Uncertainty In Dose Calculation Research Articles

In vivo dosimetry with an inorganic scintillation detector during multi-channel vaginal cylinder pulsed dose-rate brachytherapy: Dosimetry for pulsed dose-rate brachytherapy

Background and purposeIn vivo dosimetry is not standard in brachytherapy and some errors go undetected. The aim of this study was to evaluate the accuracy of multi-channel vaginal cylinder pulsed dose-rate brachytherapy using in vivo dosimetry. Materials and methodsIn vivo dosimetry data was collected during the years 2019–2022 for 22 patients (32 fractions) receiving multi-channel cylinder pulsed dose-rate brachytherapy. An inorganic scintillation detector was inserted in a cylinder channel. Each fraction was analysed as independent data sets. In vivo dosimetry-based source-tracking was used to determine the relative source-to-detector position. Measured dose was compared to planned and re-calculated source-tracking based doses. Assuming no change in organ and applicator geometry throughout treatment, the planned and source-tracking based dose distributions were compared in select volumes via γ-index analysis and dose-volume-histograms. ResultsThe mean ± SD planned vs. measured dose deviations in the first pulse were 0.8 ± 5.9 %. In 31/32 fractions the deviation was within the combined in vivo dosimetry uncertainty (averaging 9.7 %, k = 2) and planning dose calculation uncertainty (1.6 %, k = 2). The dwell-position offsets were < 2 mm for 88 % of channels, with the largest being 5.1 mm (4.0 mm uncertainty, k = 2). 3 %/2 mm γ pass-rates averaged 97.0 % (clinical target volume (CTV)), 100.0 % (rectum), 99.9 % (bladder). The mean ± SD deviation was −1.1 ± 2.9 % for CTV D98, and −0.2 ± 0.9 % and −1.2 ± 2.5 %, for bladder and rectum D2cm3 respectively, indicating good agreement between intended and delivered dose. ConclusionsIn vivo dosimetry verified accurate and stable dose delivery in multi-channel vaginal cylinder based pulsed dose-rate brachytherapy.

Object and person tracking systems to enable extremity dosimetry in nuclear medicine using computational methods

Nuclear medicine (NM) professionals are potentially exposed to high doses of ionising radiation, particularly in the skin of the hands. Ring dosimeters are used by the workers to ensure extremity doses are kept below the legal limits. However, ring dosimeters are often susceptible to large uncertainties, so it is difficult to ensure a correct measurement using the traditional occupational monitoring methods. An alternative solution is to calculate the absorbed dose by using Monte Carlo simulations. This method could reduce the uncertainty in dose calculation if the exact positions of the worker and the radiation source are represented in these simulations. In this study we present a set of computer vision and artificial intelligence algorithms that allow us to track the exact position of unshielded syringes and the hands of NM workers. We showcase a possible hardware configuration to acquire the necessary input data for the algorithms. And finally, we assess the tracking confidence of our software. The tracking accuracy achieved for the syringe detection was 57% and for the hand detection 98%.

MV-based relative electron density estimation (iMREDe) for MR-LINAC dose calculation.

MR-LINAC systems have been increasingly utilized for real-time imaging in adaptive treatments worldwide. Challenges in MR representation of air cavities and subsequent estimation of electron density maps impede planning efficiency and may lead to dose calculation uncertainties. To demonstrate the generation of accurate electron density maps using the primary MV beam with a flat-panel imager. The ViewRay MRIdian MR-LINAC system was modeled digitally for Monte Carlo simulations. Iron shimming, the magnetic field, and the proposed flat panel detector were included in the model. The effect of the magnetic field on the detector response was investigated. Acquisition of projections over 360 degrees was simulated for digital phantoms of the Catphan 505 phantom and a patient treated for Head and Neck cancer. Shim patterns on the projections were removed and detector noise linearity was assessed. Electron density maps were generated for the digital patient phantom using the flat-panel detector and compared with actual treatment planning CT generated electron density maps of the same patient. The effect of the magnetic field on the detector point-spread function (PSF) was found to be substantial for field strengths above 50 mT. Shims correction in the projection images using air normalization and in-painting effectively removed reconstruction artifacts without affecting noise linearity. The relative difference between reconstructed electron density maps from the proposed method and electron density maps generated from the treatment planning CT was 11% on average along all slices included in the iMREDe reconstruction. The proposed iMREDe technique demonstrated the feasibility of generating accurate electron densities for the ViewRay MRIdian MR-LINAC system with a flat-panel imager and the primary MV beam. This work is a step towards reducing the time and effort required for adaptive radiotherapy in the current ViewRay MR-LINAC systems.

Single energy CT-based mass density and relative stopping power estimation for proton therapy using deep learning method

BackgroundThe number of patients undergoing proton therapy has increased in recent years. Current treatment planning systems (TPS) calculate dose maps using three-dimensional (3D) maps of relative stopping power (RSP) and mass density. The patient-specific maps of RSP and mass density were obtained by translating the CT number (HU) acquired using single-energy computed tomography (SECT) with appropriate conversions and coefficients. The proton dose calculation uncertainty of this approach is 2.5%-3.5% plus 1 mm margin. SECT is the major clinical modality for proton therapy treatment planning. It would be intriguing to enhance proton dose calculation accuracy using a deep learning (DL) approach centered on SECT.ObjectivesThe purpose of this work is to develop a deep learning method to generate mass density and relative stopping power (RSP) maps based on clinical single-energy CT (SECT) data for proton dose calculation in proton therapy treatment.MethodsArtificial neural networks (ANN), fully convolutional neural networks (FCNN), and residual neural networks (ResNet) were used to learn the correlation between voxel-specific mass density, RSP, and SECT CT number (HU). A stoichiometric calibration method based on SECT data and an empirical model based on dual-energy CT (DECT) images were chosen as reference models to evaluate the performance of deep learning neural networks. SECT images of a CIRS 062M electron density phantom were used as the training dataset for deep learning models. CIRS anthropomorphic M701 and M702 phantoms were used to test the performance of deep learning models.ResultsFor M701, the mean absolute percentage errors (MAPE) of the mass density map by FCNN are 0.39%, 0.92%, 0.68%, 0.92%, and 1.57% on the brain, spinal cord, soft tissue, bone, and lung, respectively, whereas with the SECT stoichiometric method, they are 0.99%, 2.34%, 1.87%, 2.90%, and 12.96%. For RSP maps, the MAPE of FCNN on M701 are 0.85%, 2.32%, 0.75%, 1.22%, and 1.25%, whereas with the SECT reference model, they are 0.95%, 2.61%, 2.08%, 7.74%, and 8.62%. ConclusionThe results show that deep learning neural networks have the potential to generate accurate voxel-specific material property information, which can be used to improve the accuracy of proton dose calculation.Advances in knowledgeDeep learning-based frameworks are proposed to estimate material mass density and RSP from SECT with improved accuracy compared with conventional methods.

Exploring the Benefits of 3D-Printed Bolus in Cone Beam CT for Modified Radical Mastectomy Breast Cancer

To improve the accuracy of superficial dose coverage for patients undergoing modified radical mastectomy (MRM), boluses are frequently applied to the skin surface of targeted region during radiotherapy. The irregular curvature of MRM breast cases results in discrepancies of dosimetry and poor contact. Additionally, the presence of an air gap causes unnecessary high-dose escalation and uncertainty in dose calculation, making the use of commercial flat bolus problematic. This study evaluated the effectiveness of 3D-printed bolus by comparing it to commercial bolus in setup variations and dosimetric compliance through daily cone-beam computed tomography (CBCT) scans. Ten patients underwent MRM were divided into 2 groups. 5 patients treated with 0.5 cm commercial bolus as group A while the other 5 patients covered by 3D Bolus as group B. 3D bolus was made of polylactic acid filament (PLA) and contoured in advance with thickness of 0.5 cm on the surface of target. Positional errors were recorded through daily image guidance and compared with the images. Both groups had right-sided breast with neck lymph nodes involved and received 50 Gy in 25 fractions using 4 partial arcs of the volumetric modulated arc therapy (VMAT) technique. The CBCTs were recalculated through treatment planning system (TPS) to assess superficial dose coverage. A two-tailed student's t-test was applied. Groups A and B pitch angles were -0.203 ± 0.837° and 0.334 ± 0.909° (p = 0.0003). Roll angle were 0.313 ± 0.728° and -0.633 ± 1.286° (p = 0.0000013). Yaw angle were -0.034 ± 0.872° and 0.018 ± 0.883° (p = 0.721). There was a trend of differences in the Z-axis and significant statistical differences in the pitch and roll angles due to aligning gel layers directly with group A's body surface, while 3D bolus rigidly adherence to group B's delineated curve. In the planned target volume (PTV), the CI and HI of group A were 0.9448±0.0208 and 1.2061±0.0448, respectively, while 0.9776±0.0144 and 1.1472±0.0206 (p<0.005) were for group B. As for the superficial region, which is defined from body surface to 0.5cm inside PTV, CI and HI of A were 0.8290±0.0599 and 1.4675±0.2434, while for B, they were 0.9753±0.0214 and 1.1330±0.0126, respectively (p<0.005). The study analyzed the results through image comparison and investigated the CI and HI between two types of boluses. The 3D bolus reduces setup errors and improves dose coverage especially when superficial region is concerned. Better consistency of patient repositioning and dosimetry can be achieved and proved by daily assessment of CBCT scan. The customization of 3D bolus with integration of TPS and CT scans provides a solution to the inadequacies of commercial bolus. The results suggest that the use of 3D bolus is a promising development in radiation therapy for MRM breast cancer patients.

Mitigation of Dosimetric Uncertainty in MRI-Based Proton Planning Using Spot-Scanning Proton Arc (SPArc) Technique

MRI-based synthetic CT (SCT) images created using generative adversarial network (GAN) have been demonstrated to be feasible for intensity-modulated proton therapy (IMPT) planning. However, dose calculation accuracy can be uncertain in some regions within/near the target of head and neck patients due to the local CT number estimation error or sharp dose fall-off. This study investigated the feasibility of using the SPArc technique to mitigate such dosimetric uncertainty. A GAN using a 3D U-net as the generator and a 6-layer 3D convolutional neural network as the discriminator was trained with T1-weighted MR-CT image pairs from 162 nasopharyngeal carcinoma patients (14 for validation). The generator was used to generate SCT images from MR images for 7 test patients. For each test patient, the CT image was used to create a SPArc plan and an IMPT plan with the same clinical objectives. The SPArc plans (control point frequency sampling, arc trajectory, etc.) were optimized using a previously developed iterative approach. The dose distributions of both SPArc plans and IMPT plans were re-calculated on the SCT images and compared to the one calculated on the CT images. The dosimetric uncertainty was quantified using the gamma index. The 2%/2mm and 3%/3mm passing rates for SPArc plans were (96.9¡À2.7) % and (98.6¡À1.5) %, while the passing rates for IMPT plans were (94.0¡À3.9) % and (96.4+2.9) %. A significant reduction in dosimetric uncertainty was identified for SPArc plans (p ¡Ü0.021). Table 1 shows the passing rates for the 7 test individuals. SPArc can mitigate the uncertainty of dose calculation in MRI-based proton planning. Further research needs to validate these findings on a larger patient cohort. The study paves the road map for using MRI for SPArc planning.

Note on uncertainty in Monte Carlo dose calculations and its relation to microdosimetry

PurposeThe Type A standard uncertainty in Monte Carlo (MC) dose calculations is usually determined using the “history by history” method. Its applicability is based on the assumption that the central limit theorem (CLT) can be applied such that the dispersion of repeated calculations can be modeled by a Normal distribution. The justification for this assumption, however, is not obvious. The concept of stochastic quantities used in the field of microdosimetry offers an alternative approach to assess uncertainty. This leads to a new and simple expression. MethodsThe value of the MC determined absorbed dose is considered a random variable which is comparable to the stochastic quantity specific energy, z. This quantity plays an important role in microdosimetry and in the definition of the quantity absorbed dose, D. One of the main features of z is that it is itself the product of two other random variables, specifically of the mean dose contribution in a ‘single event’ and of the mean number of such events. The term ‘single event’ signifies the sum of energies imparted by all correlated particles to the matter in a given volume. The similarity between the MC calculated absorbed dose and the specific energy is used to establish the ‘event by event’ method for the determination of the uncertainty. MC dose calculations were performed to test and compare both methods. ResultsIt is shown that the dispersion of values obtained by MC dose calculations indeed depend on the product of the mean absorbed dose per event, and the number of events. Applying methods to obtain the variance of a product of two random variables, a simple formula for the assessment of uncertainties is obtained which is slightly different from the ‘history by history’ method. Interestingly, both formulas yield indistinguishable results. This finding is attributed to the large number of histories used in MC simulations. Due to the fact that the values of a MC calculated absorbed dose are the product of two approximately Normal distributions it can be demonstrated that the resulting product is also approximately normally distributed. ConclusionsThe event by event approach appears to be more suitable than the history by history approach because it takes into account the randomness of the number of events involved in MC dose calculations. Under the condition of large numbers of histories, however, both approaches lead to the same simple expression for the determination of uncertainty in MC dose calculations. It is suggested to replace the formula currently used by the new expression. Finally, it turned out that the concept and ideas that were developed in the field of microdosimetry already 50 years ago can be usefully applied also in MC calculations.

Plan quality assessment in clinical practice: Results of the 2020 ESTRO survey on plan complexity and robustness

PurposePlan complexity and robustness are two essential aspects of treatment plan quality but there is a great variability in their management in clinical practice. This study reports the results of the 2020 ESTRO survey on plan complexity and robustness to identify needs and guide future discussions and consensus. MethodsA survey was distributed online to ESTRO members. Plan complexity was defined as the modulation of machine parameters and increased uncertainty in dose calculation and delivery. Robustness was defined as a dose distribution’s sensitivity towards errors stemming from treatment uncertainties, patient setup, or anatomical changes. ResultsA total of 126 radiotherapy centres from 33 countries participated, 95 of them (75%) from Europe and Central Asia. The majority controlled and evaluated plan complexity using monitor units (56 centres) and aperture shapes (38 centres). To control robustness, 98 (97% of question responses) photon and 5 (50%) proton centres used PTV margins for plan optimization while 75 (94%) and 5 (50%), respectively, used margins for plan evaluation. Seventeen (21%) photon and 8 (80%) proton centres used robust optimisation, while 10 (13%) and 8 (80%), respectively, used robust evaluation. Primary uncertainties considered were patient setup (photons and protons) and range calculation uncertainties (protons). Participants expressed the need for improved commercial tools to control and evaluate plan complexity and robustness. ConclusionClinical implementation of methods to control and evaluate plan complexity and robustness is very heterogeneous. Better tools are needed to manage complexity and robustness in treatment planning systems. International guidelines may promote harmonization.

Quantitative Comparison of Dosimetric Data Between the Indigenous Baseplate and Commercially Available Carbon Fiber Baseplate for 6 and 15 MV Photon Energy.

Background:This study aims to design an indigenous baseplate (ID baseplate) that is economically viable and dosimetrically comparable for radiotherapy patient treatment. An ID baseplate was designed and manufactured using wood plastic composition materials that are readily available in the market and were compared dosimetrically with the commercially available carbon fiber baseplate (CF baseplate).Materials and Methods:Surface dose and beam attenuation properties of both the baseplates (ID and CF) were measured using a parallel plate chamber and compared with the dose calculated from the treatment planning system (TPS). Separate computer tomography images of both the baseplates were acquired by placing solid water phantoms. These images were used for surface dose calculation in the TPS and were validated with experimental measurements. Proper densities were assigned to the couch and baseplates to avoid uncertainties in dose calculations. All measurements were performed at field sizes 10 cm × 10 cm for 6 MV and 15 MV photon beams.Results:The percentage surface dose measured for the ID baseplate and CF baseplate was found to be matching for 6 MV beam (98.2% and 97%, respectively); however, for the 15 MV beam, the ID baseplate showed a higher surface dose of 98.6% compared to CF baseplate (87.4%). For the ID baseplate, the percentage difference in the surface dose between that TPS calculated value and the measured values were 1.6% and 1.4% for 6MV and 15MV, respectively. The ID baseplate showed higher beam attenuation than the CF baseplate by 2.2% for the 6MV beam and 3.4% for the 15MV beam when proper electron densities were not assigned. The difference between the TPS calculated dose and delivered dose was achieved within 3% after assigning proper electron density to the couch and baseplate.Conclusions:The ID baseplate has shown acceptable dosimetric results and can be an economically viable alternative to the commercially available CF baseplates. The manufacturing cost of the ID baseplate was ten times cheaper than the CF baseplate.

Proceedings to the 7th Annual Conference of the Particle Therapy Cooperative Group North America (PTCOG-NA)

Proceedings to the 7th Annual Conference of the Particle Therapy Cooperative Group North America (PTCOG-NA)

Proton Therapy for Prostate Cancer: Challenges and Opportunities.

Simple SummaryReported clinical outcomes of proton therapy (PT) for localized prostate cancer are similar to photon-based external beam radiotherapy. Apparently, the dosimetric advantages of PT have yet to be translated to clinical benefits. The suboptimal clinical outcomes of PT might be attributable to inadequate dose prescription, as indicated by the ASCENDE-RT trial. Moreover, uncertainties involved in the treatment planning and delivery processes, as well as technological limitations in PT treatment systems, may lead to discrepancies between planned doses and actual doses delivered to patients. In this article, we reviewed the current status of PT for prostate cancer and discussed different clinical implementations that could potentially improve the clinical outcome of PT for prostate cancer. Various technological advancements under which uncertainties in dose calculations can be minimized, including MRI-guided PT, dual-energy photon-counting CT and high-resolution Monte Carlo-based treatment planning systems, are highlighted.The dosimetric advantages of proton therapy (PT) treatment plans are demonstrably superior to photon-based external beam radiotherapy (EBRT) for localized prostate cancer, but the reported clinical outcomes are similar. This may be due to inadequate dose prescription, especially in high-risk disease, as indicated by the ASCENDE-RT trial. Alternatively, the lack of clinical benefits with PT may be attributable to improper dose delivery, mainly due to geometric and dosimetric uncertainties during treatment planning, as well as delivery procedures that compromise the dose conformity of treatments. Advanced high-precision PT technologies, and treatment planning and beam delivery techniques are being developed to address these uncertainties. For instance, external magnetic resonance imaging (MRI)-guided patient setup rooms are being developed to improve the accuracy of patient positioning for treatment. In-room MRI-guided patient positioning systems are also being investigated to improve the geometric accuracy of PT. Soon, high-dose rate beam delivery systems will shorten beam delivery time to within one breath hold, minimizing the effects of organ motion and patient movements. Dual-energy photon-counting computed tomography and high-resolution Monte Carlo-based treatment planning systems are available to minimize uncertainties in dose planning calculations. Advanced in-room treatment verification tools such as prompt gamma detector systems will be used to verify the depth of PT. Clinical implementation of these new technologies is expected to improve the accuracy and dose conformity of PT in the treatment of localized prostate cancers, and lead to better clinical outcomes. Improvement in dose conformity may also facilitate dose escalation, improving local control and implementation of hypofractionation treatment schemes to improve patient throughput and make PT more cost effective.

Investigation of Halcyon multi-leaf collimator model in Eclipse treatment planning system: A focus on the VMAT dose calculation with the Acuros XB algorithm.

PurposeThe dual‐layer multi‐leaf collimator (MLC) in Halcyon involves further complexities in the dose calculation process, because the leaf‐tip transmission varies according to the leaf trailing pattern. For the volumetric modulated arc therapy (VMAT) treatment, the prescribed dose for the target volume can be sensitive to the leaf‐tip transmission change. This report evaluates the dosimetric consequence due to the uncertainty of the dual‐layer MLC model in Eclipse through the dose verifications for clinical VMAT. Additionally, the Halcyon leaf‐tip model is empirically adjusted for the VMAT dose calculation with the Acuros XB.Materials and methodsFor this evaluation, an in‐house program that analyzes the leaf position in each layer was developed. Thirty‐two clinical VMAT plans were edited into three leaf sequences: dual layer (original), proximal single layer, or distal single layer. All leaf sequences were verified using Delta4 according to the dose difference (DD) and the global gamma index (GI). To improve the VMAT dose calculation accuracy, the dosimetric leaf gap (DLG) was adjusted to minimize the DD in single‐layer leaf sequences.ResultsThe mean of DD were −1.35%, −1.20%, and −1.34% in the dual‐layer, proximal single‐layer, and distal single‐layer leaf sequences, respectively. The changes in the mean of DD between leaf sequences were within 0.2%. However, the calculated doses differed from the measured doses by approximately 1% in all leaf sequences. The tuned DLG was increased by 0.8 mm from the original DLG in Eclipse. When the tuned DLG was used in the dose calculation, the mean of DD neared 0% and GI with a criterion of 2%/2 mm yielded a pass rate of more than 98%.ConclusionNo significant change was confirmed in the dose calculation accuracy between the leaf sequences. Therefore, it is suggested that the dosimetric consequence due to the leaf trailing was negligibly small in clinical VMAT plans. The DLG tuning for Halcyon can be useful for reducing the dose calculation uncertainties in Eclipse VMAT and required in the commissioning for Acuros XB.

Sensitivity analysis in a radiological impact assessment of a nuclear power plant discharge. A comparison of the Morris, Spearman and Sobol’ approaches

This paper compares the Morris, Spearman and Sobol’ methods of sensitivity analysis in radiological risk assessment. The determination of the most influential parameters on model with regards to the propagation of their uncertainties to output variables, is of greatest interest. This study aims to determine the relative importance of parameters uncertainties on the dose calculation uncertainty in the framework of a scenario of routine discharges discussed in the context of an IAEA working group. The scenario considers atmospheric and liquid discharges of three different types of radionuclides (14C, tritium as HTO and 110mAg) from a nuclear power plant located by the side of a river. It is concluded that the most reliable and practical method according to the ability of ranking influential parameters and the easiness of its application is the Spearman method. As key result, the three first influential variables for annual total dose for all pathways and all radionuclides were the water dissolved inorganic carbon concentration, the volatilisation rate constant and the soil layer solid liquid distribution in 14C.

Skin dose measurement and estimating the dosimetric effect of applicator misplacement in gynecological brachytherapy: A patient and phantom study.

To evaluate skin dose differences between TPS (treatment planning system) calculations and TLD (thermo-luminescent dosimeters) measurements along with the dosimetric effect of applicator misplacement for patients diagnosed with gynecological (GYN) cancers undergoing brachytherapy. The skin doses were measured using TLDs attached in different locations on patients' skin in pelvic regions (anterior, left, and right) for 20 patients, as well as on a phantom. In addition, the applicator surface dose was calculated with TLDs attached to the applicator. The measured doses were compared with TPS calculations to find TPS accuracy. For the phantom, different applicator shifts were applied to find the effect of applicator misplacement on the surface dose. The mean absolute dose differences between the TPS and TLDs results for anterior, left, and right points were 3.14±1.03, 6.25±1.88, and 6.20±1.97 %, respectively. The mean difference on the applicator surface was obtained 1.92±0.46 %. Applicator misplacements of 0.5, 2, and 4 cm (average of three locations) resulted in 9, 36, and 61%, dose errors respectively. The surface/skin differences between the calculations and measurements are higher in the left and right regions, which relate to the higher uncertainty of TPS dose calculation in these regions. Furthermore, applicator misplacements can result in high skin dose variations, therefore it can be an appropriate quality assurance method for future research.

A Review of the Robust Optimization Process and Advances with Monte Carlo in the Proton Therapy Management of Head and Neck Tumors.

In intensity-modulated proton therapy, robust optimization processes have been developed to manage uncertainties associated with (1) range, (2) setup, (3) anatomic changes, (4) dose calculation, and (5) biological effects. Here we review our experience using a robust optimization technique that directly incorporates range and setup uncertainties into the optimization process to manage those sources of uncertainty. We also review procedures for implementing adaptive planning to manage the anatomic uncertainties. Finally, we share some early experiences regarding the impact of uncertainties in dose calculation and biological effects, along with techniques to manage and potentially reduce these uncertainties.

The robustness of prostate radiotherapy for patients with hip prosthesis

The aim of this study was to investigate prostate radiotherapy techniques for the patients with hip prosthesis in 4 different field setups. Volumetric Modulated Arc Therapy (VMAT) technique was used in 4 different cases: (1) using full VMAT arcs (VMAT_F); (2) same arcs as in case 1 but with avoidance sectors (VMAT_ASEC); (3) as case 2 but with the addition of a lateral static field through the prosthesis (VMAT_ASEC+STAT); (4) as in case 1 but with an automated structure avoidance option to avoid irradiation through the prosthesis (VMAT_ASTR). Fifteen previously treated prostate patients were retrospectively selected to this study. Treatment plans were created for all patients using all 4 techniques. The potential prosthesis misalignment in the treatment setup was modeled by moving the prosthesis 0.5, 1.0, and 1.5 cm ventrally and dorsally and recalculating the plans in each case. For VMAT_ASEC, the dose parameters for organs at risk were the highest and the dose coverage of the target volume was the poorest when compared to the other techniques. For VMAT_ASEC+STAT, the movement of the prosthesis changed the target dose distribution the most. VMAT_F and VMAT_ASTR fulfilled the planning criteria the best, even when the prosthesis was misaligned. VMAT_F radiated through the prosthesis more than VMAT_ASTR and increased the dose near the prosthesis surface when compared to VMAT_ASTR. VMAT_ASTR and VMAT_F were the most robust techniques for the patients with the hip prosthesis considering plan quality and the effect of positioning errors. The increased prosthesis surface dose with VMAT_F and possible dose calculation uncertainties favors the use of VMAT_ASTR.

Monte Carlo evaluation of target dose coverage in lung stereotactic body radiation therapy with flattening filter-free beams.

Previous studies showed that replacing conventional flattened beams (FF) with flattening filter-free (FFF) beams improves the therapeutic ratio in lung stereotactic body radiation therapy (SBRT), but these findings could have been impacted by dose calculation uncertainties caused by the heterogeneity of the thoracic anatomy and by respiratory motion, which were particularly high for target coverage. In this study, we minimized such uncertainties by calculating doses using high-spatial-resolution Monte Carlo and four-dimensional computed tomography (4DCT) images. We aimed to evaluate more reliably the benefits of using FFF beams for lung SBRT. For a cohort of 15 patients with early stage lung cancer that we investigated in a previous treatment planning study, we recalculated dose distributions with Monte Carlo using 4DCT images. This included fifteen FF and fifteen FFF treatment plans. Compared to Monte Carlo, the treatment planning system (TPS) over-predicted doses in low-dose regions of the planning target volume. For most patients, replacing FF beams with FFF beams improved target coverage, tumor control, and uncomplicated tumor control probabilities. Monte Carlo tends to reveal deficiencies in target coverage compared to coverage predicted by the TPS. Our data support previously reported benefits of using FFF beams for lung SBRT.

Commissioning and clinical implementation of Mobius3D and MobiusFX: Experience on multiple linear accelerators.

To provide practical guidelines for Mobius3D commissioning based on experiences of commissioning/clinical implementation of Mobius3D and MobiusFX as patient-specific quality assurance tools on multiple linear accelerators. The vendor-suggested Mobius3D commissioning procedures, including beam model adjustment and dosimetric leaf gap (DLG) optimization, were performed for 6 MV X-ray beams of six Elekta linear accelerators. For the beam model adjustment, beam data, such as the percentage depth dose, off-axis ratio (OAR), and output factor (OF), were measured using a water phantom and compared to the vendor-provided reference values. DLG optimization was performed to determine an optimal DLG correction factor to minimize the mean difference between Mobius3D-calculated and measured doses for multiple volumetric modulated arc therapy (VMAT) plans. Small-field VMAT plans, in which Mobius3D has dose calculate uncertainties, were initially included in the DLG optimization, but excluded later. The measured beam data were consistent across the six linear accelerators. Relatively large differences between the reference and measured values were observed for the OAR at large off-axis distances (>5 cm) and for the OF for small fields (<3 × 3 cm2). The optimal DLG correction factor was 0.6 ± 0.3 (range: 0.3-1.0) with small-field plans and 0.2 ± 0.2 (0.0-0.5) without them. A reasonable agreement was found between the vendor-provided reference and measured beam models. DLG optimization results were dependent on the selection of the VMAT plans, requiring careful attention to the known dose calculation uncertainties of Mobius3D when determining a DLG correction factor.

Monte Carlo calculations of radiotherapy dose in "homogeneous" anatomy.

Given the substantial literature on the use of Monte Carlo (MC) simulations to verify treatment planning system (TPS) calculations of radiotherapy dose in heterogeneous regions, such as head and neck and lung, this study investigated the potential value of running MC simulations of radiotherapy treatments of nominally homogeneous pelvic anatomy. A pre-existing in-house MC job submission and analysis system, built around BEAMnrc and DOSXYZnrc, was used to evaluate the dosimetric accuracy of a sample of 12 pelvic volumetric arc therapy (VMAT) treatments, planned using the Varian Eclipse TPS, where dose was calculated with both the Analytical Anisotropic Algorithm (AAA) and the Acuros (AXB) algorithm. In-house TADA (Treatment And Dose Assessor) software was used to evaluate treatment plan complexity, in terms of the small aperture score (SAS), modulation index (MI) and a novel exposed leaf score (ELS/ELA). Results showed that the TPS generally achieved closer agreement with the MC dose distribution when treatments were planned for smaller (single-organ) targets rather than larger targets that included nodes or metastases. Analysis of these MC results with reference to the complexity metrics indicated that while AXB was useful for reducing dosimetric uncertainties associated with density heterogeneity, the residual TPS dose calculation uncertainties resulted from treatment plan complexity and TPS model simplicity. The results of this study demonstrate the value of using MC methods to recalculate and check the dose calculations provided by commercial radiotherapy TPSs, even when the treated anatomy is assumed to be comparatively homogeneous, such as in the pelvic region.

Generation of Virtual Non-Contrast CT From Intravenous Enhanced CT in Radiotherapy Using Convolutional Neural Networks.

Objective: To generate virtual non-contrast (VNC) computed tomography (CT) from intravenous enhanced CT through convolutional neural networks (CNN) and compare calculated dose among enhanced CT, VNC, and real non-contrast scanning.Method: 50 patients who accepted non-contrast and enhanced CT scanning before and after intravenous contrast agent injections were selected, and two sets of CT images were registered. A total of 40 and 10 groups were used as training and test datasets, respectively. The U-Net architecture was applied to learn the relationship between the enhanced and non-contrast CT. VNC images were generated in the test through the trained U-Net. The CT values of non-contrast, enhanced and VNC CT images were compared. The radiotherapy treatment plans for esophageal cancer were designed, and dose calculation was performed. Dose distributions in the three image sets were compared.Results: The mean absolute error of CT values between enhanced and non-contrast CT reached 32.3 ± 2.6 HU, and that between VNC and non-contrast CT totaled 6.7 ± 1.3 HU. The average CT values in enhanced CT of great vessels, heart, lungs, liver, and spinal cord were all significantly higher than those of non-contrast CT (p < 0.05), with the differences reaching 97, 83, 42, 40, and 10 HU, respectively. The average CT values of the organs in VNC CT showed no significant differences from those in non-contrast CT. The relative dose differences of the enhanced and non-contrast CT were −1.2, −1.3, −2.1, and −1.5% in the comparison of mean doses of planned target volume, heart, great vessels, and lungs, respectively. The mean dose calculated by VNC CT showed no significant difference from that by non-contrast CT. The average γ passing rate (2%, 2 mm) of VNC CT image was significantly higher than that of enhanced CT image (0.996 vs. 0.973, p < 0.05).Conclusion: Designing a treatment plan based on enhanced CT will enlarge the dose calculation uncertainty in radiotherapy. This paper proposed the generation of VNC CT images from enhanced CT images based on U-Net architecture. The dose calculated through VNC CT images was identical with that obtained through real non-contrast CT.