The aim of this work is primarily to validate the advanced techniques for treatment planning and dosimetric verification for modern megavoltage x-ray radiotherapy. With the advent of modern radiotherapy techniques, there is a great need for assuring quality of the radiation dose distributions generated by the advanced intensity modulated treatments (IMRT/VMAT). This is typically accomplished by the assessment of the treatment plan quality at the planning stage and then verification of the dose distributions through measurements on the phantoms or independent dose calculations prior to the actual delivery of these plans to patients. The major focus of this work is to clinically evaluate the modern 2D and 3D dose verification techniques. The measurement-based dosimetry systems investigated were ArcCHECK/3DVH and SRS MapCHECK. AcrCHECK/3DVH system uses the measurement-guided dose reconstruction algorithm to correct the predicted dose in the patient dataset. The system was intended for VMAT/IMRT QA. SRS MapCHECK was investigated for SRS treatments. The independent dose calculation system was DoseCHECK which employed a GPU-accelerated convolution-superposition of algorithm for 3D dose reconstruction on the patient dataset. Next, a hybrid dose verification system (PerFRACTION) was evaluated, which takes input from both the treatment planning system and the linac EPID and produces a measurement-guided 3D dose distribution for comparison with the plan. This system was investigated for potential QA applications to a modern, efficient SRS technique, involving simultaneously treating multiple targets with a single isocenter. The performance of all dosimetry systems was validated against well-characterized independent dosimeters, such as ion chamber, film and scintillator detectors, or 3D arrays (Delta4), using stringent dose comparison criteria to test their limits for the intended clinical applications. For the initial plan quality evaluation of a novel tool (Feasibility DVH) was investigated. This tool a priori estimates best achievable dose volume histograms for a specific patient, based on the basic physics properties of the megavoltage x-rays, thus helping the planners to guide their efforts. All studied dosimetry systems showed an excellent agreement of the average gamma (a mathematical combination of DD and DTA) passing rates >98% for most of the plans. The 3% DD/2mm DTA criteria were used for extracranial plans and 3%/1mm for intracranial SRS plans. As dictated by the logic of the application, the comparisons were made against TPS calculations, a bi-planar array, or film measurements. Similarly the average percent point dose errors <2% were observed against the ion chambers or film. In the rare instances when the deviations were larger, intuitive explanations were provided, based on either the physics of the plans or inhomogeneous patient anatomy and resulting algorithm limitations. Feasibility DVH was shown to reliably predict the best possible organ sparing for clinical head-and-neck VMAT plans. Overall the investigated dosimetry systems were found reliable and feasible for their intended clinical use.

Pour avoir une idée sur la qualité du réseau, la majorité des acteurs concernés (opérateurs réseau, fournisseurs de service) se basent sur la Qualité de Service (Quality of Service). Cette mesure a montré des limites et beaucoup d’efforts ont été déployés pour mettre en place une nouvelle métrique qui reflète, de façon plus précise, la qualité du service offert. Cette mesure s’appelle la qualité d’expérience (Quality of Experience). La qualité d’expérience reflète la satisfaction de l’utilisateur par rapport au service qu’il utilise. L’évaluation de la qualité d’expérience est devenue primordiale pour les fournisseurs de services et les fournisseurs de contenus. Cette nécessité nous a poussés à innover et mettre en place des nouvelles méthodes pour estimer la QoE. Dans cette thèse, nous travaillons sur l’estimation de la QoE dans le cas des communications Voix sur IP et dans le cas de la vidéo sur IP. Nous étudions les performances et la qualité des codecs iLBC, Speex et Silk pour la VoIP et les codecs MPEG-2 et H.264/SVC pour la vidéo sur IP. Nous étudions l’impact que peut avoir la majorité des paramètres réseaux, des paramètres sources (au niveau du codage) et destinations (au niveau du décodage) sur la qualité finale. Afin de mettre en place des outils précis d’estimation de la QoE en temps réel, nous nous basons sur la méthodologie Pseudo-Subjective Quality Assessment. La méthodologie PSQA est basée sur un modèle mathématique appelé les réseaux de neurones artificiels. En plus des réseaux de neurones, nous utilisons la régression polynomiale pour l’estimation de la QoE dans le cas de la VoIP. / Quality of Experience (QoE) is the key criteria for evaluating the Media Services. Unlike objective Quality of Service (QoS) metrics, QoE is more accurate to reflect the user experience. The Future of Internet is definitely going to be Media oriented. Towards this, there is a profound need for an efficient measure of the Quality of Experience (QoE). QoE will become the prominent metric to consider when deploying Networked Media services. In this thesis, we provide several methods to estimate the QoE of different media services: Voice and Video over IP. We study the performance and the quality of several VoIP codecs like iLBC, Speex and Silk. Based on this study, we proposed two methods to estimate the QoE in real-time context, without any need of information of the original voice sequence. The first method is based on polynomial regression, and the second one is based on an hybrid methodology (objective and subjective) called Pseudo-Subjective Quality Assessment. PSQA is based on the artificial neural network mathematical model. As for the VoIP, we propose also a tool to estimate video quality encoded with MPEG-2 and with H.264/SVC. We studied also the impact of several network parameters on the quality, and the impact of some encoding parameters on the SVC video quality. We tested also the performance of several SVC encoders and proposed some SVC encoding recommendations.