Determination of the KQclinfclin,Qmsr fmsr correction factors for detectors used with an 800 MU/min CyberKnife(®) system equipped with fixed collimators and a study of detector response to small photon beams using a Monte Carlo method.

PURPOSE: In a previous work, output ratio (ORdet) measurements were performed for the 800 MU/min CyberKnife(®) at the Oscar Lambret Center (COL, France) using several commercially available detectors as well as using two passive dosimeters (EBT2 radiochromic film and micro-LiF TLD-700). The primary aim of the present work was to determine by Monte Carlo calculations the output factor in water (OFMC,w) and the [Formula: see text] correction factors. The secondary aim was to study the detector response in small beams using Monte Carlo simulation. METHODS: The LINAC head of the CyberKnife(®) was modeled using the PENELOPE Monte Carlo code system. The primary electron beam was modeled using a monoenergetic source with a radial gaussian distribution. The model was adjusted by comparisons between calculated and measured lateral profiles and tissue-phantom ratios obtained with the largest field. In addition, the PTW 60016 and 60017 diodes, PTW 60003 diamond, and micro-LiF were modeled. Output ratios with modeled detectors (ORMC,det) and OFMC,w were calculated and compared to measurements, in order to validate the model for smallest fields and to calculate [Formula: see text] correction factors, respectively. For the study of the influence of detector characteristics on their response in small beams; first, the impact of the atomic composition and the mass density of silicon, LiF, and diamond materials were investigated; second, the material, the volume averaging, and the coating effects of detecting material on the detector responses were estimated. Finally, the influence of the size of silicon chip on diode response was investigated. RESULTS: Looking at measurement ratios (uncorrected output factors) compared to the OFMC,w, the PTW 60016, 60017 and Sun Nuclear EDGE diodes systematically over-responded (about +6% for the 5 mm field), whereas the PTW 31014 Pinpoint chamber systematically under-responded (about -12% for the 5 mm field). ORdet measured with the SFD diode and PTW 60003 diamond detectors were in good agreement with OFMC,w except for the 5 mm field size (about -7.5% for the diamond and +3% for the SFD). A good agreement with OFMC,w was obtained with the EBT2 film and micro-LiF dosimeters (deviation less than 1.4% for all fields investigated). [Formula: see text] correction factors for several detectors used in this work have been calculated. The impact of atomic composition on the dosimetric response of detectors was found to be insignificant, unlike the mass density and size of the detecting material. CONCLUSIONS: The results obtained with the passive dosimeters showed that they can be used for small beam OF measurements without correction factors. The study of detector response showed that ORdet is depending on the mass density, the volume averaging, and the coating effects of the detecting material. Each effect was quantified for the PTW 60016 and 60017 diodes, the micro-LiF, and the PTW 60003 diamond detectors. None of the active detectors used in this work can be recommended as a reference for small field dosimetry, but an improved diode detector with a smaller silicon chip coated with tissue-equivalent material is anticipated (by simulation) to be a reliable small field dosimetric detector in a nonequilibrium field.

Study of dental prostheses influence in radiation therapy.

Dental prostheses made of high density material contribute to modify dose distribution in head and neck cancer treatment. Our objective is to quantify dose perturbation due to high density inhomogeneity with experimental measurements and Monte Carlo simulations. Firstly, measurements were carried in a phantom representing a human jaw with thermoluminescent detectors (GR200A) and EBT2 Gafchromic films in the vicinity of three samples: a healthy tooth, a tooth with amalgam and a Ni-Cr crown, irradiated in clinical configuration. Secondly, Monte Carlo simulations (BEAMnrc code) were assessed in an identical configuration. Experimental measurements and simulation results confirm the two well-known phenomena: firstly the passage from a low density medium to a high density medium induces backscattered electrons causing a dose increase at the interface, and secondly, the passage from a high density medium to a low density medium creates a dose decrease near the interface. So, the results show a 1.4% and 23.8% backscatter dose rise and attenuation after sample of 26.7% and 10.9% respectively for tooth with amalgam and crown compared to the healthy tooth. Although a tooth with amalgam has a density of about 12-13, the changes generated are not significant. However, the results for crown (density of 8) are very significant and the discordance observed may be due to calculation point size difference 0.8 mm and 0.25 mm respectively for TLD and Monte Carlo. The use of Monte Carlo simulations and experimental measurements provides objective evidence to evaluate treatment planning system results with metal dental prostheses.

[Simulation of lung motions using an artificial neural network]. / Utilisation d'un réseau de neurones artificiels pour la simulation des mouvements pulmonaires.

PURPOSE: A way to improve the accuracy of lung radiotherapy for a patient is to get a better understanding of its lung motion. Indeed, thanks to this knowledge it becomes possible to follow the displacements of the clinical target volume (CTV) induced by the lung breathing. This paper presents a feasibility study of an original method to simulate the positions of points in patient's lung at all breathing phases. PATIENTS AND METHODS: This method, based on an artificial neural network, allowed learning the lung motion on real cases and then to simulate it for new patients for which only the beginning and the end breathing data are known. The neural network learning set is made up of more than 600 points. These points, shared out on three patients and gathered on a specific lung area, were plotted by a MD. RESULTS: The first results are promising: an average accuracy of 1mm is obtained for a spatial resolution of 1 × 1 × 2.5mm(3). CONCLUSION: We have demonstrated that it is possible to simulate lung motion with accuracy using an artificial neural network. As future work we plan to improve the accuracy of our method with the addition of new patient data and a coverage of the whole lungs.

Development of a new CBR-based platform for human contamination emergency situations.

In the case of a radiological emergency situation, involving accidental human exposure, it is necessary to establish as soon as possible a dosimetry evaluation. In most cases, this evaluation is based on numerical representations and models of the victims. Unfortunately, personalised and realistic human representations are often unavailable for the exposed subjects. Hence, existing models like the 'Reference Man' representative of the average male individual are used. However, the accuracy of the treatment depends on the similarity of the phantom to the victim. The EquiVox platform (Research of Equivalent Voxel phantom) developed in this work uses the case-based reasoning principles to retrieve, from a set of existing phantoms, the most adapted one to represent the victim. This paper introduces the EquiVox platform and gives the example of in vivo lung monitoring optimisation to prove its efficiency in choosing the right model. It also presents the artificial neural network tools being developed to adapt the model to the victim.

[Dosimetric impact of the 2D motion of a platform simulating breathing during a dynamic mode treatment]. / Impact dosimétrique du mouvement 2D d'une plateforme simulant la respiration lors d'un traitement en mode dynamique.

Breathing-adapted techniques in external radiotherapy lead to the improvement of the taken into account of the tumour motion during the patient treatment. Indeed, this motion involves dosimetric uncertainties, in particular during a dynamic treatment (intensity-modulated radiation therapy, dynamic wedge...). As tumoral movement is complex and is carried out in various directions of space, a dynamic platform moving in one or two plans was conceived. This article approaches the technical aspects of design and functioning of this prototype. A study of the dosimetric effects of the respiratory movement on one and two plans during a dynamic treatment without gating will be presented. Films were irradiated while varying the rates with wedged fields at various speeds. The penumbra of beams were compared with the static case and appeared twice broader in the majority of the cases. The results highlighted the contributions of the longitudinal and the axial components of the motion on the form of the dose distribution. These results were completed with gamma index measurements to determine an internal margin. Moreover, this platform proves to be a promising tool for breathing-adapted treatment, in particularly to test the synchronisation of RPM system in fluoroscopic mode in board imaging system.

[Dosimetric influence of hip prosthesis during radiotherapeutic treatement]. / Impact dosimétrique des prothèses de hanche lors d'un traitement radiothérapeutique.

As the population become aged, many patients with hip prosthesis are treated for a pelvic cancer. The recommended ballistic must avoid to pass in the prosthesis, but sometimes it is inevitable. So it is essential to quantify with accuracy the dose modifications linked to the presence of metallic implant. The aim of this study is to analyze by Monte Carlo method these modifications in simple and complex models (anthropomorphic phantom) which take into account the geometry and the composition of the prosthesis and its coatings. Then, this methodology was used to study the behaviour of a treatment planning system in theses extreme conditions.

Calculations of dose distributions using a neural network model.

The main goal of external beam radiotherapy is the treatment of tumours, while sparing, as much as possible, surrounding healthy tissues. In order to master and optimize the dose distribution within the patient, dosimetric planning has to be carried out. Thus, for determining the most accurate dose distribution during treatment planning, a compromise must be found between the precision and the speed of calculation. Current techniques, using analytic methods, models and databases, are rapid but lack precision. Enhanced precision can be achieved by using calculation codes based, for example, on Monte Carlo methods. However, in spite of all efforts to optimize speed (methods and computer improvements), Monte Carlo based methods remain painfully slow. A newer way to handle all of these problems is to use a new approach in dosimetric calculation by employing neural networks. Neural networks (Wu and Zhu 2000 Phys. Med. Biol. 45 913-22) provide the advantages of those various approaches while avoiding their main inconveniences, i.e., time-consumption calculations. This permits us to obtain quick and accurate results during clinical treatment planning. Currently, results obtained for a single depth-dose calculation using a Monte Carlo based code (such as BEAM (Rogers et al 2003 NRCC Report PIRS-0509(A) rev G)) require hours of computing. By contrast, the practical use of neural networks (Mathieu et al 2003 Proceedings Journees Scientifiques Francophones, SFRP) provides almost instant results and quite low errors (less than 2%) for a two-dimensional dosimetric map.