Distance To Agreement Research Articles

Dosimetric validation of intensity-modulated bolus electron conformal therapy planning and delivery using an anthropomorphic cylindrical head phantom.

This work investigated the dosimetric accuracy of the intensity-modulated bolus electron conformal therapy (IM-BECT) planning and delivery process using the decimal ElectronRT (eRT) treatment planning system. An IM-BECT treatment plan was designed using eRT for a cylindrical, anthropomorphic retromolar trigone phantom. Treatment planning involved specification of beam parameters and design of a variable thickness wax bolus and Passive Radiotherapy Intensity Modulator for Electrons (PRIME) device, which was comprised of 33 tungsten island blocks of discrete diameters from 0.158 to 0.223cm (Intensity Reduction Factors from 0.937 to 0.875, respectively) inside a 10.1×6.7 cm2 copper cutout. For comparison of calculation accuracy, a BECT plan was generated by copying the IM-BECT plan and removing the intensity modulation. For both plans, a 16 MeV electron beam was used with 104.7cm source-to-surface distance to bolus. In-phantom TLD-100 measurements (N=47) were compared with both eRT planned dose distributions, which used the pencil beam redefinition algorithm with modifications for passive electron intensity modulation (IM-PBRA). Dose difference and distance to agreement (DTA) metrics were computed for each measurement point. Comparison of measured dose distributions with planned dose distributions yielded dose differences (calculated minus measured) characterized by a mean and standard deviation of -0.36%±1.64% for the IM-BECT plan, which was similar to -0.36%±1.90% for the BECT plan. All dose measurements were within 5% of the planned dose distribution, with both the BECT and IM-BECT measurement sets having 46/47 (97.8%) points within 3% or within 3mm of the respective treatment plans. It was found that the IM-BECT treatment plan generated using eRT was sufficiently accurate for clinical use when compared to TLD measurements in a cylindrical, anthropomorphic phantom, and was similarly accurate to the BECT treatment plan in the same phantom.

Assessing quality assurance of multi-leaf collimator using the structural similarity index.

This study aims to evaluate the viability of utilizing the Structural Similarity Index (SSI*) as an innovative imaging metric for quality assurance (QA) of the multi-leaf collimator (MLC). Additionally, we compared the results obtained through SSI* with those derived from a conventional Gamma index test for three types of Varian machines (Trilogy, Truebeam, and Edge) over a 12-week period of MLC QA in our clinic. To assess sensitivity to MLC positioning errors, we designed a 1cm slit on the reference MLC, subsequently shifted by 0.5-5mm on the target MLC. For evaluating sensitivity to output error, we irradiated five 25cm×25cm open fields on the portal image with varying Monitor Units (MUs) of 96-100. We compared SSI* and Gamma index tests using three linear accelerator (LINAC) machines: Varian Trilogy, Truebeam, and Edge, with MLC leaf widths of 1, 0.5, and 0.25mm. Weekly QA included VMAT and static field modes, with Picket fence test images acquired. Mechanical uncertainties related to the LINAC head, electronic portal imaging device (EPID), and MLC during gantry rotation and leaf motion were monitored. The Gamma index test started detecting the MLC shift at a threshold of 4mm, whereas the SSI* metric showed sensitivity to shifts as small as 2mm. Moreover, the Gamma index test identified dose changes at 95MUs, indicating a 5% dose difference based on the distance to agreement (DTA)/dose difference (DD) criteria of 1mm/3%. In contrast, the SSI* metric alerted to dose differences starting from 97MUs, corresponding to a 3% dose difference. The Gamma index test passed all measurements conducted on each machine. However, the SSI* metric rejected all measurements from the Edge and Trilogy machines and two from the Truebeam. Our findings demonstrate that the SSI* exhibits greater sensitivity than the Gamma index test in detecting MLC positioning errors and dose changes between static and VMAT modes. The SSI* metric outperformed the Gamma index test regarding sensitivity across these parameters.

Commissioning and clinical evaluation of a novel high-resolution quality assurance digital detector array for SRS and SBRT.

We aimed to perform the commissioning and clinical evaluation of myQA SRS detector array for patient-specific quality assurance (PSQA) of stereotactic radiosurgery (SRS)/ stereotactic body radiotherapy (SBRT) plans. To perform the commissioning of myQA SRS, its dose linearity, dose-rate dependence, angular dependence, and field-size dependence were investigated. Ten SBRT plans were selected for clinical evaluation: 1) Common clinical deviations based on the original SBRT plan (Plan0), including multileaf collimator (MLC) positioning deviation and treatment positioning deviation were introduced. 2) Compared the performance of the myQA SRS and a high-resolution EPID dosimetry system in PSQA measurement for the SBRT plans. Evaluation parameters include gamma passing rate (GPR) and distance-to-agreement (DTA) pass rate (DPR). The dose linearity, angle dependence, and field-size dependence of myQA SRS system exhibit excellent performance. The myQA SRS is highly sensitive in the detection of MLC deviations. The GPR of (3%/1mm) decreases from 90.4% of the original plan to 72.7%/62.9% with an MLC outward/inward deviation of 3mm. Additionally, when the setup error deviates by 1mm in the X, Y, and Z directions with the GPR of (3%/1mm) decreasing by an average of -20.9%, -25.7%, and -24.7%, respectively, and DPR (1mm) decreasing by an average of -33.7%, -32.9%, and -29.8%. Additionally, the myQA SRS has a slightly higher GPR than EPID for PSQA, However, the difference is not statistically significant with the GPR of (3%/1mm) of (average 90.4%% vs. 90.1%, p=0.414). Dosimetry characteristics of the myQA SRS device meets the accuracy and sensitivity requirement of PSQA for SRS/SBRT treatment. The dose rate dependence should be adequately calibrated before its application and a more stringent GPR (3%/1mm) evaluation criterion is suggested when it is used for SRS/SBRT QA.

Clinical Experience with Commissioning a GRID Collimator for Spatially Fractionated Radiation Therapy

In this study, we report our physics commissioning experience for clinically implementing a GRID collimator based Spatially Fractionated Radiation Therapy (SFRT). For SFRT commissioning, we utilized a commercially available brass GRID collimator (DotDecimal, Sanford, FL) that is mounted on a blocking tray for positioning into the accessory mount of the Linac. The brass GRID is 7.62 cm thick and weighs 15.8 kg. The GRID has a total of 149 divergent holes arranged in a hexagonal pattern (1.43 cm in diameter and hole-centers spaced at 2.11 cm when projected at the isocenter distance). The GRID encompasses a maximum field size of 25 × 25 cm at the isocenter. A commercial 48 × 48 × 48 cm water phantom scanning system was used to collect GRID output factors (GRID field to open field ratio), depth dose and beam profile data. Output measurements were performed using a 0.13 cm3 active volume ion-chamber and beam scans were obtained with a diode detector. Data was collected for both flattening and flattening-free beams of nominal energies 6 MV and 10 MV photons. The measurement depths were at dmax (1.5 cm for 6 MV and 2.5 cm for 10 MV), 5-cm and 10-cm respectively. For each energy and depth of measurement, collimator settings were varied from 5 × 5 cm to 28 × 28 cm. From scan profiles at different depths, the valley (lowest) to peak (highest) dose ratios (VPDR) were calculated. A commercial treatment planning system (TPS) was used to test the accuracy of dose calculations with GRID. This was accomplished by importing vendor generated DICOM RT file into the TPS. A block transmission factor of 7% for 6 MV and 10.2% for 10 MV energy beams were applied. All measured data were compared with corresponding TPS calculated data. Test patient treatment plans with GRID were created in TPS and planned distributions were verified using a commercial detector array with 2.5 mm detector spacing. The VPDR, expressed as %, are presented in Table 1. Measured and TPS calculated output factors agreed within 2% for 6 MV and within 3% for 10 MV photon beams. Percent depth doses were lower in magnitude for GRID field compared to open field for all energies studied (for e.g., 6 MV depth dose at 10 cm depth for 10 cm x10cm field 62% for GRID field vs. 66% for open field). Measured and calculated GRID beam profiles agreed within 5% dose difference and 1 mm distance-to agreement. For all test cases, the planned vs. measured dose distributions passed at an average gamma passing rate of 96.5% using a 3% dose difference/ 3 mm distance to agreement and 10% threshold criteria. The Dot Decimal GRID collimator provides a simple way of achieving SFRT in the clinic, albeit heavy to use and has an irradiation field size limitation of 25 cm × 25 cm.

Clinical feasibility of a commercially available MRI-only method for radiotherapy treatment planning of the brain.

Advancements in deep-learning based synthetic computed tomography (sCT) image conversion methods have enabled the development of magnetic resonance imaging (MRI)-only based radiotherapy treatment planning (RTP) of the brain. This study evaluates the clinical feasibility of a commercial, deep-learning based MRI-only RTP method with respect to dose calculation and patient positioning verification performance in RTP of the brain. Clinical validation of dose calculation accuracy was performed by a retrospective evaluation for 25 glioma and 25 brain metastasis patients. Dosimetric and image quality of the studied MRI-only RTP method was evaluated by a direct comparison of the sCT-based and computed tomography (CT)-based external beam radiation therapy (EBRT) images and treatment plans. Patient positioning verification accuracy of sCT images was evaluated retrospectively for 10 glioma and 10 brain metastasis patients based on clinical cone-beam computed tomography (CBCT) imaging. An average mean dose difference of Dmean = 0.1% for planning target volume (PTV) and 0.6% for normal tissue (NT) structures were obtained for glioma patients. Respective results for brain metastasis patients were Dmean = 0.5% for PTVs and Dmean =1.0% for NTs. Global three-dimensional (3D) gamma pass rates using 2%/2 mm dose difference and distance-to-agreement (DTA) criterion were 98.0% for the glioma subgroup, and 95.2% for the brain metastasis subgroup using 1%/1 mm criterion. Mean distance differences of <1.0 mm were observed in all Cartesian directions between CT-based and sCT-based CBCT patient positioning in both subgroups. In terms of dose calculation and patient positioning accuracy, the studied MRI-only method demonstrated its clinical feasibility for RTP of the brain. The results encourage the use of the studied method as part of a routine clinical workflow.

Importance of Dispersion in the Molecular Geometries of Mn(III) Spin-Crossover Complexes

The computational investigation of the molecular geometries of a pair of manganese(III) spin-crossover complexes is reported. For the geometry of the quintet high-spin state, density functionals significantly overestimate Mn-Namine bond distances, although the geometry for the triplet intermediate-spin state is well described. Comparisons with several wave function-based methods demonstrate that this error is due to the limited ability of commonly used density functionals to recover dispersion beyond a certain extent. Among the methods employed for geometry optimization, restricted open-shell Møller-Plesset perturbation theory (MP2) appropriately describes the high-spin geometry but results in a slightly shorter Mn-O distance in both spin states. On the other hand, extended multistate complete active space second-order perturbation theory (XMS-CASPT2) provides a good description of the geometry for the intermediate-spin state but also sufficiently recovers dispersion, performing well for the high-spin state. Despite the fact that the electronic structure of both spin states is dominated by one-electron configuration, XMS-CASPT2 offers a balanced approach, leading to molecular geometries with much better agreement with experiment than MP2 and DFT. A scan along the Mn-Namine bond demonstrates that for these complexes coupled cluster methods (i.e., DLPNO-CCSD(T)) also yield bond distances in agreement with experiment while multiconfiguration pair density functional theory (MC-PDFT) is unable to recover dispersion well enough, analogous to single-reference DFT.

Monte Carlo modelling and validation of the elekta synergy medical linear accelerator equipped with radiosurgical cones

Monte Carlo simulations of medical linear accelerator heads help in visualizing the energy spectrum and angular spread of photons and electrons, energy deposition, and scattering from each of the head components. Hence, the purpose of this study was to validate the Monte Carlo model of the Elekta synergy medical linear accelerator equipped with stereotactic radio surgical connical collimators. For this, the Elekta synergy medical linear accelerator was modelled using the EGSnrc Monte Carlo code. The model results were validated using the measured data. The primary electron beam parameters, beam size, and energy were tuned to match the measured data; a dose profile with a field size of 40 × 40 cm2 and percentage depth dose with a field size of 10 × 10 cm2 were matched during tuning. The validation of the modelled data with the measurement results was performed using gamma analysis, point dose, and field size comparisons. For small radiation fields, relative output factors were also compared. The gamma analysis revealed good agreement between the Monte Carlo modeling results and the measured data. A gamma pass rate of more than 95% was obtained for field sizes of 40 × 40 cm2 to 2 × 2 cm2 with gamma criteria of 1% and 1 mm for the dose difference (DD) and distance to agreement (DTA), respectively; this gamma pass rate was more than 98% for the corresponding values of 2% and 2 mm for the DD and DTA, respectively. A gamma pass rate of more than 99% was obtained for a percentage depth dose with 1 mm and 1% criteria. The field size was also in good agreement with the measurement results, and the maximum deviation observed was 1.1%. The stereotactic cone field also passed this analysis with a gamma pass rate of more than 98% for dose profiles and 99% for the percentage depth dose. The small field output factor exhibited a deviation of 4.3%, 3.4%, and 1.9% for field sizes of 5 mm, 7.5 mm, and 10 mm, respectively. Thus, the Monte Carlo model of the Elekta Linear accelerator was successfully validated. The validation of radio surgical cones passed the analysis in terms of the dose profiles and percentage depth dose. The small field relative output factors exhibited deviations of up to 4.3%, and to resolve this, detector-specific and field-specific correction factors must be derived.

Evaluation of dose calculation accuracy of a commercial radiotherapy treatment planning system for adjacent radiation fields

Abstract Background: Adjacent radiation fields are applied in some radiotherapeutic cases. When using these radiation fields, considerable dose errors across the junction of radiation fields are possible. Therefore, it is necessary to evaluate the accuracy of the dose calculated by treatment planning system (TPS) when using the adjacent radiation fields. The present study aimed to quantify the dose calculation accuracy of ISOgray TPS for the photon-photon adjacent fields. Materials and methods: To assess the accuracy of dose calculations, the dose profiles were first measured by a Semiflex ionization chamber at 1, 1·5, 5 and 10 cm depths for different field sizes (6 × 6, 10 × 10 and 20 × 20 cm2), source to surface distances (SSDs) (90, 100 and 110 cm) and beam angles (0º, 15º, 30º and 45º). In the second step, the data at corresponding depths were extracted from the ISOgray TPS. Finally, the dosimetric performance of TPS was evaluated using a gamma index analysis. Results: The overall dose calculation accuracy of ISOgray TPS was within the acceptable range for the build-up region (with acceptance criteria of dose difference (DD) = 15% and distance to agreement (DTA) = 3 mm) and the depths after the build-up region (with acceptance criteria of DD = 5% and DTA = 3 mm). Moreover, the overall accuracy of dose calculations was not affected by the field size and the SSD. It was also shown that the accuracy of dose calculations was similar for the adjacent radiation fields with beam angles of 0º, 15 º and 30 º, while a considerable decrease in the pass rate values is obtained for the adjacent radiation field with 45 º beam angle. A more detailed analysis of the findings revealed that the accuracy of dose calculations in the match line regions of the adjacent radiation fields for 1 cm beam profiles was within the acceptable range; however, it declined for other depths. Conclusions: The findings showed that the overall dose calculation accuracy of ISOgray TPS was acceptable for evaluated adjacent radiation fields. However, the accuracy of dose calculations in the match line regions of the adjacent radiation fields for the depth after build-up was not within the acceptable range.

Contour interpolation by deep learning approach.

Contour interpolation is an important tool for expediting manual segmentation of anatomical structures. The process allows users to manually contour on discontinuous slices and then automatically fill in the gaps, therefore saving time and efforts. The most used conventional shape-based interpolation (SBI) algorithm, which operates on shape information, often performs suboptimally near the superior and inferior borders of organs and for the gastrointestinal structures. In this study, we present a generic deep learning solution to improve the robustness and accuracy for contour interpolation, especially for these historically difficult cases. A generic deep contour interpolation model was developed and trained using 16,796 publicly available cases from 5 different data libraries, covering 15 organs. The network inputs were a image patch and the two-dimensional contour masks for the top and bottom slices of the patch. The outputs were the organ masks for the three middle slices. The performance was evaluated on both dice scores and distance-to-agreement (DTA) values. The deep contour interpolation model achieved a dice score of and a mean DTA value of , averaged on 3167 testing cases of all 15 organs. In a comparison, the results by the conventional SBI method were and , respectively. For the difficult cases, the dice score and DTA value were and by the deep interpolator, compared with and by SBI. The t-test results confirmed that the performance improvements were statistically significant ( ) for all cases in dice scores and for small organs and difficult cases in DTA values. Ablation studies were also performed. A deep learning method was developed to enhance the process of contour interpolation. It could be useful for expediting the tasks of manual segmentation of organs and structures in the medical images.

Impact of respiratory motion on lung dose during total marrow irradiation.

We evaluated the impact of respiratory motion on the lung dose during linac-based intensity-modulated total marrow irradiation (IMTMI) using two different approaches: (1) measurement of doses within the lungs of an anthropomorphic phantom using thermoluminescent detectors (TLDs) and (2) treatment delivery measurements using ArcCHECK where gamma passing rates (GPRs) and the mean lung doses were calculated and compared with and without motion. In the first approach, respiratory motions were simulated using a programmable motion platform by using typical published peak-to-peak motion amplitudes of 5, 8, and 12mm in the craniocaudal (CC) direction, denoted here as M1, M2, and M3, respectively, with 2mm in both anteroposterior (AP) and lateral (LAT) directions. TLDs were placed in five selected locations in the lungs of a RANDO phantom. Average TLD measurements obtained with motion were normalized to those obtained with static phantom delivery. The mean dose ratios were 1.01 (0.98-1.03), 1.04 (1.01-1.09), and 1.08 (1.04-1.12) for respiratory motions M1, M2, and M3, respectively. To determine the impact of directional respiratory motion, we repeated the experiment with 5-, 8-, and 12-mm motion in the CC direction only. The differences in average TLD doses were less than 1% when compared with the M1, M2, and M3 motions indicating a minimal impact from CC motion on lung dose during IMTMI. In the second experimental approach, we evaluated extreme respiratory motion 15 mm excursion in only the CC direction. We placed an ArcCHECK device on a commercial motion platform and delivered the clinical IMTMI plans of five patients. We compared, with and without motion, the dose volume histograms (DVHs) and mean lung dose calculated with the ArcCHECK-3DVH tool as well as GPR with 3%, 5%, and 10% dose agreements and a 3-mm constant distance to agreement (DTA). GPR differed by 11.1 ± 2.1%, 3.8 ± 1.5%, and 0.1 ± 0.2% with dose agreement criteria of 3%, 5%, and 10%, respectively. This indicates that respiratory motion impacts dose distribution in small and isolated parts of the lungs. More importantly, the impact of respiratory motion on the mean lung dose, a critical indicator for toxicity in IMTMI, was not statistically significant (p > 0.05) based on the Student's t-test. We conclude that most patients treated with IMTMI will have negligible dose uncertainty due to respiratory motion. This is particularly reassuring as lung toxicity is the main concern for future IMTMI dose escalation studies.

Evaluating the Effectiveness of Deep Learning Contouring across Multiple Radiotherapy Centres

Deep learning contouring (DLC) has the potential to decrease contouring time and variability of organ contours. This work evaluates the effectiveness of DLC for prostate and head and neck across four radiotherapy centres using a commercial system. Computed tomography scans of 123 prostate and 310 head and neck patients were evaluated. Besides one head and neck model, generic DLC models were used. Contouring time using centres' existing clinical methods and contour editing time after DLC were compared. Timing was evaluated using paired and non-paired studies. Commercial software or in-house scripts assessed dice similarity coefficient (DSC) and distance to agreement (DTA). One centre assessed head and neck inter-observer variability. The mean contouring time saved for prostate structures using DLC compared to the existing clinical method was 5.9±3.5min. The best agreement was shown for the femoral heads (median DSC 0.92±0.03, median DTA 1.5±0.3mm) and the worst for the rectum (median DSC 0.68±0.04, median DTA 4.6±0.6mm). The mean contouring time saved for head and neck structures using DLC was 16.2±8.6min. For one centre there was no DLC time-saving compared to an atlas-based method. DLC contours reduced inter-observer variability compared to manual contours for the brainstem, left parotid gland and left submandibular gland. Generic prostate and head and neck DLC models can provide time-savings which can be assessed with paired or non-paired studies to integrate with clinical workload. Reducing inter-observer variability potential has been shown.

Evaluation of the Varian TrueBeam™ 6 MV phase-space files for the Monte Carlo simulation in small field dosimetry

Background: The Monte Carlo (MC) simulation is an effective tool for determining the absorbed dose in small field sizes. To calculate accurate results, the MC simulation requires precise geometric and material descriptions of the linear accelerator head. Due to proprietary information issues, the description of the Varian TrueBeam™ linear accelerator (Varian Medical Systems, Palo Alto, CA) head geometry and material information are not available. Instead, the manufacturer provided a phase-space file just above the jaw for each photon energy level. Although several studies have validated the accuracy of this phase-space file, to the best of our knowledge, there are no reported data for a small field size (&lt;2x2 cm2) of 6 MV photon beams. Objectives: The purpose of this study was to evaluate the Varian TrueBeam™ phase-space file of the 6 MV photon beam provided by the manufacturer for the Monte Carlo (MC) simulation in small field dosimetry. Materials and methods: The TrueBeam™ linear accelerator was simulated using an EGSnrc MC code with a Varian phase-space file as the input. The simulation was compared with the measurement using percent depth dose (PDD) and beam profile, and the field output factor (FOF) for the 0.6x0.6, 1x1, 2x2, 3x3, 4x4, 6x6, and 10x10 cm2 field sizes. Results: The agreement between the measurements and simulated PDD data was under 2.2% beyond the buildup region. The distance to agreement (DTA) in the buildup region was within 1.0 mm. The simulation data presented identical profiles with the measurement within 1.0% of the dose difference or 1.2 mm of the DTA. The mean dose difference in the radiation field was ≤1.5% for the ≥1x1 cm2 field size. The largest deviation was observed in the 0.6x0.6 cm2 inline beam profile. The deviation of the penumbra and full width at half maximum (FWHM) between simulation and measurement was &lt;2 mm. The agreement of the simulated and measured FOF was within 1.0%, except for the 0.6x0.6 cm2 field size. Conclusion: Overall, the MC simulation demonstrates data that is consistent with the measurement for the ≥1x1 cm2 field sizes. These data assure that the 6 MV Varian phase-space file can be used as a radiation source for accurate MC dose calculation in a small field. However, a large discrepancy in beam profiles was observed at the 0.6x0.6 cm2 field size due to the different primary source sizes among TruebeamTM machines.

Elaboration and experimental validation of a Monte Carlo source model for linac 6 MV photon beams with and without Flattening Filter

The concept of virtual source model has been developed to provide an efficient and precise particle generator mainly involved in standard photon beam treatment planing and Monte Carlo dosimetry simulations. In this work, we propose a source model for 6 MV linac photon beam for both irradiation modes, with and without flattening filter. Two sources are considered to represent primary and a scattered radiations. Energy spectra taking into account the correlation between energy and diffusion angle have been used. Model parameters were tuned through a dose distribution iterative optimisation approach. The convergence condition relies on γindex evaluation. The simulations were performed in two steps, phase space files were generated using Geant4 toolkit, then energy deposit in water were computed using DPM code. Monte Carlo dose distributions of the model were compared to experimental data of two linac systems, an Elekta Synergy® with flattening filter and a Varian TrueBeam® with and without flattening filter. Good results were obtained in terms of γindex 2%/2 mm criterion, dose difference and distance to agreement (DTA) analysis for field size range from 3 × 3 cm2 to 30 × 30 cm2.

Geometrical source modeling of 6MV flattening-filter-free (FFF) beam from TrueBeam linear accelerator and its commissioning validation using Monte Carlo simulation approach for radiotherapy

PurposeTo study geometrical source modeling of 6 MV flattening-filter-free (FFF) beam from TrueBeam linear accelerator and its commissioning validation using Monte Carlo simulation approach. Methods & materialSource modeling of 6MVFFF beam from TrueBeam linear accelerator has been accomplished by using PRIMO as the Monte-Carlo (MC) simulation software based on PENELOPE code. Initially, source modeling of 6MVFFF beam was validated against experimentally measured Percentage-depth-dose (PDD) and profile for 10 × 10cm2 field. Followed by commissioning validation of 6MVFFF beam has been carried out by simulating PDDs, profiles and output factors for range of field sizes. Besides, verification of absolute dose, beam quality index, performance analysis of dose distribution in heterogeneous phantom and simulation of radiation treatment plan for validation of Treatment planning system (TPS) was performed. Simulated results compared against measured; dose distributions were analyzed using gamma analysis with acceptance criteria of 2% Dose-difference (DD) and 2 mm Distance-to-agreement (DTA). ResultsGamma analysis for all the simulated and measured PDDs and profiles shows minimum passing rate of 100% and 98.04% respectively. Simulated values of absolute point dose, beam quality index and output factors shows good agreements with measurements. Gamma analysis of depth dose distribution in heterogeneous phantom obtained using MC simulation and calculated with Analytical anisotropic algorithm (AAA) agreed within 95.89%. However, heterogeneous medium of very high and low-density region shows larger dose discrepancy between MC and AAA due to the poor modeling of AAA compared to MC. The percentage of 99.81% of gamma passing and comparison of predicted Dose-volume-histogram (DVH) shows good resemblance between PRIMO simulated and AAA calculated plan. ConclusionStudy concludes that PRIMO is an independent MC simulation tools for verification and commissioning validation of external beam radiotherapy in treatment of cancer. The MC validation of external beam therapy modules grants higher confidence in accuracy of radiation dose delivery.

Measurement-based validation of a commercial Monte Carlo dose calculation algorithm for electron beams.

This work presents the clinical validation of RayStation's electron Monte Carlo code by the use of diodes and plane parallel radiation detectors in homogenous and heterogeneous tissues. Results are evaluated against internationally accepted criteria. The Monte Carlo-based electron beam dose calculation code was validated using diodes, air- and liquid-filled parallel radiation detectors on an Elekta linac with beam energies of 4, 6, 8, 10, and 12MeV. Treatment setups with varying source-to-skin distances, different applicators, various cutouts, and oblique beam incidences were addressed, together with dose prediction behind lung-, air-, and bone-equivalent inserts. According to NCS (Netherlands Commission for Radiation Dosimetry) report 15 for nonstandard treatment setups, a dose agreement of 3% in the δ1 region (high-dose region around Zref ), a distance-to-agreement (DTA) of 3mm or a dose agreement of 10% in the δ2 region (regions with high-dose gradients), and 4% in the δ4 region (photon tail/low-dose region) were applied. During validation, clinical routine settings of 2×2×2-mm3 dose voxels and a statistically dose uncertainty of 0.6% (250000 histories/cm2 ) were used. RayStation's electron Monte Carlo code dose prediction was able to achieve the tolerances of NCS report 15. Output predictions as a function of the SSD improve with energy and applicator size. Cutout data revealed no field size or energy dependence on the accuracy of the dose prediction. Excellent agreement for the oblique incidence data was achieved and a maximum of one voxel difference was obtained for the DTA behind heterogeneous inserts. The accuracy of RayStation's Monte Carlo-based electron beam dose prediction for Elekta accelerators is confirmed for clinical treatment planning that is not only performed within an acceptable timeframe in terms of the number of histories but also addresses for homogenous and heterogeneous media.

Establishment of criteria for gamma-analysis of individual dose distributions during verification of radiotherapy high-tech treatment plans for cancer patients

A typical process for verification of treatment plans in intensity-modulated radiation therapy is described. The main errors and uncertainties that arise in the course of planning dose distribution and in the process of dose delivery are listed. Methods for comparing dose distributions are considered: the distance to agreement (DTA) and the test for the algebraic dose difference. Formulas for calculating the shift of points of dose distributions, as well as the minimum value of the shift of points, are provided. The influences of global and local normalization and spatial resolution on the interpretation of the results obtained are defined. A methodology for determining reasonable criteria for gamma-analysis of individual dose distributions when verifying plans for irradiation of cancer patients using high-tech radiation therapy methods has been developed. Using the procedure proposed by the authors to establish action limits and tolerances will make it possible to assess the quality of medical care provided in healthcare institutions when using high-tech radiotherapy methods

Trans-Bis(4-amino-pyridine-κN)bis-(quin-ox-aline-2,3-di-thiol-ato-κ2 S,S')platinum(IV) dimethyl sulfoxide monosolvate.

In the structure of the title solvated complex, [Pt(C8H4N2S2)2(C5H6N2)2]·C2H6OS or trans-[Pt(4-ap)2(qdt)2]·dmso (4-ap = 4-amino-pyridyl, C5H6N2; qdt = quinoxaline-2,3-di-thiol-ate, C8H4N2S2; dmso = dimethyl sulfoxide, C2H6OS) the centrosymmetric complex exhibits Pt-S distances in agreement with other PtIV-S bond lengths found in platinum(IV) di-thiol-ene complexes. The qdt ligands have inter-molecular inter-actions with an amine hydrogen atom on a 4-ap ligand (hydrogen bonding) and have sandwich π-π inter-actions with a neighboring qdt ligand.

Improved reconstruction methodology of clinical electron energy spectra based on Tikhonov regularization and generalized simulated annealing

Electron beam radiotherapy is the most widespread treatment modality todeal with superficial cancers. In electron radiotherapy, the energy spectrum isimportant for electron beam modelling and accurate dose calculation. Since thepercentage depth-dose (PDD) is a function of the beam’s energy, the reconstruction of the spectrum from the depth-dose curve represents an inverse problem.Thus, the energy spectrum can be related to the depth-dose by means of anappropriate mathematical model as the Fredholm equation of the first kind.Since the Fredholm equation of the first kind is ill-posed, some regularizationmethod has to be used to achieve a useful solution. In this work the Tikhonovregularization function was solved by the generalized simulated annealing optimization method. The accuracy of the reconstruction was verified by thegamma index passing rate criterion applied to the simulated PDD curves forthe reconstructed spectra compared to experimental PDD curves. Results showa good coincidence between the experimental and simulated depth-dose curvesaccording to the gamma passing rate better than 95% for 1% dose difference(DD)/1 mm distance to agreement (DTA) criteria. Moreover, the results showimprovement from previous works not only in accuracy but also in calculationtime. In general, the proposed method can help in the accuracy of dosimetryprocedures, treatment planning and quality control in radiotherapy.

Improving GI Toxicity Models Through Deep Learning-Based Segmentation and Biomechanical Model-Based Dose Accumulation

<h3>Purpose/Objective(s)</h3> Current GI toxicity models are limited by the uncertainty in the estimated delivered dose used to develop the models. The purpose of this study is to assess the benefit of harnessing deep learning and biomechanical models to improve the understanding of the dose-toxicity relationship. <h3>Materials/Methods</h3> Retrospective dose accumulation was conducted on 75 patients with primary and metastatic liver cancer treated with external beam radiotherapy guided by daily CT-on-rails (CTOR), based on a novel deformable image registration (DIR) approach that applies biomechanical model-based and intensity-based DIR inside and outside the liver, respectively. The liver was auto-segmented on all images using a clinically validated 2D deep learning model. On a sub-cohort, the combination of stomach and duodenum region of interest (GI ROI) was auto-contoured using a 3D UNet model trained independently on 102 patients. These contours were compared to physician-drawn contours on CTOR, using Dice similarity coefficient (DSC), mean distance to agreement (DTA), Hausdorff distance (HD), and planned dose metrics. Intra-observer variability was evaluated. Doses were converted to equivalent dose in 2Gy fractions (EQD2) for analysis (α/β = 3.5). Differences between planned and delivered dose were calculated, as well as GI ROI daily dose variation. Toxicity probability was calculated based on previously developed accumulated dose normal tissue complication probability (NTCP) models for duodenum and stomach. <h3>Results</h3> Average (SD) DSC, DTA, and HD between the deep learning model and physician-drawn GI ROI were 0.9 (0.1), 0.2 (0.1) cm, and 2.4 (2.2) cm; intra-observer values were 0.9 (0.0), 0.1 (0.0) cm, and 2.3 (0.8) cm, <i>P</i> > 0.1. Average differences in volume (SD), D50 (SD), and D1 (SD) between the AI model and physician-drawn contours were 25.0 (36.7) cc, 0.6 (1.1) Gy, and 0.5 (0.2) Gy; intra-observer values were 7.1 (4.5) cc, 0.2 (0.3) Gy and 0.3 (0.3) Gy, <i>P</i> > 0.1. Average planned and accumulated D1 (EQD2) to the GI ROI were 28.1 Gy and 26.6 Gy, respectively. These distributions were significantly different (<i>P</i> < 0.01), with differences ranging from 0.2 Gy to 2.9 Gy. Daily D1 to the GI ROI varied by up to 47% (average 25%). For 38% of patients, relative differences in NTCP based on planned and accumulated dose were greater than 50%. Compared to planned dose, 63% of the patients had lower NTCP with accumulated dose, and 13% had higher NTCP. <h3>Conclusion</h3> Variability between AI-based and physician-drawn stomach and duodenum segmentation was equivalent to intra-observer variability. Accumulated dose showed statistically significant differences from planned dose for the stomach and duodenum leading to meaningful differences in NTCP. The daily variability in the maximum dose varied by an average of +/- 25%, demonstrating the potential to optimize daily fractionation based on anatomical configuration of the day.

Planning and delivery of intensity modulated bolus electron conformal therapy.

PurposeBolus electron conformal therapy (BECT) is a clinically useful, well‐documented, and available technology. The addition of intensity modulation (IM) to BECT reduces volumes of high dose and dose spread in the planning target volume (PTV). This paper demonstrates new techniques for a process that should be suitable for planning and delivering IM‐BECT using passive radiotherapy intensity modulation for electrons (PRIME) devices.MethodsThe IM‐BECT planning and delivery process is an addition to the BECT process that includes intensity modulator design, fabrication, and quality assurance. The intensity modulator (PRIME device) is a hexagonal matrix of small island blocks (tungsten pins of varying diameter) placed inside the patient beam‐defining collimator (cutout). Its design process determines a desirable intensity‐modulated electron beam during the planning process, then determines the island block configuration to deliver that intensity distribution (segmentation). The intensity modulator is fabricated and quality assurance performed at the factory (.decimal, LLC, Sanford, FL). Clinical quality assurance consists of measuring a fluence distribution in a plane perpendicular to the beam in a water or water‐equivalent phantom. This IM‐BECT process is described and demonstrated for two sites, postmastectomy chest wall and temple. Dose plans, intensity distributions, fabricated intensity modulators, and quality assurance results are presented.ResultsIM‐BECT plans showed improved D90‐10 over BECT plans, 6.4% versus 7.3% and 8.4% versus 11.0% for the postmastectomy chest wall and temple, respectively. Their intensity modulators utilized 61 (single diameter) and 246 (five diameters) tungsten pins, respectively. Dose comparisons for clinical quality assurance showed that for doses greater than 10%, measured agreed with calculated dose within 3% or 0.3 cm distance‐to‐agreement (DTA) for 99.9% and 100% of points, respectively.ConclusionThese results demonstrated the feasibility of translating IM‐BECT to the clinic using the techniques presented for treatment planning, intensity modulator design and fabrication, and quality assurance processes.