Dosimetric validation of SmART-RAD Monte Carlo modelling for x-ray cabinet radiobiology irradiators.

Objective. Accuracy and reproducibility in the measurement of radiation dose and associated reporting are critically important for the validity of basic and preclinical radiobiological studies performed with kilovolt x-ray radiation cabinets. This is essential to enable results of radiobiological studies to be repeated, as well as enable valid comparisons between laboratories. In addition, the commonly used single point dose value hides the 3D dose heterogeneity across the irradiated sample. This is particularly true for preclinical rodent models, and is generally difficult to measure directly. Radiation transport simulations integrated in an easy to use application could help researchers improve quality of dosimetry and reporting.Approach. This paper describes the use and dosimetric validation of a newly-developed Monte Carlo (MC) tool, SmART-RAD, to simulate the x-ray field in a range of standard commercial x-ray cabinet irradiators used for preclinical irradiations. Comparisons are made between simulated and experimentally determined dose distributions for a range of configurations to assess the potential use of this tool in determining dose distributions through samples, based on more readily available air-kerma calibration point measurements.Main results. Simulations gave very good dosimetric agreement with measured depth dose distributions in phantoms containing both water and bone equivalent materials. Good spatial and dosimetric agreement between simulated and measured dose distributions was obtained when using beam-shaping shielding.Significance. The MC simulations provided by SmART-RAD provide a useful tool to go from a limited number of dosimetry measurements to detailed 3D dose distributions through a non-homogeneous irradiated sample. This is particularly important when trying to determine the dose distribution in more complex geometries. The use of such a tool can improve reproducibility and dosimetry reporting in preclinical radiobiological research.

AAPM WGDCAB Report 372: A joint AAPM, ESTRO, ABG, and ABS report on commissioning of model-based dose calculation algorithms in brachytherapy.

The introduction of model-based dose calculation algorithms (MBDCAs) in brachytherapy provides an opportunity for a more accurate dose calculation and opens the possibility for novel, innovative treatment modalities. The joint AAPM, ESTRO, and ABG Task Group 186 (TG-186) report provided guidance to early adopters. However, the commissioning aspect of these algorithms was described only in general terms with no quantitative goals. This report, from the Working Group on Model-Based Dose Calculation Algorithms in Brachytherapy, introduced a field-tested approach to MBDCA commissioning. It is based on a set of well-characterized test cases for which reference Monte Carlo (MC) and vendor-specific MBDCA dose distributions are available in a Digital Imaging and Communications in Medicine-Radiotherapy (DICOM-RT) format to the clinical users. The key elements of the TG-186 commissioning workflow are now described in detail, and quantitative goals are provided. This approach leverages the well-known Brachytherapy Source Registry jointly managed by the AAPM and the Imaging and Radiation Oncology Core (IROC) Houston Quality Assurance Center (with associated links at ESTRO) to provide open access to test cases as well as step-by-step user guides. While the current report is limited to the two most widely commercially available MBDCAs and only for 192 Ir-based afterloading brachytherapy at this time, this report establishes a general framework that can easily be extended to other brachytherapy MBDCAs and brachytherapy sources. The AAPM, ESTRO, ABG, and ABS recommend that clinical medical physicists implement the workflow presented in this report to validate both the basic and the advanced dose calculation features of their commercial MBDCAs. Recommendations are also given to vendors to integrate advanced analysis tools into their brachytherapy treatment planning system to facilitate extensive dose comparisons. The use of the test cases for research and educational purposes is further encouraged.

A novel multichannel deep learning model for fast denoising of Monte Carlo dose calculations: preclinical applications.

Objective.In preclinical radiotherapy with kilovolt (kV) x-ray beams, accurate treatment planning is needed to improve the translation potential to clinical trials. Monte Carlo based radiation transport simulations are the gold standard to calculate the absorbed dose distribution in external beam radiotherapy. However, these simulations are notorious for their long computation time, causing a bottleneck in the workflow. Previous studies have used deep learning models to speed up these simulations for clinical megavolt (MV) beams. For kV beams, dose distributions are more affected by tissue type than for MV beams, leading to steep dose gradients. This study aims to speed up preclinical kV dose simulations by proposing a novel deep learning pipeline.Approach.A deep learning model is proposed that denoises low precision (∼106simulated particles) dose distributions to produce high precision (109simulated particles) dose distributions. To effectively denoise the steep dose gradients in preclinical kV dose distributions, the model uses the novel approach to use the low precision Monte Carlo dose calculation as well as the Monte Carlo uncertainty (MCU) map and the mass density map as additional input channels. The model was trained on a large synthetic dataset and tested on a real dataset with a different data distribution. To keep model inference time to a minimum, a novel method for inference optimization was developed as well.Main results.The proposed model provides dose distributions which achieve a median gamma pass rate (3%/0.3 mm) of 98% with a lower bound of 95% when compared to the high precision Monte Carlo dose distributions from the test set, which represents a different dataset distribution than the training set. Using the proposed model together with the novel inference optimization method, the total computation time was reduced from approximately 45 min to less than six seconds on average.Significance.This study presents the first model that can denoise preclinical kV instead of clinical MV Monte Carlo dose distributions. This was achieved by using the MCU and mass density maps as additional model inputs. Additionally, this study shows that training such a model on a synthetic dataset is not only a viable option, but even increases the generalization of the model compared to training on real data due to the sheer size and variety of the synthetic dataset. The application of this model will enable speeding up treatment plan optimization in the preclinical workflow.

A deep learning and Monte Carlo based framework for bioluminescence imaging center of mass-guided glioblastoma targeting.

Objective.Bioluminescence imaging (BLI) is a valuable tool for non-invasive monitoring of glioblastoma multiforme (GBM) tumor-bearing small animals without incurring x-ray radiation burden. However, the use of this imaging modality is limited due to photon scattering and lack of spatial information. Attempts at reconstructing bioluminescence tomography (BLT) using mathematical models of light propagation show limited progress.Approach.This paper employed a different approach by using a deep convolutional neural network (CNN) to predict the tumor's center of mass (CoM). Transfer-learning with a sizeable artificial database is employed to facilitate the training process for, the much smaller, target database including Monte Carlo (MC) simulations of real orthotopic glioblastoma models. Predicted CoM was then used to estimate a BLI-based planning target volume (bPTV), by using the CoM as the center of a sphere, encompassing the tumor. The volume of the encompassing target sphere was estimated based on the total number of photons reaching the skin surface.Main results.Results show sub-millimeter accuracy for CoM prediction with a median error of 0.59 mm. The proposed method also provides promising performance for BLI-based tumor targeting with on average 94% of the tumor inside the bPTV while keeping the average healthy tissue coverage below 10%.Significance.This work introduced a framework for developing and using a CNN for targeted radiation studies for GBM based on BLI. The framework will enable biologists to use BLI as their main image-guidance tool to target GBM tumors in rat models, avoiding delivery of high x-ray imaging dose to the animals.

Validation of the collapsed cone algorithm for HDR liver brachytherapy against Monte Carlo simulations.

PURPOSE: To validate the collapsed cone (CC) algorithm against Monte Carlo (MC) simulations for model-based dose calculations in high-dose-rate (HDR) liver brachytherapy. METHODS AND MATERIALS: Doses for liver brachytherapy treatment plans of 10 cases were retrospectively recalculated with a model-based approach using Monte Carlo n-Particle Code (MCNP) 6 (Dm,m-MC) and Oncentra Brachy ACE (Dm,m-ACE). Tissue segmentation consisted of assigning uniform compositions and mass densities to predefined Hounsfield Unit (HU) thresholds. Resulting doses were compared according to dose volume histogram parameters typical for clinical routine. These included the percentage liver volume receiving 5 Gy (V5Gy) or 10 Gy (V10Gy), the maximum dose to one cubic centimeter (D1cc) of organs at risk, the clinical target volume (CTV) fractions receiving 150% (V150), 100% (V100), 95% (V95) and 90% (V90) of the prescribed dose and the absolute doses to 95% (D95) and 90% (D90) of the CTV volumes. RESULTS: Doses from Oncentra Brachy ACE agreed well with MC simulations. Differences were seen far from the source, in low-density regions and bone structures. Median percentage deviations were 1.1% for the liver V5Gy and 0.4% for the liver V10Gy, with deviations of largest magnitude amounting to 2.2% and 1.0%, respectively. Organs at risk had median deviations ranging from 0.3% to 1.5% for D1cc, with outliers ranging up to 4.6%. CTV volume parameter deviations ranged between -1.5% and 0.5%, dose parameter deviations ranged mostly between -2% and 1%, with two outliers at -4.0% and -3.4% for a small CTV.

External validation of a hidden Markov model for gamma-based classification of anatomical changes in lung cancer patients using EPID dosimetry.

PURPOSE: To externally validate a hidden Markov model (HMM) for classifying gamma analysis results of in vivo electronic portal imaging device (EPID) measurements into different categories of anatomical change for lung cancer patients. Additionally, the relationship between HMM classification and deviations in dose-volume histogram (DVH) metrics was evaluated. METHODS: The HMM was developed at CHU de Québec (CHUQ), and trained on features extracted from gamma analysis maps of in vivo EPID measurements from 483 fractions (24 patients, treated with three-dimensional 3D-CRT or intensity modulated radiotherapy), using the EPID measurement of the first treatment fraction as reference. The model inputs were the average gamma value, standard deviation, and average value of the highest 1% of gamma values, all averaged over all beams in a fraction. The HMM classified each fraction into one of three categories: no anatomical change (Category 1), some anatomical change (no clinical action needed, Category 2) and severe anatomical change (clinical action needed, Category 3). The external validation dataset consisted of EPID measurements from 263 fractions of 30 patients treated at Maastro with volumetric modulated arc therapy (VMAT) or hybrid plans (containing both static beams and VMAT arcs). Gamma analysis features were extracted in the same way as in the CHUQ dataset, by using the EPID measurement of the first fraction as reference (γQ), and additionally by using an EPID dose prediction as reference (γM). For Maastro patients, cone beam computed tomography (CBCT) scans and image-guided radiotherapy (IGRT) classification of these images were available for each fraction. Contours were propagated from the planning CT to the CBCTs, and the dose was recalculated using a Monte Carlo dose engine. Dose-volume histogram metrics for targets and organs-at-risk (OARs: lungs, heart, mediastinum, spinal cord, brachial plexus) were extracted for each fraction, and compared to the planned dose. HMM classification of the external validation set was compared to threshold classification based on the average gamma value alone (a surrogate for clinical classification at CHUQ), IGRT classification as performed at Maastro, and differences in DVH metrics extracted from 3D dose recalculations on the CBCTs. RESULTS: The HMM achieved 65.4%/65.0% accuracy for γQ and γM, respectively, compared to average gamma threshold classification. When comparing HMM classification with IGRT classification, the overall accuracy was 29.7% for γQ and 23.2% for γM. Hence, HMM classification and IGRT classification of anatomical changes did not correspond. However, there is a trend towards higher deviations in DVH metrics with classification into higher categories by the HMM for large OARs (lungs, heart, mediastinum), but not for the targets and small OARs (spinal cord, brachial plexus). CONCLUSION: The external validation shows that transferring the HMM for anatomical change classification to a different center is challenging, but can still be valuable. The HMM trained at CHUQ cannot be used directly to classify anatomical changes in the Maastro data. However, it may be possible to use the model in a different capacity, as an indicator for changes in the 3D dose based on two-dimensional EPID measurements.

Advanced design, simulation, and dosimetry of a novel rectal applicator for contact brachytherapy with a conventional HDR 192Ir source.

PURPOSE: Dose escalation yields higher complete response to rectal tumors, which may enable the omission of surgery. Dose escalation using 50 kVp contact x-ray brachytherapy (CXB) allow the treatment of a selective volume, resulting in low toxicity and organs-at-risk preservation. However, the use of CXB devices is limited because of its high cost and lack of treatment planning tools. Hence, the MAASTRO applicator (for HDR 192Ir sources) was developed and characterized by measurements and Monte Carlo simulations to be a cost-effective alternative to CXB devices. METHODS AND MATERIALS: A cylindrical applicator with lateral shielding was designed to be used with a rectoscope using its tip as treatment surface. Both the applicator and the rectoscope have a slanted edge to potentially allow easier placement against tumors. The applicator design was achieved by Monte Carlo modeling and validated experimentally with film dosimetry, using the Papillon 50 (P50) device as reference. RESULTS: The applicator delivers CXB doses in less than 9 min using a 20375 U source for a treatment area of approximately 20 × 20 mm2 at 2 mm depth. Normalized at 2 mm, the dose falloff for depths of 0 mm, 5 mm, and 10 mm are 130%, 70%, and 43% for the P50 and 140%, 67%, and 38% for the MAASTRO applicator, respectively. CONCLUSIONS: The MAASTRO applicator was designed to use HDR 192Ir sources to deliver a dose distribution similar to those of CXB devices. The applicator may provide a cost-effective solution for endoluminal boosting with clinical treatment planning system integration.

A Monte Carlo based scatter removal method for non-isocentric cone-beam CT acquisitions using a deep convolutional autoencoder.

The primary cone-beam computed tomography (CBCT) imaging beam scatters inside the patient and produces a contaminating photon fluence that is registered by the detector. Scattered photons cause artifacts in the image reconstruction, and are partially responsible for the inferior image quality compared to diagnostic fan-beam CT. In this work, a deep convolutional autoencoder (DCAE) and projection-based scatter removal algorithm were constructed for the ImagingRingTM system on rails (IRr), which allows for non-isocentric acquisitions around virtual rotation centers with its independently rotatable source and detector arms. A Monte Carlo model was developed to simulate (i) a non-isocentric training dataset of ≈1200 projection pairs (primary + scatter) from 27 digital head-and-neck cancer patients around five different virtual rotation centers (DCAENONISO), and (ii) an isocentric dataset existing of ≈1200 projection pairs around the physical rotation center (DCAEISO). The scatter removal performance of both DCAE networks was investigated in two digital anthropomorphic phantom simulations and due to superior performance only the DCAENONISO was applied on eight real patient acquisitions. Measures for the quantitative error, the signal-to-noise ratio, and the similarity were evaluated for two simulated digital head-and-neck patients, and the contrast-to-noise ratio (CNR) was investigated between muscle and adipose tissue in the real patient image reconstructions. Image quality metrics were compared between the uncorrected data, the currently implemented heuristic scatter correction data, and the DCAE corrected image reconstruction. The DCAENONISO corrected image reconstructions of two digital patient simulations showed superior image quality metrics compared to the uncorrected and corrected image reconstructions using a heuristic scatter removal. The proposed DCAENONISO scatter correction in this study was successfully demonstrated in real non-isocentric patient CBCT acquisitions and achieved statistically significant higher CNRs compared to the uncorrected or the heuristic corrected image data. This paper presents for the first time a projection-based scatter removal algorithm for isocentric and non-isocentric CBCT imaging using a deep convolutional autoencoder trained on Monte Carlo composed datasets. The algorithm was successfully applied to real patient data.

The dosimetric impact of replacing the TG-43 algorithm by model based dose calculation for liver brachytherapy.

PURPOSE: To compare treatment plans for interstitial high dose rate (HDR) liver brachytherapy with 192Ir calculated according to current-standard TG-43U1 protocol with model-based dose calculation following TG-186 protocol. METHODS: We retrospectively evaluated dose volume histogram (DVH) parameters for liver, organs at risk (OARs) and clinical target volumes (CTVs) of 20 patient cases diagnosed with hepatocellular carcinoma (HCC) or metastatic colorectal cancer (mCRC). Dose calculations on a homogeneous water geometry (TG-43U1 surrogate) and on a computed tomography (CT) based geometry (TG-186) were performed using Monte Carlo (MC) simulations. The CTs were segmented based on a combination of assigning TG-186 recommended tissues to fixed Hounsfield Unit (HU) ranges and using organ contours delineated by physicians. For the liver, V5Gy and V10Gy were analysed, and for OARs the dose to 1 cubic centimeter (D1cc). Target coverage was assessed by calculating V150, V100, V95 and V90 as well as D95 and D90. For every DVH parameter, median, minimum and maximum values of the deviations of TG-186 from TG-43U1 were analysed. RESULTS: TG-186-calculated dose was found to be on average lower than dose calculated with TG-43U1. The deviation of highest magnitude for liver parameters was -6.2% of the total liver volume. For OARs, the deviations were all smaller than or equal to -0.5 Gy. Target coverage deviations were as high as -1.5% of the total CTV volume and -3.5% of the prescribed dose. CONCLUSIONS: In this study we found that TG-43U1 overestimates dose to liver tissue compared to TG-186. This finding may be of clinical importance for cases where dose to the whole liver is the limiting factor.

Modelling of the focal spot intensity distribution and the off-focal spot radiation in kilovoltage x-ray tubes for imaging.

X-ray tubes for medical applications typically generate x-rays by accelerating electrons, emitted from a cathode, with an interelectrode electric field, towards an anode target. X-rays are not emitted from one point, but from an irregularly shaped area on the anode, the focal spot. Focal spot intensity distributions and off-focal radiation negatively affect the imaging spatial resolution and broadens the beam penumbra. In this study, a Monte Carlo simulation model of an x-ray tube was developed to evaluate the spectral and spatial characteristics of off-focal radiation for multiple photon energies. Slit camera measurements were used to determine the horizontal and vertical intensity profiles of the small and the large focal spot of a diagnostic x-ray tube. First, electron beamlet weighting factors were obtained via an iterative optimization method to represent both focal spot sizes. These weighting factors were then used to extract off-focal spot radiation characteristics for the small and large focal spot sizes at 80, 100, and 120 kV. Finally, 120 kV simulations of a steel sphere (d = 4 mm) were performed to investigate image blurring with a point source, the small focal spot, and the large focal spot. The magnitude of off-focal radiation strongly depends on the anode size and the electric field coverage, and only minimally on the tube potential and the primary focal spot size. In conclusion, an x-ray tube Monte Carlo simulation model was developed to simulate focal spot intensity distributions and to evaluate off-focal radiation characteristics at several energies. This model can be further employed to investigate focal spot correction methods and to improve cone-beam CT image quality.

Dose to water versus dose to medium from cavity theory applied to small animal irradiation with kilovolt x-rays.

Dose reporting is a matter of concern in the preclinical field as the different dose descriptors dose-to-water-in-medium [Formula: see text] and dose-to-medium-in-medium [Formula: see text] coexist. For kV photons differences between both quantities are expected to be amplified due to photon energy absorption coefficients differences for different media, and could represent a limiting factor for accurate translation of pre-clinical research into clinical trials. The main goal of this study was to analyse the relationship between [Formula: see text] and [Formula: see text] for kV irradiation of small animals, using different flavours of the intermediate cavity theory (ICT). Irradiations of mathematical phantoms and a mouse CT scan, both with different voxel sizes and materials, were investigated. A modified version of the Monte Carlo code DOSXYZnrc was used to derive [Formula: see text] and convert to [Formula: see text] using ICT. Local photon spectra were generated in different regions of the mouse. Depending on energy and cavity size, which we equate to the voxel size, [Formula: see text] ranged from 0.68 to 4.37 times [Formula: see text]. Higher kV energy combined with very small cavity sizes yielded decreased [Formula: see text] in comparison to [Formula: see text]; this behaviour was reversed for larger cavities combined with lower kV energies. Hence, the impact of the cavity dimensions on estimated [Formula: see text] is significant on pre-clinical kV beams. [Formula: see text] and [Formula: see text] in the ex vivo male mouse were found to differ by -29% to 286%. Caution is advised when using the ICT due to a lack of consensus on weighting factor (d-parameter) deriving methods; for the same irradiation conditions, different d-values affected [Formula: see text] up to 20%. Pre-clinically, such divergence between dose descriptors could enable biological damage. The abiding debate over which quantity to favour is foreseen to linger while it is unclear which quantity correlates better with the biological effects of ionizing irradiation: preclinical radiotherapy might represent an ideal platform for measurement-based studies to settle this fundamental question. Finally, dose distribution comparisons require caution and should use the same reporting quantity.

Dose painting by dynamic irradiation delivery on an image-guided small animal radiotherapy platform.

OBJECTIVE:: Using synchronized three-dimensional stage translation and multiangle radiation delivery to improve conformality and homogeneity of radiation delivery to complexly shaped target volumes for precision preclinical radiotherapy. METHODS:: A CT image of a mouse was used to design irradiation plans to target the spinal cord and an orthotopic lung tumour. A dose painting method is proposed that combines heterogeneous two-dimensional area irradiations from multiple beam directions. For each beam direction, a two-dimensional area was defined based on the projection of the target volume. Each area was divided into many single beam Monte Carlo simulations, based on radiochromic film characterization of a 2.4 mm beam of a commercial precision image-guided preclinical irradiation platform. Beam-on time optimization including all simulated beams from multiple beam directions was used to achieve clinically relevant irradiation objects. Dose painting irradiation plans were compared to irradiation plans using a fixed aperture and rotatable variable aperture collimator. RESULTS:: Irradiation plans for the proposed dose painting approach achieved good target coverage, similar dose to avoidance structures in comparison with irradiation using a rotatable variable aperture collimator, and considerably less dose to avoidance volumes in comparison with irradiation using a non-rotatable fixed aperture collimator. Required calculations and beam-on times were considerably longer for the dose painting method. CONCLUSION:: It was shown that the proposed dose painting strategy is a valuable extension to increase the versatility of current generation precision preclinical radiotherapy platforms. More conformal and homogeneous dose delivery may be achieved at the cost of increased radiation planning and delivery duration. ADVANCES IN KNOWLEDGE:: More advanced radiation planning for image-guided preclinical radiotherapy platforms can improve target dose conformality and homogeneity with the use of optimized dynamic irradiations with synchronized couch translation. The versatility of these platforms can be increased without hardware modifications.

On the determination of planning target margins due to motion for mice lung tumours using a four-dimensional MOBY phantom.

OBJECTIVE:: This work aims to analyse the effect of respiratory motion on optimal irradiation margins for murine lung tumour models. METHODS:: Four-dimensional mathematical phantoms with different lung tumour locations affected by respiratory motion were created. Two extreme breathing curves were adopted and divided into time-points. Each time-point was loaded in a treatment planning system and Monte Carlo (MC) dose calculations were performed for a 360° arc plan. A time-resolved dose was derived, considering the gantry rotation and the breathing motion. Radiotherapy metrics were derived to assess the final treatment plans. An interpolation function was investigated to reduce calculation cost. RESULTS:: The effect of respiratory motion on the treatment plan quality is strongly dependent on the breathing pattern and the tumour position. Tumours located closer to the diaphragm required a compromise between tumour conformity and healthy tissue damage. A recipe, which considers collimator size, was proposed to derive tumour margins and spare the organs at risk (OARs) by respecting constraints on user-defined metrics. CONCLUSION:: It is recommended to add a target margin, especially on sites where movement is substantial. A simple recipe to derive tumour margins was developed. ADVANCES IN KNOWLEDGE:: This work is a first step towards a standard planning target volume concept in pre-clinical radiotherapy.

Exploring the feasibility of a clinical proton beam with an adaptive aperture for pre-clinical research.

OBJECTIVE:: To investigate whether the Mevion S250i with HYPERSCAN clinical proton system could be used for pre-clinical research with millimetric beams. METHODS:: The nozzle of the proton beam line, consisting of an energy modulation system (EMS) and an adaptive aperture (AA), was modelled with the TOPAS Monte Carlo Simulation Toolkit. With the EMS, the 230 MeV beam nominal range can be decreased in multiples of 2.1 mm. Monte Carlo dose calculations were performed in a mouse lung tumour CT image. The AA allows fields as small as 5 × 1 mm2 to be used for irradiation. The best plans to give 2 Gy to the tumour were derived from a set of discrete energies allowed by the EMS, different field sizes and beam directions. The final proton plans were compared to a precision photon irradiation plan. Treatment times were also assessed. RESULTS:: Seven different proton beam plans were investigated, with a good coverage to the tumour (D95 > 1.95 Gy, D5 < 2.3 Gy) and with potentially less damage to the organs at risk than the photon plan. For very small fields and low energies, the number of protons arriving to the target drops to 1-3%, nevertheless the treatment times would be below 5 s. CONCLUSION:: The proton plans made in this study, collimated by an AA, could be used for animal irradiation. ADVANCES IN KNOWLEDGE:: This is one of the first study to demonstrate the feasibility of pre-clinical research with a clinical proton beam with an adaptive aperture used to create small fields.

A novel rectal applicator for contact radiotherapy with HDR 192Ir sources.

PURPOSE: Dose escalation to rectal tumors leads to higher complete response rates and may thereby enable omission of surgery. Important advantages of endoluminal boosting techniques include the possibility to apply a more selective/localized boost than using external beam radiotherapy. A novel brachytherapy (BT) rectal applicator with lateral shielding was designed to be used with a rectoscope for eye-guided positioning to deliver a dose distribution similar to the one of contact x-ray radiotherapy devices, using commonly available high-dose-rate 192Ir BT sources. METHODS AND MATERIALS: A cylindrical multichannel BT applicator with lateral shielding was designed by Monte Carlo modeling, validated experimentally with film dosimetry and compared with results found in the literature for the Papillon 50 (P50) contact x-ray radiotherapy device regarding rectoscope dimensions, radiation beam shape, dose fall-off, and treatment time. RESULTS: The multichannel applicator designed is able to deliver 30 Gy under 13 min with a 20350 U (5 Ci) source. The use of multiple channels and lateral shielding provide a uniform circular treatment surface with 22 mm in diameter. The resulting dose fall-off is slightly steeper (maximum difference of 5%) than the one generated by the P50 device with the 22 mm applicator. CONCLUSIONS: A novel multichannel rectal applicator for contact radiotherapy with high-dose-rate 192Ir sources that can be integrated with commercially available treatment planning systems was designed to produce a dose distribution similar to the one obtained by the P50 device.

Monte Carlo proton dose calculations using a radiotherapy specific dual-energy CT scanner for tissue segmentation and range assessment.

Proton beam ranges derived from dual-energy computed tomography (DECT) images from a dual-spiral radiotherapy (RT)-specific CT scanner were assessed using Monte Carlo (MC) dose calculations. Images from a dual-source and a twin-beam DECT scanner were also used to establish a comparison to the RT-specific scanner. Proton ranges extracted from conventional single-energy CT (SECT) were additionally performed to benchmark against literature values. Using two phantoms, a DECT methodology was tested as input for Geant4 MC proton dose calculations. Proton ranges were calculated for different mono-energetic proton beams irradiating both phantoms; the results were compared to the ground truth based on the phantom compositions. The same methodology was applied in a head-and-neck cancer patient using both SECT and dual-spiral DECT scans from the RT-specific scanner. A pencil-beam-scanning plan was designed, which was subsequently optimized by MC dose calculations, and differences in proton range for the different image-based simulations were assessed. For phantoms, the DECT method yielded overall better material segmentation with >86% of the voxel correctly assigned for the dual-spiral and dual-source scanners, but only 64% for a twin-beam scanner. For the calibration phantom, the dual-spiral scanner yielded range errors below 1.2 mm (0.6% of range), like the errors yielded by the dual-source scanner (<1.1 mm, <0.5%). With the validation phantom, the dual-spiral scanner yielded errors below 0.8 mm (0.9%), whereas SECT yielded errors up to 1.6 mm (2%). For the patient case, where the absolute truth was missing, proton range differences between DECT and SECT were on average in -1.2 ± 1.2 mm (-0.5% ± 0.5%). MC dose calculations were successfully performed on DECT images, where the dual-spiral scanner resulted in media segmentation and range accuracy as good as the dual-source CT. In the patient, the various methods showed relevant range differences.

The impact of dual energy CT imaging on dose calculations for pre-clinical studies.

BACKGROUND: To investigate the feasibility of using dual-energy CT (DECT) for tissue segmentation and kilovolt (kV) dose calculations in pre-clinical studies and assess potential dose calculation accuracy gain. METHODS: Two phantoms and an ex-vivo mouse were scanned in a small animal irradiator with two distinct energies. Tissue segmentation was performed with the single-energy CT (SECT) and DECT methods. A number of different material maps was used. Dose calculations were performed to verify the impact of segmentations on the dose accuracy. RESULTS: DECT showed better overall results in comparison to SECT. Higher number of DECT segmentation media resulted in smaller dose differences in comparison to the reference. Increasing the number of materials in the SECT method yielded more instability. Both modalities showed a limit to which adding more materials with similar characteristics ceased providing better segmentation results, and resulted in more noise in the material maps and the dose distributions. The effect was aggravated with a decrease in beam energy. For the ex-vivo specimen, the choice of only one high dense bone for the SECT method resulted in large volumes of tissue receiving high doses. For the DECT method, the choice of more than one kind of bone resulted in lower dose values for the different tissues occupying the same volume. For the organs at risk surrounded by bone, the doses were lower when using the SECT method in comparison to DECT, due to the high absorption of the bone. SECT material segmentation may lead to an underestimation of the dose to OAR in the proximity of bone. CONCLUSIONS: The DECT method enabled the selection of a higher number of materials thereby increasing the accuracy in dose calculations. In phantom studies, SECT performed best with three materials and DECT with seven for the phantom case. For irradiations in preclinical studies with kV photon energies, the use of DECT segmentation combined with the choice of a low-density bone is recommended.

What is the impact of innovation on output in healthcare with a special focus on treatment innovations in radiotherapy? A literature review.

OBJECTIVE: To analyse how often innovations in healthcare are evaluated regarding output, especially in radiotherapy. Output was defined as either survival, toxicity, safety, service, efficiency or cost-effectiveness. METHODS: A systematic literature review was conducted, using three search strategies: (1) innovations in general healthcare; (2) radiotherapy-specific innovations, i.e. organizational innovations and general implementation of innovations; (3) innovations per tumour group/radiotherapy technique. Scientific levels were classified according to the system used in European Society for Medical Oncology guidelines. Finally, we calculated the percentage of implemented innovations in Dutch radiotherapy centres for which we found evidence regarding output in the literature review. RESULTS: Only 94/1072 unique articles matched the inclusion criteria. Significant results on patient outcome, service or safety were reported in 65% of papers, which rose to 76% if confined to radiotherapy reviews. A significant technological improvement was identified in 26%, cost-effectiveness in 10% and costs/efficiency in 36% of the papers. The scientific level of organizational innovations was lower than that of clinical papers. Dutch radiotherapy treatment innovations were adequately evaluated on outcome data before implementation in clinical routine in a minimum of 64-92% of cases. CONCLUSION: Only few studies report on output when considering innovations in general, but radiotherapy reviews give a reasonably good insight into innovation output effects, with a higher level of evidence. In Dutch radiotherapy centres only small improvements are possible regarding evaluation of treatment innovations before implementation. Advances in knowledge: This study is the first of its kind measuring how innovations are evaluated in scientific literature, before implementation in clinical practice.

A generic TG-186 shielded applicator for commissioning model-based dose calculation algorithms for high-dose-rate 192 Ir brachytherapy.

PURPOSE: A joint working group was created by the American Association of Physicists in Medicine (AAPM), the European Society for Radiotherapy and Oncology (ESTRO), and the Australasian Brachytherapy Group (ABG) with the charge, among others, to develop a set of well-defined test case plans and perform calculations and comparisons with model-based dose calculation algorithms (MBDCAs). Its main goal is to facilitate a smooth transition from the AAPM Task Group No. 43 (TG-43) dose calculation formalism, widely being used in clinical practice for brachytherapy, to the one proposed by Task Group No. 186 (TG-186) for MBDCAs. To do so, in this work a hypothetical, generic high-dose rate (HDR) 192 Ir shielded applicator has been designed and benchmarked. METHODS: A generic HDR 192 Ir shielded applicator was designed based on three commercially available gynecological applicators as well as a virtual cubic water phantom that can be imported into any DICOM-RT compatible treatment planning system (TPS). The absorbed dose distribution around the applicator with the TG-186 192 Ir source located at one dwell position at its center was computed using two commercial TPSs incorporating MBDCAs (Oncentra® Brachy with Advanced Collapsed-cone Engine, ACE™, and BrachyVision ACUROS™) and state-of-the-art Monte Carlo (MC) codes, including ALGEBRA, BrachyDose, egs_brachy, Geant4, MCNP6, and Penelope2008. TPS-based volumetric dose distributions for the previously reported "source centered in water" and "source displaced" test cases, and the new "source centered in applicator" test case, were analyzed here using the MCNP6 dose distribution as a reference. Volumetric dose comparisons of TPS results against results for the other MC codes were also performed. Distributions of local and global dose difference ratios are reported. RESULTS: The local dose differences among MC codes are comparable to the statistical uncertainties of the reference datasets for the "source centered in water" and "source displaced" test cases and for the clinically relevant part of the unshielded volume in the "source centered in applicator" case. Larger local differences appear in the shielded volume or at large distances. Considering clinically relevant regions, global dose differences are smaller than the local ones. The most disadvantageous case for the MBDCAs is the one including the shielded applicator. In this case, ACUROS agrees with MC within [-4.2%, +4.2%] for the majority of voxels (95%) while presenting dose differences within [-0.12%, +0.12%] of the dose at a clinically relevant reference point. For ACE, 95% of the total volume presents differences with respect to MC in the range [-1.7%, +0.4%] of the dose at the reference point. CONCLUSIONS: The combination of the generic source and generic shielded applicator, together with the previously developed test cases and reference datasets (available in the Brachytherapy Source Registry), lay a solid foundation in supporting uniform commissioning procedures and direct comparisons among treatment planning systems for HDR 192 Ir brachytherapy.

Application of single- and dual-energy CT brain tissue segmentation to PET monitoring of proton therapy.

The purpose of this work was to evaluate the ability of single and dual energy computed tomography (SECT, DECT) to estimate tissue composition and density for usage in Monte Carlo (MC) simulations of irradiation induced ß + activity distributions. This was done to assess the impact on positron emission tomography (PET) range verification in proton therapy. A DECT-based brain tissue segmentation method was developed for white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). The elemental composition of reference tissues was assigned to closest CT numbers in DECT space (DECTdist). The method was also applied to SECT data (SECTdist). In a validation experiment, the proton irradiation induced PET activity of three brain equivalent solutions (BES) was compared to simulations based on different tissue segmentations. Five patients scanned with a dual source DECT scanner were analyzed to compare the different segmentation methods. A single magnetic resonance (MR) scan was used for comparison with an established segmentation toolkit. Additionally, one patient with SECT and post-treatment PET scans was investigated. For BES, DECTdist and SECTdist reduced differences to the reference simulation by up to 62% when compared to the conventional stoichiometric segmentation (SECTSchneider). In comparison to MR brain segmentation, Dice similarity coefficients for WM, GM and CSF were 0.61, 0.67 and 0.66 for DECTdist and 0.54, 0.41 and 0.66 for SECTdist. MC simulations of PET treatment verification in patients showed important differences between DECTdist/SECTdist and SECTSchneider for patients with large CSF areas within the treatment field but not in WM and GM. Differences could be misinterpreted as PET derived range shifts of up to 4 mm. DECTdist and SECTdist yielded comparable activity distributions, and comparison of SECTdist to a measured patient PET scan showed improved agreement when compared to SECTSchneider. The agreement between predicted and measured PET activity distributions was improved by employing a brain specific segmentation applicable to both DECT and SECT data.