Analysis of the bias induced by voxel and unstructured mesh Monte Carlo models for the MCNP6 code in orthovoltage applications

Photon-counting CT (PCCT) is the latest technology enabling imaging with reduced noise and inherent spectral separation, with the potential to directly calculate a more accurate tissue stopping power from spectral data. This potential benefit is difficult to quantify in practice and is currently evaluated mainly in phantoms with simplified geometries that only approximate real patient anatomy. In this work, we proposed virtual imaging simulators as an alternative approach to experimental validation of beam range uncertainty in complex patient geometry using a computational model of a human head and a CT system. In addition, we validate the accuracy of stopping power ratio (SPR) calculations on a model of a PCCT scanner using a conventional stoichiometric calibration approach and a prototype software TissueXplorer. A validated CT simulator (DukeSim) was used to generate PCCT projections of a computational head phantom, which were reconstructed with an open-source toolbox (ASTRA). The dose of 2 Gy was delivered through protons in a single fraction to target two different cases of nasal and brain tumors. The ground-truth treatment plan was made directly on the computational phantom using clinical treatment planning software (RayStation). This plan was then recalculated on the corresponding CT images for which SPR values were estimated using both the conventional method and the prototype software TissueXplorer. The resulting dose distributions were subsequently compared against the ground-truth plan to quantify dose differences arising from SPR estimation. The mean percentage difference in estimating the SPR with TissueXplorer in all head tissues inside the scanned volume was 0.28%. SPRs obtained with this method showed smaller dose distribution differences from the ground truth plan than the conventional stoichiometric calibration method on the computational head phantom. Virtual imaging offers an alternative approach to validation of the SPR prediction from CT imaging, as well as its effect on the dose distribution and thus downstream clinical outcomes. According to this simulation study, software solutions that utilize spectral information hold promise for more accurate prediction of the SPR than the conventional stoichiometricapproach.

Estimation of secondary cancer risks following rectal cancer photon and proton therapy: A computational phantom study.

The use of non-ionizing electric fields from low-intensity voltage sources (<10 V) to control malignant tumor growth is showing increasing potential as a cancer treatment modality. A method of applying these low-intensity electric fields using multiple implanted electrodes within or adjacent to tumor volumes has been termed as intratumoral modulation therapy (IMT). This study explores advancements in the previously established IMT optimization algorithm, and the development of a custom treatment planning system for patient-specific IMT. The practicality of the treatment planning system is demonstrated by implementing the full optimization pipeline on a brain phantom with robotic electrode implantation, postoperative imaging, and treatment stimulation. The integrated planning pipeline in 3D Slicer begins with importing and segmenting patient magnetic resonance images (MRI) or computed tomography (CT) images. The segmentation process is manual, followed by a semi-automatic smoothing step that allows the segmented brain and tumor mesh volumes to be smoothed and simplified by applying selected filters. Electrode trajectories are planned manually on the patient MRI or CT by selecting insertion and tip coordinates for a chosen number of electrodes. The electrode tip positions and stimulation parameters (phase shift and voltage) can then be optimized with the custom semi-automatic IMT optimization algorithm where users can select the prescription electric field, voltage amplitude limit, tissue electrical properties, nearby organs at risk, optimization parameters (electrode tip location, individual contact phase shift and voltage), desired field coverage percent, and field conformity optimization. Tables of optimization results are displayed, and the resulting electric field is visualized as a field-map superimposed on the MR or CT image, with 3D renderings of the brain, tumor, and electrodes. Optimized electrode coordinates are transferred to robotic electrode implantation software to enable planning and subsequent implantation of the electrodes at the desired trajectories. An IMT treatment planning system was developed that incorporates patient-specific MRI or CT, segmentation, volume smoothing, electrode trajectory planning, electrode tip location and stimulation parameter optimization, and results visualization. All previous manual pipeline steps operating on diverse software platforms were coalesced into a single semi-automated 3D Slicer-based user interface. Brain phantom validation of the full system implementation was successful in preoperative planning, robotic electrode implantation, and postoperative treatment planning to adjust stimulation parameters based on actual implant locations. Voltage measurements were obtained in the brain phantom to determine the electrical parameters of the phantom and validate the simulated electric field distribution. A custom treatment planning and implantation system for IMT has been developed in this study and validated on a phantom brain model, providing an essential step in advancing IMT technology toward future clinical safety and efficacy investigations.

Purpose: Dose calculation for lung tumors can be challenging due to the low density and the fine structure of the geometry. The latter is not fully considered in the CT image resolution used in treatment planning causing the prediction of a more homogeneous tissue distribution. In proton therapy, this could result in predicting an unrealistically sharp distal dose falloff, i.e. an underestimation of the distal dose falloff degradation. The goal of this work was the quantification of such effects. Methods: Two computational phantoms, resembling a two‐dimensional heterogeneous random lung geometry and a swine lung were considered applying a variety of voxel sizes for dose calculation. Monte Carlo simulations were used to compare the dose distributions predicted with the voxel size typically used for the treatment planning procedure with those expected to be delivered using the finest resolution. Results: The results show, for example, distal falloff position differences of up to 4 mm between planned and expected dose at the 90% level for the heterogeneous random lung (assuming treatment plan on a 2×2×2.5 mm3 grid). For the swine lung, differences of up to 38 mm were seen when airways are present in the beam path when the treatment plan was done on a 0.8×0.8×2.4 mm3 grid.Conclusion: The two‐dimensional heterogeneous random lung phantom apparently does not describe the impact of the geometry adequately because of the lack of heterogeneities in the axial direction. The differences observed in the swine lung between planned and expected dose are presumably due to the poor axial resolution of the CT images used in clinical routine. In conclusion, when assigning margins for treatment planning for lung cancer, proton range uncertainties due to the heterogeneous lung geometry and CT image resolution need to be considered.

Purpose:Radiation‐induced cancer effects are well‐documented following radiotherapy. Further investigation is needed to more accurately determine a dose‐response relationship for late radiation effects. Recent dosimetry studies tend to use representative patients (Taylor 2009) or anthropomorphic phantoms (Wirth 2008) for estimating organ mean doses. In this study, we compare hybrid computational phantoms to patient‐specific voxel phantoms to test the accuracy of University of Florida Hybrid Phantom Library (UFHP Library) for historical dose reconstructions.Methods:A cohort of 10 patients with CT images was used to reproduce the data that was collected historically for Hodgkin's lymphoma patients (i.e. caliper measurements and photographs). Four types of phantoms were generated to show a range of refinement from reference hybrid‐computational phantom to patient‐specific phantoms. Each patient is matched to a reference phantom from the UFHP Library based on height and weight. The reference phantom is refined in the anterior/posterior direction to create a ‘caliper‐scaled phantom’. A photograph is simulated using a surface rendering from segmented CT images. Further refinement in the lateral direction is performed using ratios from a simulated‐photograph to create a ‘photograph and caliper‐scaled phantom’; breast size and position is visually adjusted. Patient‐specific hybrid phantoms, with matched organ volumes, are generated and show the capabilities of the UF Hybrid Phantom Library. Reference, caliper‐scaled, photograph and caliper‐scaled, and patient‐specific hybrid phantoms are compared with patient‐specific voxel phantoms to determine the accuracy of the study.Results:Progression from reference phantom to patient specific hybrid shows good agreement with the patient specific voxel phantoms. Each stage of refinement shows an overall trend of improvement in dose accuracy within the study, which suggests that computational phantoms can show improved accuracy in historical dose estimates.Conclusion:Computational hybrid phantoms show promise for improved accuracy within retrospective studies when CTs and other x‐ray images are not available.

Background: Computed tomography (CT) is one of the crucial diagnostic tools in modern medicine. However, careful monitoring of radiation dose for CT patients is essential since the procedure involves ionizing radiation, a known carcinogen.Materials and Methods: The most desirable CT dose descriptor for risk analysis is the organ absorbed dose. A variety of CT organ dose calculators currently available were reviewed in this article.Results and Discussion: Key common elements included in CT dose calculators were discussed and compared, such as computational human phantoms, CT scanner models, organ dose database, effective dose calculation methods, tube current modulation modeling, and user interface platforms.Conclusion: It is envisioned that more research needs to be conducted to more accurately map CT coverage on computational human phantoms, to automatically segment organs and tissues for patient-specific dose calculations, and to accurately estimate radiation dose in the cone beam computed tomography process during image-guided radiation therapy.

Purpose: Epidemiological study of second cancer risk for cancer survivors often requires the dose to normal tissues located outside the anatomy covered by radiological imaging, which is usually limited to tumor and organs at risk. We have investigated the feasibility of using whole body computational human phantoms for estimating out-of-field organ doses for patients treated by Intensity Modulated Radiation Therapy (IMRT). Methods: Identical 7-field IMRT prostate plans were performed using X-ray Voxel Monte Carlo (XVMC), a radiotherapy-specific Monte Carlo transport code, on the computed tomography (CT) images of the torso of an adult male patient (175 cm height, 66 kg weight) and an adult male hybrid computational phantom with the equivalent body size. Dose to the liver, right lung, and left lung were calculated and compared. Results: Considerable differences are seen between the doses calculated by XVMC for the patient CT and the hybrid phantom. One major contributing factor is the treatment method, deep inspiration breath hold (DIBH), used for this patient. This leads to significant differences in the organ position relative to the treatment isocenter. The transverse distances from the treatment isocenter to the inferior border of the liver, left lung, and right lung are 19.5cm, 29.5cm, and 30.0cm, respectively for the patient CT, compared with 24.3cm, 36.6cm, and 39.1cm, respectively, for the hybrid phantom. When corrected for the distance, the mean doses calculated using the hybrid phantom are within 28% of those calculated using the patient CT. Conclusion: This study showed that mean dose to the organs located in the missing CT coverage can be reconstructed by using whole body computational human phantoms within reasonable dosimetric uncertainty, however appropriate corrections may be necessary if the patient is treated with a technique that will significantly deform the size or location of the organs relative to the hybrid phantom.

X-ray CT examinations are required not only in routine medical examinations but also in various situations such as emergency medical care. Although medical staff may be exposed to radiation when assisting patients, the distribution of air-absorbed doses in the CT examination room when using a special protective shield for CT has not been clarified. Here, we measured air-absorbed doses at several points simultaneously to clarify the distribution of these doses and the effect of a special protective shield for CT in reducing them. A human phantom was imaged with an X-ray CT system. The absorbed dose in the air dose profile distribution was measured with an OSL dosimeter in the presence and absence of a special protective shield for CT. The highest air absorbed doses of 4.27 mGy were at 0 cm in the horizontal direction, 120 cm in the vertical direction, and 50 cm in the body axis direction. The largest reduction in air absorbed dose following installation of the special protective shield for CT was 91.7%, obtained at 0 cm in the horizontal direction, 150 cm in the vertical direction, and 50 cm in the body axis direction. A 91.7% reduction in air-absorbed dose was o directly behind the special protective shield for CT. The reduction in air-absorbed dose was 65.8% at the location of a gap between the special protective shield for CT and gantry.

Purpose: Characterize a medical linear accelerator using Monte Carlo methods to investigate the precision and exactitude of dose delivery on small animal irradiation, particularly Wistar rat species. Method and Materials: A dedicated 6.0 MV linear accelerator (Novalis®, BrainLAB, Germany) for stereotactic radiosurgery (SRS) was simulated using BEAMnrc. A phase space (PS) data file was generated. The Monte Carlo (MC) calculations were tuned and validated to match depth and off‐axis dose profile data measured using a shielded diode detector (PFD3G, IBA‐dosimetry, Germany) for a 15.0 mm circular collimator. The animal model was based on a computed tomography (CT) scan of a Wistar rat for medullar trauma lesion model. An in‐house mask fixation system compatible with the treatment planning system (TPS) was developed to immobilize the rat. The CT scan images were imported to DOSXYZnrc using ctcreate tool and to the TPS via DICOM network. Dose distribution was calculated by the TPS using 2 non‐coplanar circular (NCAs). The NCAs were simulated using 20 static beams. The MC dose calculations were exported for analysis and compared with TPS dose calculations. On the other hand, absolute dose measurements were performed using the PFD3G inter calibrated using a Farmer type ionization chamber. Results: Absolute dose measurements showed that dose difference between TPS and treatment delivery is less than 4.3% on the selected points. Difference between TPS and MC dose calculations showed an over‐estimation by the TPS up to 15.0%. However, in the spinal cord lesion there is a good agreement between TPS and MC calculated data. Conclusion: Dose delivered by the dedicated linear accelerator is reliable to perform spinal cord irradiation in trauma lesion models. These preliminary results must be improved including an accurate source model of an arc radiation beam instead of the 20 discrete static beams.

BackgroundThe purpose of this study was to compare dose distributions from three different algorithms with the x-ray Voxel Monte Carlo (XVMC) calculations, in actual computed tomography (CT) scans for use in stereotactic radiotherapy (SRT) of small lung cancers.MethodsSlow CT scan of 20 patients was performed and the internal target volume (ITV) was delineated on Pinnacle3. All plans were first calculated with a scatter homogeneous mode (SHM) which is compatible with Clarkson algorithm using Pinnacle3 treatment planning system (TPS). The planned dose was 48 Gy in 4 fractions. In a second step, the CT images, structures and beam data were exported to other treatment planning systems (TPSs). Collapsed cone convolution (CCC) from Pinnacle3, superposition (SP) from XiO, and XVMC from Monaco were used for recalculating. The dose distributions and the Dose Volume Histograms (DVHs) were compared with each other.ResultsThe phantom test revealed that all algorithms could reproduce the measured data within 1% except for the SHM with inhomogeneous phantom. For the patient study, the SHM greatly overestimated the isocenter (IC) doses and the minimal dose received by 95% of the PTV (PTV95) compared to XVMC. The differences in mean doses were 2.96 Gy (6.17%) for IC and 5.02 Gy (11.18%) for PTV95. The DVH's and dose distributions with CCC and SP were in agreement with those obtained by XVMC. The average differences in IC doses between CCC and XVMC, and SP and XVMC were -1.14% (p = 0.17), and -2.67% (p = 0.0036), respectively.ConclusionsOur work clearly confirms that the actual practice of relying solely on a Clarkson algorithm may be inappropriate for SRT planning. Meanwhile, CCC and SP were close to XVMC simulations and actual dose distributions obtained in lung SRT.

Adaptive statistical iterative reconstruction (ASIR) is a reconstruction technique for computed tomography (CT) that reduces image noise. The purpose of our study was to investigate whether ASIR improves the quality of volume-rendered (VR) CT portovenography. Institutional review board approval, with waived consent, was obtained. A total of 19 patients (12 men, 7 women; mean age 69.0 years; range 25-82 years) suspected of having liver lesions underwent three-phase enhanced CT. VR image sets were prepared with both the conventional method and ASIR. The required time to make VR images was recorded. Two radiologists performed independent qualitative evaluations of the image sets. The Wilcoxon signed-rank test was used for statistical analysis. Contrast-noise ratios (CNRs) of the portal and hepatic vein were also evaluated. Overall image quality was significantly improved by ASIR (P < 0.0001 and P = 0.0155 for each radiologist). ASIR enhanced CNRs of the portal and hepatic vein significantly (P < 0.0001). The time required to create VR images was significantly shorter with ASIR (84.7 vs. 117.1 s; P = 0.014). ASIR enhances CNRs and improves image quality in VR CT portovenography. It also shortens the time required to create liver VR CT portovenographs.

Ion therapy guideline (Version 2020)

Application of the measurement-based Monte Carlo method in nasopharyngeal cancer patients for intensity modulated radiation therapy

Background HDR brachytherapy is one of the commonest methods of nasopharyngeal cancer treatment. In this method, depending on how advanced one tumor is, 2 to 6 Gy dose as intracavitary brachytherapy is prescribed. Due to high dose rate and tumor location, accuracy evaluation of treatment planning system (TPS) is particularly important. Common methods used in TPS dosimetry are based on computations in a homogeneous phantom. Heterogeneous phantoms, especially patient-specific voxel phantoms can increase dosimetric accuracy.Materials and MethodsIn this study, using CT images taken from a patient and ctcreate-which is a part of the DOSXYZnrc computational code, patient-specific phantom was made. Dose distribution was plotted by DOSXYZnrc and compared with TPS one. Also, by extracting the voxels absorbed dose in treatment volume, dose-volume histograms (DVH) was plotted and compared with Oncentra™ TPS DVHs.ResultsThe results from calculations were compared with data from Oncentra™ treatment planning system and it was observed that TPS calculation predicts lower dose in areas near the source, and higher dose in areas far from the source relative to MC code. Absorbed dose values in the voxels also showed that TPS reports D90 value is 40% higher than the Monte Carlo method.ConclusionToday, most treatment planning systems use TG-43 protocol. This protocol may results in errors such as neglecting tissue heterogeneity, scattered radiation as well as applicator attenuation. Due to these errors, AAPM emphasized departing from TG-43 protocol and approaching new brachytherapy protocol TG-186 in which patient-specific phantom is used and heterogeneities are affected in dosimetry.

Due to the complexity of radiotherapy techniques, rigorous Patient-Specific Quality Assurance (PSQA) is crucial to ensure the accuracy of treatment plans. This study aims to evaluate the performance of the Treatment Planning System (TPS) by comparing its dose distribution calculations with those obtained from the PRIMO Monte Carlo simulation. Treatment plans for 3D-CRT, IMRT, and VMAT were generated for a Rando breast phantom using the TPS. Subsequently, the dose distributions from the TPS were compared with those obtained from the PRIMO Monte Carlo simulation. Key metrics, including Homogeneity Index (HI) and Conformity Index (CI), were calculated to assess the quality of dose distribution. Furthermore, the dose constraints on OARs were evaluated to assess the impact on surrounding healthy tissues. To further validate the TPS, dose distributions from the linac log file (Dynalog) for VMAT were reconstructed within the PRIMO environment. These reconstructed distributions were then compared with the dose distributions calculated directly by the TPS. Gamma index analysis was employed to evaluate the agreement between these two sets of data. The comparison between TPS and Monte Carlo simulations revealed that 3D-CRT plans exhibited smaller deviations in HI and CI compared to IMRT and VMAT plans. However, a significant improvement in HI and CI values was observed in both IMRT planning simulations and Dynalog VMAT file simulations, indicating enhanced plan quality. The dose received by OARs in all treatment plans remained within the acceptable dose thresholds, demonstrating effective sparing of surrounding healthy tissues. For the PSQA procedure, the 3D-CRT technique is still the safest due to its lower level of complexity compared to IMRT and VMAT. More complex treatments should consider the robustness of treatment transfer information from TPS to linac to avoid dosimetry errors.