Direct aperture optimization for IMRT using Monte Carlo generated beamlets

This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5 X 5.0 mm2 beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is approximately 33% compared to fluence-based optimization methods.     

Monte Carlo modelling of a virtual wedge

Compared with a set of physical photon wedges, a non physical wedge (virtual or dynamic wedge), realized by a moving collimator jaw, offers an alternative that allows creation of a wedged field with any arbitrary wedge angle instead of the traditional four physical wedges (15 degrees, 30 degrees, 45 degrees and 60 degrees). It is commonly assumed that non-physical wedges do not alter the photon spectrum compared with physical wedges that introduce beam hardening and loss of dose uniformity in the unwedged direction. In this study, we investigated the influence of a virtual wedge on the photon spectra of a 6-10 MV Siemens MD2 accelerator with the Monte Carlo code EGS4/BEAM. Good agreement was obtained between calculated and measured lateral dose profiles at the depth of maximum dose and at 10 cm depth for 20 x 20 cm2 fields for 6 and 10 MV photon beams. By comparing Monte Carlo models of a physical wedge and the virtual wedge that was studied in this work, it is confirmed that the latter has an insignificant effect on the beam quality, whereas the former can introduce significant beam hardening.     

Denoising of electron beam Monte Carlo dose distributions using digital filtering techniques

The Monte Carlo (MC) method has long been viewed as the ultimate dose distribution computational technique. The inherent stochastic dose fluctuations (i.e. noise), however, have several important disadvantages: noise will affect estimates of all the relevant dosimetric and radiobiological indices, and noise will degrade the resulting dose contour visualizations. We suggest the use of a post-processing denoising step to reduce statistical fluctuations and also improve dose contour visualization. We report the results of applying four different two-dimensional digital smoothing filters to two-dimensional dose images. The Integrated Tiger Series MC code was used to generate 10 MeV electron beam dose distributions at various depths in two different phantoms. The observed qualitative effects of filtering include: (a) the suppression of voxel-to voxel (high-frequency) noise and (b) the resulting contour plots are visually more comprehensible. Drawbacks include, in some cases, slight blurring of penumbra near the surface and slight blurring of other very sharp real dosimetric features. Of the four digital filters considered here, one, a filter based on a local least-squares principle, appears to suppress noise with negligible degradation of real dosimetric features. We conclude that denoising of electron beam MC dose distributions is feasible and will yield improved dosimetric reliability and improved visualization of dose distributions.     

Monte Carlo modelling of light propagation in breast tissue

Light transport in three-dimensional plane-parallel tissue slabs has been modelled by Monte Carlo analogue simulation. The model design has allowed the study of transmission properties that are pertinent to imaging systems for the detection of breast cancer. An important aspect of the investigations is that they make use of data obtained from quantitative measurements of light scattering and absorption in normal and pathological breast tissues. It is shown that an imaging technique which used a raster scanning laser and detector arrangement and plane-parallel compression of the breast could have considerable advantages in terms of improved transmittance, spatial unsharpness and contrast. Time-of-flight gating of images is also found to be beneficial provided that the light intensities after temporal filtering remain adequate.     

Monte Carlo role in radiobiological modelling of radiotherapy outcomes

Radiobiological models are essential components of modern radiotherapy. They are increasingly applied to optimize and evaluate the quality of different treatment planning modalities. They are frequently used in designing new radiotherapy clinical trials by estimating the expected therapeutic ratio of new protocols. In radiobiology, the therapeutic ratio is estimated from the expected gain in tumour control probability (TCP) to the risk of normal tissue complication probability (NTCP). However, estimates of TCP/NTCP are currently based on the deterministic and simplistic linear-quadratic formalism with limited prediction power when applied prospectively. Given the complex and stochastic nature of the physical, chemical and biological interactions associated with spatial and temporal radiation induced effects in living tissues, it is conjectured that methods based on Monte Carlo (MC) analysis may provide better estimates of TCP/NTCP for radiotherapy treatment planning and trial design. Indeed, over the past few decades, methods based on MC have demonstrated superior performance for accurate simulation of radiation transport, tumour growth and particle track structures; however, successful application of modelling radiobiological response and outcomes in radiotherapy is still hampered with several challenges. In this review, we provide an overview of some of the main techniques used in radiobiological modelling for radiotherapy, with focus on the MC role as a promising computational vehicle. We highlight the current challenges, issues and future potentials of the MC approach towards a comprehensive systems-based framework in radiobiological modelling for radiotherapy.     

Monte Carlo modelling of external radiotherapy photon beams

An essential requirement for successful radiation therapy is that the discrepancies between dose distributions calculated at the treatment planning stage and those delivered to the patient are minimized. An important component in the treatment planning process is the accurate calculation of dose distributions. The most accurate way to do this is by Monte Carlo calculation of particle transport, first in the geometry of the external or internal source followed by tracking the transport and energy deposition in the tissues of interest. Additionally, Monte Carlo simulations allow one to investigate the influence of source components on beams of a particular type and their contaminant particles. Since the mid 1990s, there has been an enormous increase in Monte Carlo studies dealing specifically with the subject of the present review, i.e., external photon beam Monte Carlo calculations, aided by the advent of new codes and fast computers. The foundations for this work were laid from the late 1970s until the early 1990s. In this paper we will review the progress made in this field over the last 25 years. The review will be focused mainly on Monte Carlo modelling of linear accelerator treatment heads but sections will also be devoted to kilovoltage x-ray units and 60Co teletherapy sources.     

A Monte Carlo study of grid performance in diagnostic radiology: task-dependent optimization for digital imaging

A Monte Carlo computational model has been used to optimize grid design in digital radiography. The optimization strategy involved finding grid designs that, for a constant signal-to-noise ratio, resulted in the lowest mean absorbed dose in the patient. Different examinations were simulated to explore the dependence of the optimal scatter-rejection technique on the imaging situation. A large range of grid designs was studied, including grids with both aluminium and fibre interspaces and covers, and compared to a 20 cm air gap. The results show that the optimal tube potential in each examination does not depend strongly on the scatter-rejection technique. There is a significant dose reduction associated with the use of fibre-interspaced grids, particularly in paediatric radiography. The optimal grid ratio and strip width increase with increasing scattering volume. With increasing strip density, the optimal strip width decreases, and the optimal grid ratio increases. Optimal grid ratios are higher than those used today, particularly for grids with large strip density. It is, however, possible to identify grids of good performance for a range of strip densities and grid ratios provided the strip width is selected accordingly. The computational method has been validated by comparison with measurements with a caesium iodide image receptor.     

Monte Carlo dose computation for IMRT optimization

A method which combines the accuracy of Monte Carlo dose calculation with a finite size pencil-beam based intensity modulation optimization is presented. The pencil-beam algorithm is employed to compute the fluence element updates for a converging sequence of Monte Carlo dose distributions. The combination is shown to improve results over the pencil-beam based optimization in a lung tumour case and a head and neck case. Inhomogeneity effects like a broader penumbra and dose build-up regions can be compensated for by intensity modulation.     

Monte Carlo simulations of a scintillation camera using GATE: validation and application modelling

Geant4 application for tomographic emission (GATE) is a recently developed simulation platform based on Geant4, specifically designed for PET and SPECT studies. In this paper we present validation results of GATE based on the comparison of simulations against experimental data, acquired with a standard SPECT camera. The most important components of the scintillation camera were modelled. The photoelectric effect. Compton and Rayleigh scatter are included in the gamma transport process. Special attention was paid to the processes involved in the collimator: scatter, penetration and lead fluorescence. A LEHR and a MEGP collimator were modelled as closely as possible to their shape and dimensions. In the validation study, we compared the simulated and measured energy spectra of different isotopes: 99mTc, 22Na, 57Co and 67Ga. The sensitivity was evaluated by using sources at varying distances from the detector surface. Scatter component analysis was performed in different energy windows at different distances from the detector and for different attenuation geometries. Spatial resolution was evaluated using a 99mTc source at various distances. Overall results showed very good agreement between the acquisitions and the simulations. The clinical usefulness of GATE depends on its ability to use voxelized datasets. Therefore, a clinical extension was written so that digital patient data can be read in by the simulator as a source distribution or as an attenuating geometry. Following this validation we modelled two additional camera designs: the Beacon transmission device for attenuation correction and the Solstice scanner prototype with a rotating collimator. For the first setup a scatter analysis was performed and for the latter design. the simulated sensitivity results were compared against theoretical predictions. Both case studies demonstrated the flexibility and accuracy of GATE and exemplified its potential benefits in protocol optimization and in system design.     

Monte Carlo modelling of radiotherapy kV x-ray units.

To obtain accurate information for absorbed dose calculations in water for kilovoltage x-rays, the photon spectrum, planar fluence and the angular distribution of the photons at the collimator exit of the x-ray unit have to be known. The only way to obtain this information is by Monte Carlo (MC) simulation. Compared with the situation for high-energy photons and electrons, where in recent years numerous papers have been devoted to MC modelling of complete clinical accelerator units, there is a lack of similar work for kV x-ray units. A reliable MC model for a kV x-ray unit would allow the output information to be used in a treatment planning system for regular and irregular treatment fields. Furthermore, with MC simulation, perturbation factors of dose-measuring devices, such as those specified in codes of practice, can be calculated. In this work, the MC code EGS4/BEAM was used to build realistic models of two complete x-ray units. The tungsten target, exit window, collimator, additional filtration and applicator were taken into account. For some aspects of the work, a comparison was made with the simulations from another MC code, MCNP4B. The contribution to the characteristic radiation from electron impact ionization and from the photoelectric effect of reabsorbed bremsstrahlung photons was studied. Calculated and measured photon fluence spectra in air and half-value layers for a Philips MCN410 tube were compared for several anode voltages and additional filtrations. Results from the two codes agreed well, and the agreement with measured spectra was found to be good for energies above 50 keV but rather less good below that energy. For a Siemens Stabilipan 2 Th300 x-ray tube, HVLs and dose distributions in water were compared with measurements for several clinical x-ray qualities. For most of the combinations of radiation qualities and applicators, good agreement was obtained, although there were also some cases where the agreement was not so good. Electron contamination and photon build-up at the water surface were studied using MC simulation. The influence of depth on the photon spectral distribution was investigated. Both EGS4/BEAM and MCNP4B, in their default versions, handle inadequately the production of characteristic x-rays. This was found to have only a minor influence on the calculated dosimetric quantities. Simulations with MCNP4B required the use of several variance reduction techniques in order to obtain results within reasonable calculation times.     

Monte Carlo modelling of electron beams from medical accelerators

Monte Carlo simulation of radiation transport is considered to be one of the most accurate methods of radiation therapy dose calculation. With the rapid development of computer technology, Monte Carlo based treatment planning for radiation therapy is becoming practical. A basic requirement for Monte Carlo treatment planning is a detailed knowledge of the radiation beams from medical accelerators. A practical approach to obtain the above is to perform Monte Carlo simulation of radiation transport in the medical accelerator. Additionally, Monte Carlo modelling of the treatment machine head can also improve our understanding of clinical beam characteristics, help accelerator design and improve the accuracy of clinical dosimetry by providing more realistic beam data. This paper summarizes work over the past two decades on Monte Carlo simulation of clinical electron beams from medical accelerators.     

Photon beam characterization and modelling for Monte Carlo treatment planning

Photon beams of 4, 6 and 15 MV from Varian Clinac 2100C and 2300C/D accelerators were simulated using the EGS4/BEAM code system. The accelerators were modelled as a combination of component modules (CMs) consisting of a target, primary collimator, exit window, flattening filter, monitor chamber, secondary collimator, ring collimator, photon jaws and protection window. A full phase space file was scored directly above the upper photon jaws and analysed using beam data processing software, BEAMDP, to derive the beam characteristics, such as planar fluence, angular distribution, energy spectrum and the fractional contributions of each individual CM. A multiple-source model has been further developed to reconstruct the original phase space. Separate sources were created with accurate source intensity, energy, fluence and angular distributions for the target, primary collimator and flattening filter. Good agreement (within 2%) between the Monte Carlo calculations with the source model and those with the original phase space was achieved in the dose distributions for field sizes of 4 cm x 4 cm to 40 cm x 40 cm at source surface distances (SSDs) of 80-120 cm. The dose distributions in lung and bone heterogeneous phantoms have also been found to be in good agreement (within 2%) for 4, 6 and 15 MV photon beams for various field sizes between the Monte Carlo calculations with the source model and those with the original phase space.     

自动曝光控制技术在数字化 X 射线胸部摄影中的应用探讨简

目的探讨自动曝光控制（AEC）技术在胸部数字化X射线摄影（DR）中的应用及其对图像质量的影响。方法使用AEC技术和根据经验设置曝光条件法,分别采集50张胸部后前位X射线图像,分为2组。试验组使用AEC技术：其中男性27例,女性23例,年龄9-81岁,平均年龄43．6岁。对照组使用手动选择曝光条件：其中男性24例．女性26例．年龄17-76岁,平均年龄45.3岁。记录每次成像的曝光指数（EU并对两组数据进行统计学分析。结果试验组与对照组图像EI比较,差异无统计学意义（1951．00vs1961．80,P〉0．05）,且绝大多数图像质量都在可诊断范围之内。但AEC技术EI的标准差较小．说明AEC技术能更精确地控制曝光量。结论AEC技术可以减少因曝光量不足引起的图像质量下降．也可以避免因曝光过度而产生不必要的患者辐射．     

Beta-particle dosimetry of the trabecular skeleton using Monte Carlo transport within 3D digital images

Presently, skeletal dosimetry models utilized in clinical medicine simulate electron path lengths through skeletal regions based upon distributions of linear chords measured across bone trabeculae and marrow cavities. In this work, a human thoracic vertebra has been imaged via nuclear magnetic resonance (NMR) spectroscopy yielding a three-dimensional voxelized representation of this skeletal site. The image was then coupled to the radiation transport code EGS4 allowing for 3D tracing of electron paths within its true 3D structure. The macroscopic boundaries of the trabecular regions, as well as the cortex of cortical bone surrounding the bone site, were explicitly considered in the voxelized transport model. For the case of a thoracic vertebra, energy escape to the cortical bone became significant at source energies exceeding approximately 2 MeV. Chord-length distributions were acquired from the same NMR image, and subsequently used as input for a chord-based dosimetry model. Differences were observed in the absorbed fractions given by the chord-based model and the voxel transport model, suggesting that some of the input chord distributions for the chord-based models may not be accurate. Finally, this work shows that skeletal mass estimates can be made from the same NMR image in which particle transport is performed. This feature allows one to determine a skeletal S-value using absorbed fraction and mass data taken from the same anatomical tissue sample. The techniques developed in this work may be applied to a variety of skeletal sites, thus allowing for the development of skeletal dosimetry models at all skeletal sites for both males and females and as a function of subject age.     

Optimization of x-ray spectra in digital mammography through Monte Carlo simulations

In this work, a Monte Carlo code was used to investigate the performance of different x-ray spectra in digital mammography, through a figure of merit (FOM), defined as FOM = CNR2/(ˉ)D(g), with CNR being the contrast-to-noise ratio in image and [Formula: see text] being the average glandular dose. The FOM was studied for breasts with different thicknesses t (2 cm ≤ t ≤ 8 cm) and glandular contents (25%, 50% and 75% glandularity). The anode/filter combinations evaluated were those traditionally employed in mammography (Mo/Mo, Mo/Rh, Rh/Rh), and a W anode combined with Al or K-edge filters (Zr, Mo, Rh, Pd, Ag, Cd, Sn), for tube potentials between 22 and 34 kVp. Results show that the W anode combined with K-edge filters provides higher values of FOM for all breast thicknesses investigated. Nevertheless, the most suitable filter and tube potential depend on the breast thickness, and for t ≥ 6 cm, they also depend on breast glandularity. Particularly for thick and dense breasts, a W anode combined with K-edge filters can greatly improve the digital technique, with the values of FOM up to 200% greater than that obtained with the anode/filter combinations and tube potentials traditionally employed in mammography. For breasts with t < 4 cm, a general good performance was obtained with the W anode combined with 60 μm of the Mo filter at 24-25 kVp, while 60 μm of the Pd filter provided a general good performance at 24-26 kVp for t = 4 cm, and at 28-30 and 29-31 kVp for t = 6 and 8 cm, respectively.     

Analytical positron range modelling in heterogeneous media for PET Monte Carlo simulation

Monte Carlo simulation codes that model positron interactions along their tortuous path are expected to be accurate but are usually slow. A simpler and potentially faster approach is to model positron range from analytical annihilation density distributions. The aims of this paper were to efficiently implement and validate such a method, with the addition of medium heterogeneity representing a further challenge. The analytical positron range model was evaluated by comparing annihilation density distributions with those produced by the Monte Carlo simulator GATE and by quantitatively analysing the final reconstructed images of Monte Carlo simulated data. In addition, the influence of positronium formation on positron range and hence on the performance of Monte Carlo simulation was investigated. The results demonstrate that 1D annihilation density distributions for different isotope-media combinations can be fitted with Gaussian functions and hence be described by simple look-up-tables of fitting coefficients. Together with the method developed for simulating positron range in heterogeneous media, this allows for efficient modelling of positron range in Monte Carlo simulation. The level of agreement of the analytical model with GATE depends somewhat on the simulated scanner and the particular research task, but appears to be suitable for lower energy positron emitters, such as (18)F or (11)C. No reliable conclusion about the influence of positronium formation on positron range and simulation accuracy could be drawn.     

Diagnostic x-ray dosimetry using Monte Carlo simulation

An Electron Gamma Shower version 4 (EGS4) based user code was developed to simulate the absorbed dose in humans during routine diagnostic radiological procedures. Measurements of absorbed dose using thermoluminescent dosimeters (TLDs) were compared directly with EGS4 simulations of absorbed dose in homogeneous, heterogeneous and anthropomorphic phantoms. Realistic voxel-based models characterizing the geometry of the phantoms were used as input to the EGS4 code. The voxel geometry of the anthropomorphic Rando phantom was derived from a CT scan of Rando. The 100 kVp diagnostic energy x-ray spectra of the apparatus used to irradiate the phantoms were measured, and provided as input to the EGS4 code. The TLDs were placed at evenly spaced points symmetrically about the central beam axis, which was perpendicular to the cathode-anode x-ray axis at a number of depths. The TLD measurements in the homogeneous and heterogenous phantoms were on average within 7% of the values calculated by EGS4. Estimates of effective dose with errors less than 10% required fewer numbers of photon histories (1 x 10(7)) than required for the calculation of dose profiles (1 x 10(9)). The EGS4 code was able to satisfactorily predict and thereby provide an instrument for reducing patient and staff effective dose imparted during radiological investigations.     

Digital mammography image simulation using Monte Carlo

Monte Carlo simulations of digital images of the contrast detail phantom and the ACR phantom are presented for two different x-ray digital mammography modalities: a synchrotron mammography system and a next-generation scanning slot clinical system. A combination of variance reduction methods made it possible to simulate accurate images using real pixel dimensions within reasonable computation times. The complete method of image simulation, including a simple detector response model, a simple noise model, and the incorporation of system effects (MTF), is presented. The simulated images of the phantoms show good agreement with images measured on the two systems.