No description available.

<p>Microbeam radiation therapy (MRT) is an experimental radiotherapy concept that has been primarily developed for the treatment of malignant brain tumours. MRT uses high flux synchrotron x-rays delivered as an array of parallel microbeams in high doses of irradiation in fractions of seconds. The aims of this study were to 1) investigate the induction of bystander effects after normal and tumour-bearing rat brains were exposed to MRT and homogenous radiation; 2) validate a brain bystander proteome by detecting protein expression throughout immunohistochemistry: and 3) to investigate whether communication of bystander signals can be produced between animals.</p> <p>Healthy and tumour-bearing Wistar rats were exposed to 17.5, 35, 70 or 350 Gy of MRT or homogenous field of synchrotron radiation to the right brain hemisphere. To study the communication of bystander effects between animals, irradiated rats shared the same cage with non-irradiated rats over a period of 48 hours. After euthanasia of the animals, brains and bladders were dissected, and samples for immunohistochemistry and bystander clonogenic assays were set up.</p> <p>Clonogenic survival of the reporter HPVG cells showed that bystander effects occurred in both the non-irradiated hemisphere and bladder of normal and tumour-bearing rats, while the irradiated hemisphere showed the direct effects of radiation. Moreover, communication of bystander signals was confirmed in the non-irradiated rats.</p> <p>In conclusion, the results suggest that the MRT and homogenous radiation of unilateral normal and tumour-bearing rat brains produce bystander signals that affect the whole organism and that those signals also can be transmitted to non-irradiated animals.</p> / Master of Science (MSc)

Eine der drei Säulen der Krebsbehandlung ist die Strahlentherapie. Einer der neuesten Ansätze hierbei ist die Bestrahlung mit Ionen, zurzeit insbesondere Protonen und Kohlenstoffionen. Diese Hochpräzisionstherapie erfordert ein hohes Maß an Kontrolle, da die applizierte Dosisverteilung sehr empfindlich von Dichteveränderungen im durchstrahlten Gewebe abhängt. Das bisher einzige klinisch eingesetzte Verfahren zur in vivo Überwachung der Dosisapplikation bei Ionenbestrahlungen ist die Positronen-Emissions-Tomographie (PET). Sie ermöglicht eine Verifikation der Teilchenreichweite sowie der Lage des Bestrahlungsfeldes. Die mit der PET-Methode gemessene Aktivitätsverteilung lässt sich jedoch nicht direkt mit der geplanten Dosisverteilung vergleichen. Daher ist eine Vorherberechnung der erwarteten Aktivitätsverteilung auf der Grundlage des Bestrahlungsplanes notwendig, welche dann mit der Messung verglichen wird und eine qualitative Beurteilung der Bestrahlung ermöglicht. Die Vorherberechnung der erwarteten Aktivitätsverteilung erfordert bislang die Kenntnis einer Vielzahl von Wirkungsquerschnitten. Nur für wenige dieser Wirkungsquerschnitte liegen jedoch Messdaten im benötigten Energiebereich und mit ausreichender Genauigkeit vor. Daher verwenden viele Monte-Carlo-Simulationen intrinsische Kernmodelle oder semi-empirische Modellierungen, die häufig eine unzureichende Genauigkeit aufweisen. In Fachkreisen ist bisher noch nicht geklärt, welches die optimale Ionensorte für die Tumortherapie ist. Insbesondere Lithiumionen weisen aufgrund ihrer physikalischen und radiobiologischen Eigenschaften ein großes Potenzial auf. Auch für Bestrahlungen mit diesen Ionen ist ein PET-Monitoring der Therapie erstrebenswert. In der vorliegenden Arbeit wird zunächst die Anwendbarkeit der Reichweite-Verifikation mittels PET bei Bestrahlung mit Lithiumionen gezeigt. Des Weiteren wird ein Konzept zur Modellierung der Positronenemitter-Verteilung ohne Kenntnis der Wirkungsquerschnitte entwickelt. Diese Vorhersage beruht auf in Referenzmaterialien (Wasser, Graphit und Polyethylen) gemessenen tiefenabhängigen Positronenemitter-Yields, mit welchen durch geeignete Linearkombination die Verteilung der Positronenemitter in beliebigen Materialien bekannter Stöchiometrie vorausberechnet werden kann. Die Anwendbarkeit des Yield-Konzeptes wird gezeigt für Lithium- und Kohlenstoffbestrahlungen homogener Polymethylmethacrylat (PMMA) Targets sowie verschiedener inhomogener Targets. / One of the three main tumour treatment forms is radiation therapy. Here, the application of ion beams, in particular protons and carbon ions, is of growing importance. This high precision therapy requires a consequent monitoring of the dose delivery since the induced dose deposition is very sensitive to density changes in the irradiated tissue. Up to now, positron emission tomography (PET) is the only in vivo method in clinical use for monitoring the dose deposition in ion beam therapy. It allows for the verification of the particle range as well as the position of the irradiation field. The distribution of activity measured by means of PET cannot be compared directly to the planned dose distribution. Thus, a calculation of the expected activity distribution is required which then can be compared to the measurement. Simulation of the expected activity distribution requires the exact knowledge of various cross sections. Only a few of them have been measured in the required energy range so far. Therefore, in Monte Carlo simulations often intrinsic nuclear models or semi-empirical parametrization are used which often exhibit insufficient accuray. Among experts the question on the optimum ion species for tumour therapy is still open. Especially lithium ions exhibit a great potential due to their favourable physical and radiobiological properties. Also for these ions a PET monitoring is highly desirable. The presented work shows the feasibility of range verification by means of PET for lithium irradiation. Furthermore, a concept for modeling positron emitter distributions without the knowledge of cross sections is developed. This prediction is based on depth-dependent positron emitter yields measured in reference materials (water, graphite and polyethylene). With these data the positron emitter distribution in any material of known stoichiometry can be calculated by means of an appropriate linear combination. The feasibility of the yield concept is shown for lithium and carbon irradiation, respectively, of homogeneous polymethyl methacrylate (PMMA) as well as various inhomogeneous targets.

This thesis addresses three problems related to image registration, prediction and tracking, applied to Angiography and Oncology. For image analysis, various probabilistic models have been employed to characterize the image deformations, target motions and state estimations. (i) In Digital Subtraction Angiography (DSA), having a high quality visualization of the blood motion in the vessels is essential both in diagnostic and interventional applications. In order to reduce the inherent movement artifacts in DSA, non-rigid image registration is used before subtracting the mask from the contrast image. DSA image registration is a challenging problem, as it requires non-rigid matching across spatially non-uniform control points, at high speed. We model the problem of sub-pixel matching, as a labeling problem on a non-uniform Markov Random Field (MRF). We use quad-trees in a novel way to generate the non uniform grid structure and optimize the registration cost using graph-cuts technique. The MRF formulation produces a smooth displacement field which results in better artifact reduction than with the conventional approach of independently registering the control points. The above approach is further improved using two models. First, we introduce the concept of pivotal and non-pivotal control points. `Pivotal control points' are nodes in the Markov network that are close to the edges in the mask image, while 'non-pivotal control points' are identified in soft tissue regions. This model leads to a novel MRF framework and energy formulation. Next, we propose a Gaussian MRF model and solve the energy minimization problem for sub-pixel DSA registration using Random Walker (RW). An incremental registration approach is developed using quad-tree based MRF structure and RW, wherein the density of control points is hierarchically increased at each level M depending of the features to be used and the required accuracy. A novel numbering scheme of the control points allows us to reuse the computations done at level M in M + 1. Both the models result in an accelerated performance without compromising on the artifact reduction. We have also provided a CUDA based design of the algorithm, and shown performance acceleration on a GPU. We have tested the approach using 25 clinical data sets, and have presented the results of quantitative analysis and clinical assessment. (ii) In External Beam Radiation Therapy (EBRT), in order to monitor the intra fraction motion of thoracic and abdominal tumors, the lung diaphragm apex can be used as an internal marker. However, tracking the position of the apex from image based observations is a challenging problem, as it undergoes both position and shape variation. We propose a novel approach for tracking the ipsilateral hemidiaphragm apex (IHDA) position on CBCT projection images. We model the diaphragm state as a spatiotemporal MRF, and obtain the trace of the apex by solving an energy minimization problem through graph-cuts. We have tested the approach using 15 clinical data sets and found that this approach outperforms the conventional full search method in terms of accuracy. We have provided a GPU based heterogeneous implementation of the algorithm using CUDA to increase the viability of the approach for clinical use. (iii) In an adaptive radiotherapy system, irrespective of the methods used for target observations there is an inherent latency in the beam control as they involve mechanical movement and processing delays. Hence predicting the target position during `beam on target' is essential to increase the control precision. We propose a novel prediction model (called o set sine model) for the breathing pattern. We use IHDA positions (from CBCT images) as measurements and an Unscented Kalman Filter (UKF) for state estimation. The results based on 15 clinical datasets show that, o set sine model outperforms the state of the art LCM model in terms of prediction accuracy.

Eine der drei Säulen der Krebsbehandlung ist die Strahlentherapie. Einer der neuesten Ansätze hierbei ist die Bestrahlung mit Ionen, zurzeit insbesondere Protonen und Kohlenstoffionen. Diese Hochpräzisionstherapie erfordert ein hohes Maß an Kontrolle, da die applizierte Dosisverteilung sehr empfindlich von Dichteveränderungen im durchstrahlten Gewebe abhängt. Das bisher einzige klinisch eingesetzte Verfahren zur in vivo Überwachung der Dosisapplikation bei Ionenbestrahlungen ist die Positronen-Emissions-Tomographie (PET). Sie ermöglicht eine Verifikation der Teilchenreichweite sowie der Lage des Bestrahlungsfeldes. Die mit der PET-Methode gemessene Aktivitätsverteilung lässt sich jedoch nicht direkt mit der geplanten Dosisverteilung vergleichen. Daher ist eine Vorherberechnung der erwarteten Aktivitätsverteilung auf der Grundlage des Bestrahlungsplanes notwendig, welche dann mit der Messung verglichen wird und eine qualitative Beurteilung der Bestrahlung ermöglicht. Die Vorherberechnung der erwarteten Aktivitätsverteilung erfordert bislang die Kenntnis einer Vielzahl von Wirkungsquerschnitten. Nur für wenige dieser Wirkungsquerschnitte liegen jedoch Messdaten im benötigten Energiebereich und mit ausreichender Genauigkeit vor. Daher verwenden viele Monte-Carlo-Simulationen intrinsische Kernmodelle oder semi-empirische Modellierungen, die häufig eine unzureichende Genauigkeit aufweisen. In Fachkreisen ist bisher noch nicht geklärt, welches die optimale Ionensorte für die Tumortherapie ist. Insbesondere Lithiumionen weisen aufgrund ihrer physikalischen und radiobiologischen Eigenschaften ein großes Potenzial auf. Auch für Bestrahlungen mit diesen Ionen ist ein PET-Monitoring der Therapie erstrebenswert. In der vorliegenden Arbeit wird zunächst die Anwendbarkeit der Reichweite-Verifikation mittels PET bei Bestrahlung mit Lithiumionen gezeigt. Des Weiteren wird ein Konzept zur Modellierung der Positronenemitter-Verteilung ohne Kenntnis der Wirkungsquerschnitte entwickelt. Diese Vorhersage beruht auf in Referenzmaterialien (Wasser, Graphit und Polyethylen) gemessenen tiefenabhängigen Positronenemitter-Yields, mit welchen durch geeignete Linearkombination die Verteilung der Positronenemitter in beliebigen Materialien bekannter Stöchiometrie vorausberechnet werden kann. Die Anwendbarkeit des Yield-Konzeptes wird gezeigt für Lithium- und Kohlenstoffbestrahlungen homogener Polymethylmethacrylat (PMMA) Targets sowie verschiedener inhomogener Targets. / One of the three main tumour treatment forms is radiation therapy. Here, the application of ion beams, in particular protons and carbon ions, is of growing importance. This high precision therapy requires a consequent monitoring of the dose delivery since the induced dose deposition is very sensitive to density changes in the irradiated tissue. Up to now, positron emission tomography (PET) is the only in vivo method in clinical use for monitoring the dose deposition in ion beam therapy. It allows for the verification of the particle range as well as the position of the irradiation field. The distribution of activity measured by means of PET cannot be compared directly to the planned dose distribution. Thus, a calculation of the expected activity distribution is required which then can be compared to the measurement. Simulation of the expected activity distribution requires the exact knowledge of various cross sections. Only a few of them have been measured in the required energy range so far. Therefore, in Monte Carlo simulations often intrinsic nuclear models or semi-empirical parametrization are used which often exhibit insufficient accuray. Among experts the question on the optimum ion species for tumour therapy is still open. Especially lithium ions exhibit a great potential due to their favourable physical and radiobiological properties. Also for these ions a PET monitoring is highly desirable. The presented work shows the feasibility of range verification by means of PET for lithium irradiation. Furthermore, a concept for modeling positron emitter distributions without the knowledge of cross sections is developed. This prediction is based on depth-dependent positron emitter yields measured in reference materials (water, graphite and polyethylene). With these data the positron emitter distribution in any material of known stoichiometry can be calculated by means of an appropriate linear combination. The feasibility of the yield concept is shown for lithium and carbon irradiation, respectively, of homogeneous polymethyl methacrylate (PMMA) as well as various inhomogeneous targets.

Prostate cancer is one of the most frequently diagnosed cancers and failure to manage localized disease contributes to the majority of deaths. Radiation therapy (RT) is a common treatment for localized prostate cancer and uses ionizing radiation (IR) to damage DNA. Although RT is potentially curative, tumors often recur and progress to terminal disease. The cellular response to RT is multidimensional. For example, cells respond to a single dose of IR by activating the DNA damage response (DDR) to repair the DNA. Targeting proteins involved in the DDR is an effective clinical strategy to sensitize cancer cells to RT. However, multiple radiation treatments, as in fractionated ionizing radiation (FIR), can promote neuroendocrine differentiation (NED). FIR-induced NED is an emerging resistance mechanism to RT and tumors that undergo NED are highly aggressive and remain incurable.<br><br> Currently, the only clinical approach that improves RT for prostate cancer treatment is androgen deprivation therapy (ADT). ADT blocks androgen receptor (AR) signaling which inhibits the repair of DNA damage. In 2017, my lab reported that targeting Protein arginine methyltransferase 5 (PRMT5) blocks AR protein expression. Therefore, targeting PRMT5 may also sensitize prostate cancer cells to RT via a novel mechanism of action.<br><br> This dissertation focuses on the role of PRMT5 in the cellular response to IR and the goal of my work is to validate PRMT5 as a therapeutic target to enhance RT for prostate cancer treatment. I demonstrate that PRMT5 has several roles in the cellular response to IR. Upon a single dose of IR, PRMT5 cooperates with pICln to function as a master epigenetic activator of DDR genes and efficiently repair IR-induced DNA damage. There is an assumption in the field that the methyltransferase activity and epigenetic function of PRMT5 is dependent on the cofactor MEP50. I demonstrate that PRMT5 can function independently of MEP50 and identify pICln as a novel epigenetic cofactor of PRMT5. During FIR, PRMT5, along with both cofactors MEP50 and pICln, are essential for initiation of NED, maintenance of NED, and cell survival. Targeting PRMT5 also sensitizes prostate cancer xenograft tumors in mice to RT, significantly reduces and delays tumor recurrence, and prolongs overall survival. Incredibly, while 100% of control mice died due to tumor burden, targeting PRMT5 effectively cured ~85% of mice from their xenograft tumor. Overall, this work provides strong evidence for PRMT5 as a therapeutic target and suggests that targeting PRMT5 during RT should be assessed clinically.<br>

Le Cyberknife (Accuray, Sunnyvale, CA) est un appareil de radiochirurgie stéréotaxique sans cadre. Il a été développé pour administrer de fortes doses dans des volumes restreints. Aussi, pour obtenir une conformation optimale de traitement, des champs circulaires de petites dimensions sont utilisés (\phi = 0,5 à 6 cm). L'étude dosimétrique de ces petits champs doit être menée selon de nouveaux standards puisque ceux-ci échappent aux définitions du TG-51. L'objectif de ce projet est d'implanter une plateforme de calcul de dose de type Monte Carlo pour le CyberKnife en clinique. Il s'articule autour de deux réalisations principales. Tout d'abord, une caractérisation dosimétrique du modèle Monte Carlo de l'accélérateur linéaire du CyberKnife a été menée à travers des simulations Monte Carlo générées par le moteur de EGSnrc. Cette étude est basée sur la caractérisation de la réponse d'un détecteur à un champ de type CK à partir de simulations EGS_chamber. Cette approche permet de prendre en compte l'impact du détecteur sur les mesures expérimentales. Cet aspect est d'autant plus important que le modèle Monte Carlo de l'accélérateur est validé à partir de mesures expérimentales. Les résultats obtenus montrent une bonne concordance, <1% ou 1 mm, entre les mesures expérimentales et les données de simulations pour les grands champs. Pour les champs de diamètre < 12,5 mm, le modèle est moins exact et une correction est appliquée pour atteindre une différence de <1% ou 1 mm. Deuxièmement, ce modèle validé du CK a été implanté dans un cadre de calcul Monte Carlo complet. Une plateforme de calcul dédiée aux calculs Monte Carlo, WebTPS, a été adaptée aux calculs de dose CK. Cette plateforme reçoit les données relatives au plan de traitement et lance des calcul EGSnrc sur un superordinateur. Cette approche tend à réduire les approximations lors de l'évaluation dosimétrique de plans de traitements cliniques. Une incertitude inférieure à 1% peut être atteinte en deux heures de calcul. Ce projet a donc pour objectif de développer une référence clinique pour le calcul de dose dans le cadre de la radiochirurgie stéréotaxique. L'outil WebTPS pourrait être particulièrement utile en clinique, l'algorithme de calcul de dose du CK étant limité dans plusieurs situations de traitement. / Purpose: The scope of this study is to implement a clinical Monte Carlo dose calculation system based on the EGSnrc engine. This web-based tool will be mostly used to evaluate clinical treatment plans in highly heterogeneous phantoms. Methods: The Monte Carlo calculation tool is based on the DOSXYZnrc user code. The platform automatically converts CyberKnife clinical plan to the user code input files. Phantoms can be created from HU to ED curves or by manually assigning material using medical contours. Parallel computation is made on a Compute Canada high-performance cluster to reduce simulation time. A Monte Carlo CyberKnife model is built on BEAMnrc user code using the manufacturer specifications. Simulated and experimental data is compared to estimate the electron beam parameters. The beam energy estimation is based on percent depth dose (PDD) comparison while the full width at half max (FWHM) is validated by output factor (OF) and off-axis ratio (OAR). An EGS_chamber model of the PTW60012 diode is used in the OF calculation. A set of phase-spaces is generated from the optimal model and for each collimator to calculate dose contribution from each incident beam. Results: The linac model optimisation yielded a 0.5% PDD agreement between experimental and simulation data, and a 0.5% or 1 mm for OAR. DOSxyz simulation of full treatment plan, based on the preliminary CyberKnife model, were achieved. Total Monte Carlo dose calculation have been achieved for heterogeneous phantoms. Uncertainty under 1% can be achieved for less than 2 hour of computing time. However, computing time estimation is nontrivial due to its dependence on cluster availability. Conclusion: This work aims to develop a suitable tool for reference plan dose calculation. This web-based tool would be used in several clinical and research applications where the CyberKnife embedded ray-tracing algorithm would show significant limitations. Because it is destined to a clinical use, the whole dose calculation system will be rigorously validated. / Le travail de modélisation a été réalisé à travers EGSnrc, un logiciel développé par le Conseil National de Recherche Canada.

Le travail de modélisation a été réalisé à travers EGSnrc, un logiciel développé par le Conseil National de Recherche Canada. / Le Cyberknife (Accuray, Sunnyvale, CA) est un appareil de radiochirurgie stéréotaxique sans cadre. Il a été développé pour administrer de fortes doses dans des volumes restreints. Aussi, pour obtenir une conformation optimale de traitement, des champs circulaires de petites dimensions sont utilisés (\phi = 0,5 à 6 cm). L'étude dosimétrique de ces petits champs doit être menée selon de nouveaux standards puisque ceux-ci échappent aux définitions du TG-51. L'objectif de ce projet est d'implanter une plateforme de calcul de dose de type Monte Carlo pour le CyberKnife en clinique. Il s'articule autour de deux réalisations principales. Tout d'abord, une caractérisation dosimétrique du modèle Monte Carlo de l'accélérateur linéaire du CyberKnife a été menée à travers des simulations Monte Carlo générées par le moteur de EGSnrc. Cette étude est basée sur la caractérisation de la réponse d'un détecteur à un champ de type CK à partir de simulations EGS_chamber. Cette approche permet de prendre en compte l'impact du détecteur sur les mesures expérimentales. Cet aspect est d'autant plus important que le modèle Monte Carlo de l'accélérateur est validé à partir de mesures expérimentales. Les résultats obtenus montrent une bonne concordance, <1% ou 1 mm, entre les mesures expérimentales et les données de simulations pour les grands champs. Pour les champs de diamètre < 12,5 mm, le modèle est moins exact et une correction est appliquée pour atteindre une différence de <1% ou 1 mm. Deuxièmement, ce modèle validé du CK a été implanté dans un cadre de calcul Monte Carlo complet. Une plateforme de calcul dédiée aux calculs Monte Carlo, WebTPS, a été adaptée aux calculs de dose CK. Cette plateforme reçoit les données relatives au plan de traitement et lance des calcul EGSnrc sur un superordinateur. Cette approche tend à réduire les approximations lors de l'évaluation dosimétrique de plans de traitements cliniques. Une incertitude inférieure à 1% peut être atteinte en deux heures de calcul. Ce projet a donc pour objectif de développer une référence clinique pour le calcul de dose dans le cadre de la radiochirurgie stéréotaxique. L'outil WebTPS pourrait être particulièrement utile en clinique, l'algorithme de calcul de dose du CK étant limité dans plusieurs situations de traitement. / Purpose: The scope of this study is to implement a clinical Monte Carlo dose calculation system based on the EGSnrc engine. This web-based tool will be mostly used to evaluate clinical treatment plans in highly heterogeneous phantoms. Methods: The Monte Carlo calculation tool is based on the DOSXYZnrc user code. The platform automatically converts CyberKnife clinical plan to the user code input files. Phantoms can be created from HU to ED curves or by manually assigning material using medical contours. Parallel computation is made on a Compute Canada high-performance cluster to reduce simulation time. A Monte Carlo CyberKnife model is built on BEAMnrc user code using the manufacturer specifications. Simulated and experimental data is compared to estimate the electron beam parameters. The beam energy estimation is based on percent depth dose (PDD) comparison while the full width at half max (FWHM) is validated by output factor (OF) and off-axis ratio (OAR). An EGS_chamber model of the PTW60012 diode is used in the OF calculation. A set of phase-spaces is generated from the optimal model and for each collimator to calculate dose contribution from each incident beam. Results: The linac model optimisation yielded a 0.5% PDD agreement between experimental and simulation data, and a 0.5% or 1 mm for OAR. DOSxyz simulation of full treatment plan, based on the preliminary CyberKnife model, were achieved. Total Monte Carlo dose calculation have been achieved for heterogeneous phantoms. Uncertainty under 1% can be achieved for less than 2 hour of computing time. However, computing time estimation is nontrivial due to its dependence on cluster availability. Conclusion: This work aims to develop a suitable tool for reference plan dose calculation. This web-based tool would be used in several clinical and research applications where the CyberKnife embedded ray-tracing algorithm would show significant limitations. Because it is destined to a clinical use, the whole dose calculation system will be rigorously validated.

Le Carcinome Hépatocellulaire a une incidence mondiale élevée et est associé à un mauvais pronostic. Les traitements curatifs existants ne sont applicables qu’à une minorité de patients. La radiothérapie sélective interne (SIRT) est un traitement palliatif de plus en plus utilisé. Elle consiste à l’injection sélective intra-tumorale de microsphères d’yttrium-90 par infusion intra-artérielle, et repose sur deux étapes : une étape pré-thérapeutique de simulation du traitement avec l’injection de macroagrégats d’albumines marqués au 99mTc et le traitement en lui-même. Cependant les caractéristiques de ces deux vecteurs diffèrent et peuvent conduire à des variations de biodistribution et à une dosimétrie approximative. Ce travail a pour but de développer un vecteur radiothéranostique unique pour la SIRT : les microparticules à base d’amidon (SBMP), afin de pallier aux différents problèmes rencontrés en clinique. L’optimisation du radiomarquage par le 68Ga et le 188Re sous forme de kits lyophilisés prêts-à-l’emploi, a permis d’obtenir une pureté radiochimique > 98 % et > 95 % respectivement. Une étude préliminaire par imagerie TEP/TDM in vivo chez le rat, suite à l’injection intraartérielle des 68Ga-SBMP a montré une biodistribution spécifique des microparticules avec plus de 95 % de l’activité retrouvée dans le foie et plus particulièrement dans les tumeurs. Les SBMP offrent plusieurs avantages répondant à différents problèmes actuels et constituent un agent théranostique prometteur pour la SIRT. Une présentation de la SIRT, des différentes microparticules en développement pour la SIRT et des modèles animaux de tumeur hépatique existants seront également développées dans ce travail. / The Hepatocellular Carcinoma has a high incidence worldwide and is associated with a bad prognostic. The existing curative treatments can only be apply in a minority of cases. The selective internal radiation therapy (SIRT) is a palliative treatment that is increasingly used. This technique is define by the selective intratumoral injection of yttrium-90microspheres via intra-arterial infusion. It involves two steps : a pre-therapeutic one for treatment simulation purpose with the injection of serum albumin macroaggregates radiolabeled with 99mTc and the treatment itself. However the characteristics of these two vectors are different and can lead to variations in biodistribution and approximate dosimetry. This works aims to develop a unique radiotheranostic vector for the SIRT: the starch-basedmicroparticles (SBMP), in order to overcome the different currents clinical problems. The optimization of the radiolabeling by the 68Ga and the 188Re in the form of ready-to-use radiolabeling kits allowed to obtain a radiochemical purity > 98 % and > 95 % respectively. A preliminary in vivo study by PET/CT imaging in rat, following the intra-arterial injection of 68Ga-SBMP displayed a specific biodistribution of the microparticles with more than 95 % of the activity found in the liver and mostly in the tumors. The SBMP offer several advantages that answer different current issues and area promising theranostic agent for the SIRT. A presentation of the SIRT, the different microparticles in development and the existing animal models of hepatic tumor will also be developed in this work.

No description available.