0000000000178730
AUTHOR
Régine Gschwind
9 Development of an experimental tool to evaluate normal tissue 3D doses in external-beam radiotherapy
Introduction Recently, cancer treatment improvement enabled an increase in patients’ survival rate. In more than half of the cases, radiotherapy participates in the cure for cancer. The efficacy of this technique is well known but it inevitably delivers doses to normal tissues exposing them to radio-induced complications risks [1] . Moreover, the longer patients’ life expectancy increases the risk of developing long-term complications such as second cancers. Thus, evaluating the risks following cancer treatment involving radiotherapy constitutes a major challenge. In this context, an experimental tool has been developed to evaluate normal tissue doses delivered by the different radiotherapy…
Characterisation of two new radiochromic gel dosimeters TruView™ and ClearView™ in combination with the vista™ optical CT scanner: A feasibility study
This study aims at characterising the properties of TruView™ and ClearView™ two new gel dosimeters (Modus Medical Devices Inc.) and at studying the feasibility of relative dosimetry using these dosimeters and the Vista™ Optical CT scanner to accurately evaluate dose.In this work, we investigated key dosimetric aspects (dose response, energy and dose rate dependence) and stability of these radiochromic gels initiated in preliminary works (Huet et al., 2017; Colnot et al., 2017) using spectrophotometric measurements. Moreover, by mean of optical CT scanning (Vista™), their performances to measure relative depth dose (PDD) and cross profiles were analysed.TruView™ and ClearView™ present a line…
Abstract ID: 133 Fast and accurate 3D dose distribution computations using artificial neural networks
In radiation therapy, the trade-off between accuracy and speed is the key of the algorithms used in Treatment Planning Systems (TPS). For photon beams, commercial solutions generally relies on analytic algorithms, biased Monte Carlo, or heavily parallelized Monte Carlo on Graphics Processing Units (GPU). Alternatively, we propose an algorithm using Artificial Neural Network (ANN) to compute the dose distributions resulting from ionizing radiations inside a phantom [1] , [2] . We present an evolution of this platform taking into account modulated field sizes and shapes, and various orientations of the beam to the phantom. Firstly, tomodensitometry-based phantoms are created to validate the d…