Three-dimensional Dose Distributions Research Articles

EyeDose: An open-source tool for using published Monte Carlo results to estimate the radiation dose delivered to the tumor and critical ocular structures for 125I Collaborative Ocular Melanoma Study eye plaques

PurposeRadiation side effects and visual outcome for uveal melanoma patients managed with plaque radiotherapy are dependent on the radiation dose administered to the tumor and nearby healthy tissues. We have developed an open-source software tool, EyeDose, to simplify and standardize tumor and critical structure dose reporting for Collaborative Ocular Melanoma Study eye plaques. Methods and MaterialsEyeDose is a MATLAB-based program that calculates point dose and volume dose metrics for standard models of the tumor and critical ocular structures. It uses published three-dimensional dose distributions for eye plaques, calculated with Monte Carlo methods, which are oriented with respect to the eye using the tumor's position on a fundus diagram. A standard model for the ocular structures was created using published measurements and patient CT scans. EyeDose reports radiation statistics for the fovea, optic disc, lens, lacrimal gland, retina, and tumor. The dosimetric margin for implant placement uncertainty is also calculated. ResultsEyeDose calculations were validated against previously published Monte Carlo results for eight different tumor positions, including the dose to the fovea, optic disc, lacrimal gland, lens, and along the central axis. EyeDose accepts a spreadsheet input for rapidly processing large retrospective patient data sets, with an average run time of <40 s per patient. EyeDose is published as an open-source tool for easy adaptation at different institutions. ConclusionsEyeDose calculates radiation statistics for Collaborative Ocular Melanoma Study eye plaque patients with Monte Carlo accuracy and without a treatment planning system. EyeDose streamlines data collection for large retrospective studies and can also be used prospectively to assess plaque applicability.

Verification of the Machine Delivery Parameters of Treatment Plan via Deep Learning

To develop a generative adversarial network (GAN)-based deep learning approach to estimate the multileaf collimator (MLC) aperture and corresponding monitor units (MUs) from a given three-dimensional (3D) dose distribution. We developed a treatment plan verification framework by implementing a modified pix2pix network to learn a mapping between CT, segment 3D dose and MUs/MLC shapes. The proposed design of adversarial network, which integrates a residual block into pix2pix framework, jointly trains a “U-Net”-like architecture as generator and a convolutional “PatchGAN” classifier as discriminator. 199 patients, including nasopharyngeal, lung and rectum, treated with intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) techniques were utilized to train the network. The resliced volumetric dose of each segment and CT image datasets were labeled by the corresponding MUs/MLC maps. Additional 47 patients were used to test the prediction accuracy of the proposed deep learning model. The Dice similarity coefficient (DSC) was calculated to evaluate the similarity between the MLC aperture shapes obtained from the treatment planning system (TPS) and the deep learning prediction. The average and standard deviation of the bias between the TPS generated MUs and predicted MUs were calculated to evaluate the MU prediction accuracy. Additionally, the differences between TPS and deep learning-predicted MLC leaf positions were compared. The model performance was first evaluated by five simple fields, including four square fields and one irregular field. The DSC is found to be 0.99, 0.99, 0.99, 0.98 and 0.96, respectively. And the MUs prediction agree with the original plans to within 5%. The average and standard deviation of DSC was 0.94 ± 0.043 for 47 testing patients. The average deviation of predicted MUs from the planned MUs normalized to each beam or arc was within 2% for all the testing patients. The average deviation of the predicted MLC leaf positions was around one pixel for all the testing patients. A novel pix2pix deep learning network was developed to predict MUs/MLC shapes for treatment plan verification. It is the first attempt in using deep learning method to predict fundamental machine delivery parameters and it may provide radiation oncology community a useful tool for improving the efficiency and accuracy of patient specific QA and plan second check process.

EyeDose: An Open Source Tool For Calculating The Radiation Dose Delivered To The Tumor And Critical Ocular Structures For 125I COMS Eye Plaques

Radiation side effects and visual outcome for uveal melanoma patients managed with plaque radiotherapy are dependent on the radiation dose administered to the tumor and nearby healthy tissues. The AAPM Task Group Report 129 recommends that the dose to critical normal structures be recorded, preferably using heterogeneity corrected dose distributions. We have developed an open source software tool, EyeDose, to simplify and standardize tumor and critical structure dose reporting for COMS eye plaques. This work builds upon the accomplishments of previous researchers and aims to combine the best features of prior tools, including the accuracy of Monte Carlo, the elimination of manual contouring and the treatment planning system, the standardization of eye geometry, and precise plaque localization using high resolution fundus diagrams. The software may be used for prospective clinical decision making, for example to help with plaque size selection or a comparison of plaque radiotherapy versus proton therapy, or to rapidly process large retrospective data sets, without repetitive manual entry, for reporting on the relationships between dosimetry and outcomes. EyeDose is a Matlab program that calculates point and volume (DVH) dose metrics for the tumor and critical ocular structures. The three-dimensional dose distributions for 125I Collaborative Ocular Melanoma Study (COMS) eye plaques, calculated with Monte Carlo methods, are oriented with respect to the eye using the tumor’s position on a fundus diagram. A standard model for the ocular structures was created using published measurements and patient CT scans. EyeDose reports radiation statistics for the fovea, optic disc, lens, lacrimal gland, retina, and tumor. The dosimetric margin for implant placement uncertainty is also calculated. EyeDose calculations were validated against published Monte Carlo results for nasal, temporal, inferior, and superior tumor positions, including the dose to the fovea, optic disc, lacrimal gland, lens, and along the central axis. The EyeDose program demonstrated close agreement with published Monte Carlo results. The mean, median, and maximum point dose differences between EyeDose and previous Monte Carlo studies were 0.0, 0.0, and 0.5 Gy. The mean difference, reported as %volume, among the DVH calculations was -0.2% ± 0.2% (Std. Dev.) with a range from -1.08% to 0.05%. The execution time averaged <40 sec. per patient on an Intel i-5-6500 CPU @ 3.20 GHz with 32 GB RAM. EyeDose is published as an open source tool for easy adaptation at different institutions. EyeDose calculates radiation statistics for COMS eye plaque patients with Monte Carlo accuracy and without a treatment planning system. EyeDose streamlines data collection for large retrospective studies and can also be used prospectively to assess plaque applicability.

A preliminary study of a photon dose calculation algorithm using a convolutional neural network

The aim of dose calculation algorithm research is to improve the calculation accuracy while maximizing the calculation efficiency. In this study, the three-dimensional distribution of total energy release per unit mass (TERMA) and the electron density (ED) distribution are considered inputs in a method for calculating the three-dimensional dose distribution based on a convolutional neural network (CNN). Attempts are made to improve the efficiency of the collapsed cone convolution/superposition (CCCS) algorithm while providing an approach to improve the efficiency of other traditional dose calculation algorithms. Twelve sets of computed tomography (CT) images were employed for training. Data sets were generated by the CCCS algorithm with a random beam configuration. For each monoenergetic photon model, 7500 samples were generated for the training set, and 1500 samples were generated for the validation set. Training occurred for 0.5 MeV, 1 MeV, 2 MeV, 3 MeV, 4 MeV, 5 MeV, and 6 MeV monoenergetic photon models. To evaluate the usability under linac conditions, a comparison between CCCS and CNN-Dose was performed for the Mohan 6-MV spectrum for 12 additional new sets of CT images with different anatomies. A total of 1512 test samples were generated. For all anatomies, the mean value, 95% lower confidence limit (LCL) and 95% upper confidence limit (UCL) were 99.56%, 99.51% and 99.61%, respectively, at the 3%/2 mm criteria. The mean value, 95% LCL and 95% UCL were 98.57%, 98.46% and 98.67%, respectively, at the 2%/2 mm criteria. The results meet the relevant clinical requirements. In the proposed methods, the dose distribution of clinical energy can be obtained by TERMA, and the electronic density can be obtained with a CNN. This method can also be used for other traditional dose algorithms and displays potential in treatment planning, adaptive radiation therapy, and in vivo verification.

Dose response of three-dimensional silicone-based radiochromic dosimeters for photon irradiation in the presence of a magnetic field.

The magnetic field in magnetic resonance imaging guided radiotherapy (MRgRT) delivery systems influences charged-particle trajectories and hence the three-dimensional (3D) radiation dose distributions. This study investigated the dose-response as well as dose-rate and fractionation dependencies of silicone-based 3D radiochromic dosimeters for photon irradiation in a magnetic field using a 0.35 T MRgRT system. We found a linear dose response up to 22.6 Gy and no significant dose-rate dependency as a function of depth. A difference in optical response was observed for dosimeters irradiated in a single compared to multiple fractions. The dosimeter showed clinical potential for verification of MRgRT delivery.

Behaviour and mechanism of micelle gel dosimeter for carbon-ion-beam irradiation

Micellar gel dosimeters can measure complex three-dimensional dose distributions. However, they have rarely been applied to measure radiation other than X-rays. In this study, we evaluated the radiological characteristics of a micelle gel dosimeter for clinical carbon-ion-beam irradiation. We irradiated a micelle gel dosimeter with a carbon ion beam and determined the reaction rate of the dye by measuring the absorbance after irradiation. In the micellar gel dosimeter used, a drastic change in the reaction rate was observed near the Bragg peak predicted in the treatment plan. In addition, chemical species generated during carbon-ion-beam irradiation were predicted by Monte Carlo simulations. When the measured and calculated results were compared, the reaction rate of the micelle gel dosimeter showed a correlation with the amount of OH radicals generated by the carbon ion beam. The results of this study will help expand the application range of micelle gel dosimeters in cancer therapy.

A robust optimization method for weighted-layer-stacking proton beam therapy

The layer-stacking method can provide three-dimensional conformal dose distributions to the target based on a passive scattering method using mini-spread-out Bragg peak (SOBP). The purpose of this work is to demonstrate the effectiveness of a new weight optimization algorithm that can enhance the robustness of dose distributions against layer depth variation in layer-stacking proton beam therapy.In the robustness algorithm, the upper limit of the layer’s weight was adapted to the conventional algorithm and varied for 620 weight set evaluations. The optimal weight set was selected by using an analytical objective function based on Gaussian function with σ = 3 mm for WED variation. Then, we evaluated the stabilities of the one-dimensional depth dose distribution against WED variation generated by Gaussian samples. Three-dimensional dose distributions in the water phantom were also evaluated using the Monte-Carlo dose calculation. The variation of dose as well as dose volume histograms for the spherical target and the organ at risk (OAR) were evaluated.The robustness algorithm reduced the change of the dose distribution due to the WED variation by a factor of almost 3/4 compared to those with the conventional procedure. The rate of 91.8% in total samples was maintained within 5% change of the maximum dose, compared with the rate of 64.9% in the conventional algorithm. In the MC calculation, the high dose-volume in the OAR was reduced around the lateral penumbra and distal falloff region by the robustness algorithm.The stability of depth dose distributions was enhanced under the WED variation, compared to the conventional algorithm. This robust algorithm in layer-stacking proton therapy may be useful for treatment in which the sharpness of the distal falloff along the depth distribution needs to be maintained to spare the organ at risk and keep the dose coverage for the target tumor.

Validation of the dosimetry of total skin irradiation techniques by Monte Carlo simulation.

PurposeTo validate the dose measurements for two total skin irradiation techniques with Monte Carlo simulation, providing more information on dose distributions, and guidance on further technique optimization.MethodsTwo total skin irradiation techniques (stand‐up and lay‐down) with different setup were simulated and validated. The Monte Carlo simulation was primarily performed within the EGSnrc environment. Parameters of jaws, MLCs, and a customized copper (Cu) filter were first tuned to match the profiles and output measured at source‐to‐skin distance (SSD) of 100 cm where the secondary source is defined. The secondary source was rotated to simulate gantry rotation. VirtuaLinac, a cloud‐based Monte Carlo package, was used for Linac head simulation as a secondary validation. The following quantities were compared with measurements: for each field/direction at the treatment SSDs, the percent depth dose (PDD), the profiles at the depth of maximum, and the absolute dosimetric output; the composite dose distribution on cylindrical phantoms of 20 to 40 cm diameters.ResultsCu filter broadened the FWHM of the electron beam by 44% and degraded the mean energy by 0.7 MeV. At SSD = 100 cm, MC calculated PDDs agreed with measured data within 2%/2 mm (except for the surface voxel) and lateral profiles agreed within 3%. At the treatment SSD, profiles and output factors of individual field matched within 4%; dmax and R80 of the simulated PDDs also matched with measurement within 2 mm. When all fields were combined on the cylindrical phantom, the dmax shifted toward the surface. For lay‐down technique, the maximum x‐ray contamination at the central axis was (MC: 2.2; Measurement: 2.1)% and reduced to 0.2% at 40 cm off the central axis.ConclusionsThe Monte Carlo results in general agree well with the measurement, which provides support in our commissioning procedure, as well as the full three‐dimensional dose distribution of the patient phantom.

Radiotherapy dose distribution prediction for breast cancer using deformable image registration

BackgroundRadiotherapy treatment planning dose prediction can be used to ensure plan quality and guide automatic plan. One of the dose prediction methods is incorporating historical treatment planning data into algorithms to estimate the dose–volume histogram (DVH) of organ for new patients. Although DVH is used extensively in treatment plan quality and radiotherapy prognosis evaluation, three-dimensional dose distribution can describe the radiation effects more explicitly. The purpose of this retrospective study was to predict the dose distribution of breast cancer radiotherapy by means of deformable registration into atlas images with historical treatment planning data that were considered to achieve expert level. The atlas cohort comprised 20 patients with left-sided breast cancer, previously treated by volumetric-modulated arc radiotherapy. The registration-based prediction technique was applied to 20 patients outside the atlas cohort. This study evaluated and compared three different approaches: registration to the most similar image from a dataset of individual atlas images (SIM), registration to all images from a database of individual atlas images with the average method (WEI_A), and the weighted method (WEI_F). The dose prediction performance of each strategy was quantified using nine metrics, including the region of interest dose error, 80% and 100% prescription area dice similarity coefficients (DSCs), and γ metrics. A Friedman test and a nonparametric exact Wilcoxon signed rank test were performed to compare the differences among groups. The clinical doses of all cases served as the gold standard.ResultsThe WEI_F method could achieve superior dose prediction results to those of WEI_A. WEI_F outperformed SIM in the organ-at-risk mean absolute difference (MAD). When using the WEI_F method, the MAD values for the ipsilateral lung, heart, and whole lung were 197.9 ± 42.9, 166 ± 55.1, 122.3 ± 25.5, and 55.3 ± 42.2 cGy, respectively. Moreover, SIM exhibited superior prediction in the DSC and γ metrics. When using the SIM method, the means of the 80% and 100% prescription area DSCs, 33γ metric, and 55γ metric were 0.85 ± 0.05, 0.84 ± 0.05, 0.64 ± 0.13, and 0.84 ± 0.10, respectively. The plan target volume and spinal cord MAD when using SIM and WEI were 235.6 ± 158.4 cGy versus 227.4 ± 144.0 cGy (p > 0.05) and 61.4 ± 44.9 cGy versus 55.3 ± 42.2 cGy (p > 0.05), respectively.ConclusionsA predicted dose distribution that approximated the clinical plan could be generated using the methods presented in this study.

Tomographic-based 3D scintillation dosimetry using a three-view plenoptic imaging system.

To demonstrate the feasibility of a three-plenoptic camera projection, scintillation-based dosimetry system for measuring three-dimensional (3D) dose distributions of static photon radiation fields. Static x-ray photon beams were delivered to a cubic plastic scintillator volume embedded within acrylic blocks. For each beam, three orthogonal projections of the scintillating light emission were recorded using a multifocus plenoptic camera. Experimental 3D reconstructions of the light distribution were obtained using an iterative maximum likelihood-expectation maximization (ML-EM) algorithm. For this purpose, the elements of the system matrix representing the contribution of the scintillator volume voxels to the camera sensor pixels were calculated using optical design software. A reconstruction-specific correction was applied to light reconstructions to account for scintillating light imaged by the camera but not directly resulting from dose deposition. Cross beam profiles (CBPs) and percentage depth dose (PDD) curves were compared to treatment planning system data for square fields. Three-dimensional and 3D gamma analyses were performed for concave-shaped dose distributions and the Pearson correlation coefficient and reconstruction error were employed to assess the quality of the measured relative 3D dose distributions. A full and accurate model of the plenoptic camera-based scintillation dosimetry system was implemented using the light ray tracing capabilities of optical design software. With this model, light distributions were successfully reconstructed over a volume of 60×60×60mm at a resolution of 2mm. For relative 3D measurements of square radiation fields of , and compared with treatment planning system reference distributions, the maximum root-mean-square error of the CBPs evaluated at two different depths was of 3.2%, 1.2%, and 1.1%, respectively; as for the corresponding linearly fitted PDDs of the square fields, the slopes of the reconstructed dose distributions overestimated those of the reference distributions by at most 0.2%/cm. The 2D gamma passing rate with a criterion of 2%/2mm for the concave-shaped photon field was of 61.6%, 66.1%, and 76.4% using one, two, and three plenoptic projections; the respective success rates become 77.1%, 87.5%, and 94.9% using a criterion of 3%/3mm. The 3D correlation coefficient for the corresponding reconstructions was of 0.688, 0.905, and 0.976, respectively. Three-dimensional light distributions emitted from within a plastic scintillator volume were successfully recovered using optical design software to establish a complete tomographic model of a plenoptic camera-based prototype. The tomographic model can equivalently extend to dynamic dose delivery measurements, providing temporal resolution limited by the camera's exposure time. This feasibility study enables a simplified design-to-implementation process for volumetric scintillation dosimetry prototypes toward fully meeting the clinical needs of 3D dose measurements for static and dynamic delivery techniques.

Technical Note: Comprehensive performance tests of the first clinical real-time motion tracking and compensation system using MLC and jaws.

PurposeTo evaluate the performance of the first clinical real‐time motion tracking and compensation system using multileaf collimator (MLC) and jaws during helical tomotherapy delivery.MethodsAppropriate mechanical and dosimetry tests were performed on the first clinical real‐time motion tracking system (Synchrony on Radixact, Accuray Inc) recently installed in our institution. kV radiography dose was measured by CTDIw using a pencil chamber. Changes of beam characteristics with jaw offset and MLC leaf shift were evaluated. Various dosimeters and phantoms including A1SL ion chamber (Standard Imaging), Gafchromic EBT3 films (Ashland), TomoPhantom (Med Cal), ArcCheck (Sun Nuclear), Delta4 (ScandiDos), with fiducial or high contrast inserts, placed on two dynamical motion platforms (CIRS dynamic motion‐CIRS, Hexamotion‐ScandiDos), were used to assess the dosimetric accuracy of the available Synchrony modalities: fiducial tracking with nonrespiratory motion (FNR), fiducial tracking with respiratory modeling (FR), and fiducial free (e.g., lung tumor tracking) with respiratory modeling (FFR). Motion detection accuracy of a tracking target, defined as the difference between the predicted and instructed target positions, was evaluated with the root mean square (RMS). The dose accuracy of motion compensation was evaluated by verifying the dose output constancy and by comparing measured and planned (predicted) three‐dimensional (3D) dose distributions based on gamma analysis.ResultsThe measured CTDIw for a single radiograph with a 120 kVp and 1.6 mAs protocol was 0.084 mGy, implying a low imaging dose of 8.4 mGy for a typical Synchrony motion tracking fraction with 100 radiographs. The dosimetric effect of the jaw swing or MLC leaf shift was minimal on depth dose (<0.5%) and was <2% on both beam profile width and output for typical motions. The motion detection accuracies, that is, RMS, were 0.84, 1.13, and 0.48 mm for FNR, FR, and FFR, respectively, well within the 1.5 mm recommended tolerance. Dose constancy with Synchrony was found to be within 2%. The gamma passing rates of 3D dose measurements for a variety of Synchrony plans were well within the acceptable level.ConclusionsThe motion tracking and compensation using kV radiography, MLC shifting, and jaw swing during helical tomotherapy delivery was tested to be mechanically and dosimetrically accurate for clinical use.

Digital holographic interferometry for measuring the absorbed three-dimensional dose distribution

Ionizing radiations are being widely used in a variety of medical and industrial applications in which the exact determination of the absorbed dose distribution is of crucial importance. Digital holographic interferometry (DHI) is an optical technique that uses lasers to produce fringe patterns which must be reconstructed to measure the physical quantities of interest. The DHI technique is sensitive to noise that makes it difficult to adopt this technique for practically measuring the absorbed dose. In this paper, a new approach to DHI has been developed based on using fringe contouring, polynomial phase fitting and inverse Abel transformation, to reconstruct the three-dimensional dose distribution in noisy conditions. In order to assess the feasibility of this approach in measuring the absorbed dose distributions in noisy conditions, the whole approach is modeled for high energy electrons. It is shown that the three-dimensional dose distribution inside the absorbing medium can be obtained with good accuracy even in the presence of considerable amounts of deliberately added noise to the holograms.

Magnetic resonance image-based tomotherapy planning for prostate cancer.

PurposeTo evaluate and compare the feasibilities of magnetic resonance (MR) image-based planning using synthetic computed tomography (sCT) versus CT (pCT)-based planning in helical tomotherapy for prostate cancer.Materials and MethodsA retrospective evaluation was performed in 16 patients with prostate cancer who had been treated with helical tomotherapy. MR images were acquired using a dedicated therapy sequence; sCT images were generated using magnetic resonance for calculating attenuation (MRCAT). The three-dimensional dose distribution according to sCT was recalculated using a previously optimized plan and was compared with the doses calculated using pCT. ResultsThe mean planning target volume doses calculated by sCT and pCT differed by 0.65% ± 1.11% (p = 0.03). Three-dimensional gamma analysis at a 2%/2 mm dose difference/distance to agreement yielded a pass rate of 0.976 (range, 0.658 to 0.986). ConclusionThe dose distribution results obtained using tomotherapy from MR-only simulations were in good agreement with the dose distribution results from simulation CT, with mean dose differences of less than 1% for target volume and normal organs in patients with prostate cancer.

A mathematical expression for depth-light curves of therapeutic proton beams in a quenching scintillator.

Recently, there has been increasing interest in the development of scintillator-based detectors for the measurement of depth-dose curves of therapeutic proton beams (Beaulieu and Beddar [2016], Phys Med Biol., 61:R305-R343). These detectors allow the measurement of single beam parameters such as the proton range or the reconstruction of the full three-dimensional dose distribution. Thus, scintillation detectors could play an important role in beam quality assurance, online beam monitoring, and proton imaging. However, the light output of the scintillator as a function of dose deposition is subject to quenching effects due to the high-specific energy loss of incident protons, particularly in the Bragg peak. The aim of this work is to develop a model that describes the percent depth-light curve in a quenching scintillator and allow the extraction of information about the beam range and the strength of the quenching. A mathematical expression of a depth-light curve, derived from a combination of Birks' law (Birks [1951], Proc Phys Soc A., 64:874) and Bortfeld's Bragg curve (Bortfeld [1997], Med Phys., 24:2024-2033) that is termed a "quenched Bragg" curve, is presented. The model is validated against simulation and measurement. A fit of the quenched Bragg model to simulated depth-light curves in a polystyrene-based scintillator shows good agreement between the two, with a maximum deviation of 2.5% at the Bragg peak. The differences are larger behind the Bragg peak and in the dose build-up region. In the same simulation, the difference between the reconstructed range and the reference proton range is found to be always smaller than 0.16mm. The comparison with measured data shows that the fitted beam range agrees with the reference range within their respective uncertainties. The quenched Bragg model is, therefore, an accurate tool for the range measurement from quenched depth-dose curves. Moreover, it allows the reconstruction of the beam energy spread, the particle fluence, and the magnitude of the quenching effect from a measured depth-light curve.

Technical Note: Radiotherapy dose characterization of gel dosimetry using shear wave elasticity imaging.

Radiotherapy is an effective treatment for many types of cancer in clinical settings. Gel dosimetry has the potential to record three-dimensional (3D) dose distribution compared to a conventional ion chamber. As the elasticity of the gel is altered after irradiation due to gel polymerization, we aim to measure the dose recorded in gel dosimetry with ultrasonic shear wave elasticity imaging (SWEI), a nondestructive and quantitative elasticity imaging tool. In this study, a cylindrical N-isopropylacrylamide (NIPAM) polymer gel with a diameter of 10cm and a height of 10cm and with cellulose as an ultrasonic scatterer was irradiated by a linear accelerator with the irradiation parameters of 6MV x-ray, dose rate of 100cGy/min and field size of 10 20mm2 . The six gel phantoms were irradiated with the dose of 0, 1, 3, 5, 8, or 10Gy. The gel phantoms were measured with SWEI at 24, 36, and 48h after x-ray irradiation. The two-dimensional (2D) shear wave velocity and Young's modulus maps corresponding to x-ray dose distribution were reconstructed following a time-of-flight reconstruction from a set of time-series displacement maps. The spatial resolution of the reconstructed SWEI image is ~1mm. Our results show that the elastic modulus increases linearly as irradiation dose increases (R2 =0.94 at 24h, R2 =0.98 at 36h, R2 =0.98 at 48h), suggesting that the gel elasticity is highly associated with x-ray irradiation dose at 36h post irradiation, and the dose resolution was 0.66kPa/Gy. From the 3D elastic modulus maps, the dose distribution along the depth and lateral direction can be reflected in the NIPAM gel dosimetry using SWEI as well. In this study, the irradiated NIPAM gel phantom was quantitatively measured with SWEI for the first time to read the dose distribution recorded in the gel dosimetry. The results suggest that the gel elasticity is highly associated with x-ray irradiation dose. In the future, 2D/or 3D dose distribution from intensity modulated radiotherapy (IMRT) or other potential particle radiotherapy will be measured and reconstructed with SWEI and compared with the dose map from a treatment planning system (TPS) in the clinic.

Intraoperative computed tomography imaging for dose calculation in intraoperative electron radiation therapy: Initial clinical observations.

In intraoperative electron radiation therapy (IOERT) the energy of the electron beam is selected under the conventional assumption of water-equivalent tissues at the applicator end. However, the treatment field can deviate from the theoretic flat irradiation surface, thus altering dose profiles. This patient-based study explored the feasibility of acquiring intraoperative computed tomography (CT) studies for calculating three-dimensional dose distributions with two factors not included in the conventional assumption, namely the air gap from the applicator end to the irradiation surface and tissue heterogeneity. In addition, dose distributions under the conventional assumption and from preoperative CT studies (both also updated with intraoperative data) were calculated to explore whether there are other alternatives to intraoperative CT studies that can provide similar dose distributions. The IOERT protocol was modified to incorporate the acquisition of intraoperative CT studies before radiation delivery in six patients. Three studies were not valid to calculate dose distributions due to the presence of metal artefacts. For the remaining three cases, the average gamma pass rates between the doses calculated from intraoperative CT studies and those obtained assuming water-equivalent tissues or from preoperative CT studies were 73.4% and 74.0% respectively. The agreement increased when the air gap was included in the conventional assumption (98.1%) or in the preoperative CT images (98.4%). Therefore, this factor was the one mostly influencing the dose distributions of this study. Our experience has shown that intraoperative CT studies are not recommended when the procedure includes the use of shielding discs or surgical retractors unless metal artefacts are removed. IOERT dose distributions calculated under the conventional assumption or from preoperative CT studies may be inaccurate unless the air gap (which depends on the surface irregularities of the irradiated volume and on the applicator pose) is included in the calculations.

Predictive gamma passing rate for three-dimensional dose verification with finite detector elements via improved dose uncertainty potential accumulation model.

We aim to develop a method to predict the gamma passing rate (GPR) of a three-dimensional (3D) dose distribution measured by the Delta4 detector system using the dose uncertainty potential (DUP) accumulation model. Sixty head-and-neck intensity-modulated radiation therapy (IMRT) treatment plans were created in the XiO treatment planning system. All plans were created using nine step-and-shoot beams of the ONCOR linear accelerator. Verification plans were created and measured by the Delta4 system. The planar DUP (pDUP) manifesting on a field edge was generated from the segmental aperture shape with a Gaussian folding on the beam's-eye view. The DUP at each voxel ( ) was calculated by projecting the pDUP on the Delta4 phantom with its attenuation considered. The learning model (LM), an average GPR as a function of the DUP, was approximated by an exponential function to compensate for the low statistics of the learning data due to a finite number of the detectors. The coefficient was optimized to ensure that the difference between the measured and predicted GPRs ( ) was minimized. The standard deviation (SD) of the was evaluated for the optimized LM. It was confirmed that the coefficient was larger for tighter tolerance. This result corresponds to the expectation that the attenuation of the will be large for tighter tolerance. The and were observed to be proportional for all tolerances investigated. The SD of was 2.3, 4.1, and 6.7% for tolerances of 3%/3mm, 3%/2mm, 2%/2mm, respectively. The DUP-based predicting method of the GPR was extended to 3D by introducing DUP attenuation and an optimized analytical LM to compensate for the low statistics of the learning data due to a finite number of detector elements. The precision of the predicted GPR is expected to be improved by improving the LM and by involving other metrics.

Region-specific three-dimensional dose distribution prediction: a feasibility study on prostate VMAT cases

Purpose: To investigate region-specific models for organ’s three-dimensional dose distribution prediction with neural network.Methods: The dose distribution from different bladder regions for 52 pr...

Fabrication of anthropomorphic phantoms for use in total body irradiations studies

AbstractPurpose:The aim of this study was to produce a low-cost anatomical model of adult male including lower limbs to evaluate the three-dimensional dose distribution for dosimetry measurements, especially in total body irradiation (TBI) and total skin electron therapy (TSET).Materials and methods:Computed tomography (CT) scan images of the atomic energy organisation RANDO phantom and lower limb CT scan images of 20 healthy persons were averaged. Selections of different body tissues substitute materials and phantom validation were performed according to previous studies worked on construction of radiation therapy phantoms.Results:The dosimetry aspect of the selected substitute materials from all considered methods showed that they were in good agreement with real human tissue, especially bone, with a percentage error of 0·5%. The results show that the electron densities obtained from the linear attenuation coefficient (reDLAC) for the tissue equivalent material used in the phantom is a better option for validation.Conclusions:This validated phantom has numerous advantages over the origin type of RANDO phantom. Therefore, using it in TBI and TSET dosimetry is recommendable.

Volumetric and actuarial analysis of brain necrosis in proton therapy using a novel mixture cure model

Background and purposeHigh-dose fractionated radiotherapy is often necessary to achieve long-term tumor control in several types of tumors involving or within close proximity to the brain. There is limited data to guide on optimal constraints to the adjacent nontarget brain. This investigation explored the significance of the three-dimensional (3D) dose distribution of passive scattering proton therapy to the brain with other clinicopathological factors on the development of symptomatic radiation necrosis. Materials and methodsAll patients with head and neck, skull base, or intracranial tumors who underwent proton therapy (minimum prescription dose of 59.4 Gy(RBE)) with collateral moderate to high dose radiation exposure to the nontarget brain were retrospectively reviewed. A mixture cure model with respect to necrosis-free survival was used to derive estimates for the normal tissue complication probability (NTCP) model while adjusting for potential confounding factors. ResultsOf 179 identified patients, 83 patients had intracranial tumors and 96 patients had primary extracranial tumors. The optimal dose measure obtained to describe the occurrence of radiation necrosis was the equivalent uniform dose (EUD) with parameter a = 9. The best-fit parameters of logistic NTCP models revealed D50 = 57.7 Gy for intracranial tumors, D50 = 39.5 Gy for extracranial tumors, and γ50 = 2.5 for both tumor locations. Multivariable analysis revealed EUD and primary tumor location to be the strongest predictors of brain radiation necrosis. ConclusionIn the current clinical volumetric data analyses with multivariable modelling, EUD was identified as an independent and strong predictor for brain radiation necrosis from proton therapy.