT. The SynthRAD2023 challenge was organized to compare synthetic CT generation methods using multi-center ground truth data from 1080 patients, divided into two tasks: (1) MRI-to-CT and (2) CBCT-to-CT. The evaluation included image similarity and dose-based metrics from proton and photon plans.The challenge attracted significant participation, with 617 registrations and 22/17 valid submissions for tasks 1/2. Top-performing teams achieved high structural similarity indices (≥0.87/0.90) and gamma pass rates for photon (≥98.1%/99.0%) and proton (≥97.3%/97.0%) plans. However, no significant correlation was found between image similarity metrics and dose accuracy, emphasizing the need for dose evaluation when assessing the clinical applicability of sCT.SynthRAD2023 facilitated the investigation and benchmarking of sCT generation techniques, providing insights for developing MRI-only and CBCT-based adaptive radiotherapy. It showcased the growing capacity of deep learning to produce high-quality sCT, reducing reliance on conventional CT for treatment planning.