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Register a new userTesting Monte Carlo absolute dosimetry formalisms for a small field `D-shaped collimator used in retinoblastoma external beam radiotherapy
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Purpose: To investigate the validity of two Monte Carlo simulation absolute dosimetry approaches in the case of a small field dedicated `D-shaped collimator used for the retinoblastoma treatment with external photon beam radiotherapy. Methods: The Monte Carlo code {sc penelope} is used to simulate the linac, the dedicated collimator and a water phantom. The absolute doses (in Gy per monitor unit) for the field sizes considered are obtained within the approach of Popescu {it et al.} in which the tallied backscattered dose in the monitor chamber is accounted for. The results are compared to experimental data, to those found with a simpler Monte Carlo approximation for the calculation of absolute doses and to those provided by the analytical anisotropic algorithm. Our analysis allows for the study of the simulation tracking parameters. Two sets of parameters have been considered for the simulation of the particle transport in the linac target. Results: The change in the tracking parameters produced non-negligible differences, of about 10% or larger, in the doses estimated in reference conditions. The Monte Carlo results for the absolute doses differ from the experimental ones by 2.6% and 1.7% for the two parameter sets for the collimator geometries analyzed. For the studied fields, the simpler approach produces absolute doses that are statistically compatible with those obtained with the approach of Popescu {it et al.} The analytical anisotropic algorithm underestimates the experimental absolute doses with discrepancies larger than those found for Monte Carlo results. Conclusions: The approach studied can be considered for absolute dosimetry in the case of small, `D-shaped and off-axis radiation fields. However, a detailed description of the radiation transport in the linac target is mandatory for an accurate absolute dosimetry.
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Purpose: Retinoblastoma (RB) is the most common eye tumor in childhood and can be treated external radiotherapy. The purpose of this work is to evaluate the adequacy of Monte Carlo simulations and the accuracy of a commercial treatment planning system by means of experimental measurements. Dose measurements in water were performed using a dedicated collimator. Methods: A 6MV Varian Clinac 2100 C/D and a dedicated collimator are used for RB treatment. The collimator conforms a D-shaped off-axis field whose irradiated area can be either 5.2 or 3.1cm$^2$. Depth dose distributions and lateral profiles were measured and compared with Monte Carlo simulations run with PENELOPE and with calculations performed with the analytical anisotropic algorithm (AAA) using the gamma test. Results: PENELOPE simulations agree well with the experimental data with discrepancies in the dose profiles less than 3mm of distance-to-agreement and 3% of dose. Discrepancies between the results of AAA and the experimental data reach 3mm and 6%. The agreement in the penumbra region between AAA and the experiment is noticeably worse than that between the latter and PENELOPE. The percentage of voxels passing the gamma test when comparing PENELOPE (AAA) and the experiment is on average 99% (93%) assuming a 3mm distance-to-agreement and a discrepancy of 3% of dose. Conclusions: Although the discrepancies between AAA and experimental results are noticeable, it is possible to consider this algorithm for routine treatment planning of RB patients, provided the limitations of the algorithm are known and taken into account by the medical physicist. Monte Carlo simulation is essential for knowing these limitations. Monte Carlo simulation is required for optimizing the treatment technique and the dedicated collimator.
Monte Carlo (MC) methods provide the most accurate to-date dose calculations in heterogeneous media and complex geometries, and this spawns increasing interest in incorporating MC calculations into treatment planning quality assurance process. This involves MC dose calculations for clinically produced treatment plans. To perform these calculations, a number of treatment plan parameters specifying radiation beam and patient geometries need to be transferred to MC codes, such as BEAMnrc and DOSXYZnrc. Extracting these parameters from DICOM files is not a trivial task, one that has previously been performed mostly using Matlab-based software. This paper describes the DICOM tags that contain information required for MC modeling of conformal and IMRT plans, and reports the development of an in-house DICOM interface, through a library (named Vega) of platform-independent, object-oriented C++ codes. The Vega library is small and succinct, offering just the fundamental functions for reading/modifying/writing DICOM files in a C++ program. The library, however, is flexible enough to extract all MC required data from DICOM files, and write MC produced dose distributions into DICOM files that can then be processed in a treatment planning system environment. The library can be made available upon request to the authors.
Flattening filter free (FFF) beams due to their non-uniformity, are sub-optimal for larger field sizes. The purpose of this study was to investigate the incident electron beam distributions that would produce flat FFF beams without the use of flattening filter. Monte Carlo (MC) simulations with BEAMnrc and DOSXYZnrc codes have been performed to evaluate the feasibility of this approach. The dose distributions in water for open 6MV beams were simulated using Varian 21EX linac head model, which will be called flattening filter (FF) model. Flattening filter has then been removed from FF model, and MC simulations were performed using (1) 6 MeV electrons incident on the target, (2) 6 MeV electron beam with electron angular distributions optimized to provide as flat dose profiles as possible. Configuration (1) represents FFF beam while configuration (2) allowed producing a flat FFF (F4) beam. Optimizations have also been performed to produce flattest profiles for a set of dose rates (DRs) in the range from 1.25 to 2.4 of the DR of FF beam. Profiles and percentage depth doses PDDs from 6MV F4 beams have been calculated and compared to those from FF beam. Calculated profiles demonstrated improved flatness of the FFF beams. In fact, up to field sizes within the circle of 35 cm diameter the flatness of F4 beam at dmax was better or comparable to that of FF beam. At 20 cm off-axis the dose increased from 52% for FFF to 92% for F4 beam. Also, profiles of F4 beams did not change considerably with depth, and for large fields out-of-field dose was reduced by about a factor of two compared to FF beam. PDDs from F4 beams were similar to those of FFF beam. The DR for the largest modeled (44 cm diameter) F4 beam was higher than the DR from FF beam by a factor of 1.25. It was shown that the DR can be increased while maintaining beam flatness, but at the cost of reduced field size.
The next great leap toward improving treatment of cancer with radiation will require the combined use of online adaptive and magnetic resonance guided radiation therapy techniques with automatic X-ray beam orientation selection. Unfortunately, by uniting these advancements, we are met with a substantial expansion in the required dose information and consequential increase to the overall computational time imposed during radiation treatment planning, which cannot be handled by existing techniques for accelerating Monte Carlo dose calculation. We propose a deep convolutional neural network approach that unlocks new levels of acceleration and accuracy with regards to post-processed Monte Carlo dose results by relying on data-driven learned representations of low-level beamlet dose distributions instead of more limited filter-based denoising techniques that only utilize the information in a single dose input. Our method uses parallel UNET branches acting on three input channels before mixing latent understanding to produce noise-free dose predictions. Our model achieves a normalized mean absolute error of only 0.106% compared with the ground truth dose contrasting the 25.7% error of the under sampled MC dose fed into the network at prediction time. Our models per-beamlet prediction time is ~220ms, including Monte Carlo simulation and network prediction, with substantial additional acceleration expected from batched processing and combination with existing Monte Carlo acceleration techniques. Our method shows promise toward enabling clinical practice of advanced treatment technologies.
While spatial dose conformity delivered to a target volume has been pushed to its practical limits with advanced treatment planning and delivery, investigations in novel temporal dose delivery are unfolding new mechanisms. Recent advances in ultra-high dose radiotherapy, abbreviated as FLASH, indicate the potential for reduction in healthy tissue damage while preserving tumor control. FLASH therapy relies on very high dose rate of > 40Gy/sec with sub-second temporal beam modulation, taking a seemingly opposite direction from the conventional paradigm of fractionated therapy. FLASH brings unique challenges to dosimetry, beam control, and verification, as well as complexity of radiobiological effective dose through altered tissue response. In this review, we compare the dosimetric methods capable of operating under high dose rate environments. Due to excellent dose-rate independence, superior spatial (~<1 mm) and temporal (~ns) resolution achievable with Cherenkov and scintillation-based detectors, we show that luminescent detectors have a key role to play in the development of FLASH-RT, as the field rapidly progresses towards clinical adaptation. Additionally, we show that the unique ability of certain luminescence-based methods to provide tumor oxygenation maps in real-time with submillimeter resolution can elucidate the radiobiological mechanisms behind the FLASH effect. In particular, such techniques will be crucial for understanding the role of oxygen in mediating the FLASH effect.
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