This paper describes BEAM, a general purpose Monte Carlo code to simulate the radiation beams from radiotherapy units including high-energy electron and photon beams, 60Co beams and orthovoltage units. The code handles a variety of elementary geometric entities which the user puts together as needed (jaws, applicators, stacked cones, mirrors, etc.), thus allowing simulation of a wide variety of accelerators. The code is not restricted to cylindrical symmetry. It incorporates a variety of powerful variance reduction techniques such as range rejection, bremsstrahlung splitting and forcing photon interactions. The code allows direct calculation of charge in the monitor ion chamber. It has the capability of keeping track of each particle's history and using this information to score separate dose components (e.g., to determine the dose from electrons scattering off the applicator). The paper presents a variety of calculated results to demonstrate the code's capabilities. The calculated dose distributions in a water phantom irradiated by electron beams from the NRC 35 MeV research accelerator, a Varian Clinac 2100C, a Philips SL75-20, an AECL Therac 20 and a Scanditronix MM50 are all shown to be in good agreement with measurements at the 2 to 3% level. Eighteen electron spectra from four different commercial accelerators are presented and various aspects of the electron beams from a Clinac 2100C are discussed. Timing requirements and selection of parameters for the Monte Carlo calculations are discussed.

Advances in radiation treatment with beamlet-based intensity modulation, image-guided radiation therapy, and stereotactic radiosurgery (including specialized equipments like CyberKnife, Gamma Knife, tomotherapy, and high-resolution multileaf collimating systems) have resulted in the use of reduced treatment fields to a subcentimeter scale. Compared to the traditional radiotherapy with fields > or =4 x 4 cm2, this can result in significant uncertainty in the accuracy of clinical dosimetry. The dosimetry of small fields is challenging due to nonequilibrium conditions created as a consequence of the secondary electron track lengths and the source size projected through the collimating system that are comparable to the treatment field size. It is further complicated by the prolonged electron tracks in the presence of low-density inhomogeneities. Also, radiation detectors introduced into such fields usually perturb the level of disequilibrium. Hence, the dosimetric accuracy previously achieved for standard radiotherapy applications is at risk for both absolute and relative dose determination. This article summarizes the present knowledge and gives an insight into the future procedures to handle the nonequilibrium radiation dosimetry problems. It is anticipated that new miniature detectors with controlled perturbations and corrections will be available to meet the demand for accurate measurements. It is also expected that the Monte Carlo techniques will increasingly be used in assessing the accuracy, verification, and calculation of dose, and will aid perturbation calculations of detectors used in small and highly conformal radiation beams. rican Association of Physicists in Medicine.

The purpose of this study is to provide detailed characteristics of incident photon beams for different field sizes and beam energies. This information is critical to the future development of accurate treatment planning systems. It also enhances our knowledge of radiotherapy photon beams. The EGS4 Monte Carlo code, BEAM, has been used to simulate 6 and 18 MV photon beams from a Varian Clinac-2100EX accelerator. A simulated realistic beam is stored in a phase space data file, which contains details of each particle's complete history including where it has been and where it has interacted. The phase space files are analysed to obtain energy spectra, angular distribution, fluence profile and mean energy profiles at the phantom surface for particles separated according to their charge and history. The accuracy of a simulated beam is validated by the excellent agreement between the Monte Carlo calculated and measured dose distributions. Measured depth-dose curves are obtained from depth-ionization curves by accounting for newly introduced chamber fluence corrections and the stopping-power ratios for realistic beams. The study presents calculated depth-dose components from different particles as well as calculated surface dose and contribution from different particles to surface dose across the field. It is shown that the increase of surface dose with the increase of the field size is mainly due to the increase of incident contaminant charged particles. At 6 MV, the incident charged particles contribute 7% to 21% of maximum dose at the surface when the field size increases from 10 x 10 to 40 x 40 cm2. At 18 MV, their contributions are up to 11% and 29% of maximum dose at the surface for 10 x 10 cm2 and 40 x 40 cm2 fields respectively. However, the fluence of these incident charged particles is less than 1% of incident photon fluence in all cases.

The increased utilization of x-ray imaging in image-guided radiotherapy has dramatically improved the radiation treatment and the lives of cancer patients. Daily imaging procedures, such as cone-beam computed tomography (CBCT), for patient setup may significantly increase the dose to the patient's normal tissues. This study investigates the dosimetry from a kilovoltage (kV) CBCT for real patient geometries. Monte Carlo simulations were used to study the kV beams from a Varian on-board imager integrated into the Trilogy accelerator. The Monte Carlo calculated results were benchmarked against measurements and good agreement was obtained. The authors developed a novel method to calibrate Monte Carlo simulated beams with measurements using an ionization chamber in which the air-kerma calibration factors are obtained from an Accredited Dosimetry Calibration Laboratory. The authors have introduced a new Monte Carlo calibration factor, fMCcal, which is determined from the calibration procedure. The accuracy of the new method was validated by experiment. When a Monte Carlo simulated beam has been calibrated, the simulated beam can be used to accurately predict absolute dose distributions in the irradiated media. Using this method the authors calculated dose distributions to patient anatomies from a typical CBCT acquisition for different treatment sites, such as head and neck, lung, and pelvis. Their results have shown that, from a typical head and neck CBCT, doses to soft tissues, such as eye, spinal cord, and brain can be up to 8, 6, and 5 cGy, respectively. The dose to the bone, due to the photoelectric effect, can be as much as 25 cGy, about three times the dose to the soft tissue. The study provides detailed information on the additional doses to the normal tissues of a patient from a typical kV CBCT acquisition. The methodology of the Monte Carlo beam calibration developed and introduced in this study allows the user to calculate both relative and absolute absorbed doses.

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For electron beam reference dosimetry in radiotherapy, it is shown that by choosing the reference depth as dref = 0.6R(50)-0.1 cm, where R50 is the half-value depth in centimeters, the Spencer-Attix water-to-air stopping-power ratio at dref is given by (Llp)airw = 1.2534 - 0.1487 (R50)0.2144. This is derived from data for (Llp)airw obtained from realistic Monte Carlo simulations for 24 clinical beams. The rms deviation of this expression from the Monte Carlo calculations is 0.16%, with a maximum deviation of 0.26%. This approach fully takes into account the spectral differences between real electron beams of the same R50 and allows an absorbed-dose calibration at a standards laboratory to be easily and accurately transferred to a reference clinical beam. Using a single parameter to specify (Llp)airw, rather than the two parameters (R50 and depth) needed when the reference depth is chosen as the depth of dose maximum, has the potential to greatly simplify electron beam dosimetry protocols and allows the use of a similar formalism for photon and electron beam dosimetry. For use in converting a depth-ionization curve into a depth-dose curve, a somewhat less accurate but general expression for (Llp)w(air) as a function of R50 and depth is presented.

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The purpose of this work was to characterize expert variation in segmentation of intracranial structures pertinent to radiation therapy, and to assess a registration-driven atlas-based segmentation algorithm in that context. Eight experts were recruited to segment the brainstem, optic chiasm, optic nerves, and eyes, of 20 patients who underwent therapy for large space-occupying tumors. Performance variability was assessed through three geometric measures: volume, Dice similarity coefficient, and Euclidean distance. In addition, two simulated ground truth segmentations were calculated via the simultaneous truth and performance level estimation (STAPLE) algorithm and a novel application of probability maps. The experts and automatic system were found to generate structures of similar volume, though the experts exhibited higher variation with respect to tubular structures. No difference was found between the mean Dice coefficient (DSC) of the automatic and expert delineations as a group at a 5% significance level over all cases and organs. The larger structures of the brainstem and eyes exhibited mean DSC of approximately 0.8–0.9, whereas the tubular chiasm and nerves were lower, approximately 0.4–0.5. Similarly low DSC have been reported previously without the context of several experts and patient volumes. This study, however, provides evidence that experts are similarly challenged. The average maximum distances (maximum inside, maximum outside) from a simulated ground truth ranged from (−4.3, +5.4) mm for the automatic system to (−3.9, +7.5) mm for the experts considered as a group. Over all the structures in a rank of true positive rates at a 2 mm threshold from the simulated ground truth, the automatic system ranked second of the nine raters. This work underscores the need for large scale studies utilizing statistically robust numbers of patients and experts in evaluating quality of automatic algorithms.