QUANTITATIVE METHODS FOR ANALYSIS OF TSPO AVAILABILITY IN PROGRESSIVE MULTIPLE SCLEROSIS, USING BRAIN PET IMAGING WITH RADIOLIGAND 11C-PBR28

Background – The translocator protein 18kDA (TSPO) is closely related to diffuse inflammatory demyelinating injury and hence represents an ideal target for brain imaging in progressive-MS pathology in vivo. However, quantification of the TSPO is associated with number of challenges corresponding to its genetic polymorphism and localization in the CNS and surroundings. Subsequent inaccuracy in TSPO quantification with plasma concentration or anatomical brain reference region proposes for implementation of alternative quantification approaches that are hypothesized to compensate the shortcomings. Objectives – This study has tried to perform a comparative evaluation of novel quantification approaches for analyzing neuroinflammation using 11C-PBR28 tracer in MR-PET brain imaging of the patients with SPMS versus healthy control participants. Methods – Nine secondary progressive MS and 11 healthy controls have been examined in 3Tesla MR and (11C-PBR28) PET brain imaging in Turku PET Centre (TPC). Brain segmentation and image preprocessing were fulfilled using Freesurfer v.5.3 and SPM12 toolset in MATLAB. Lesion and ROIs delineation was performed via in house software. Tracer binding activity was measured, and volume of distribution was quantified via 2TCM compartmental model. Four brain reference regions were considered for normalization of the values, consisted of three anatomical reference regions in addition to one supervised clustering pseudo-references modified version of the algorithm developed in the Harvard university for similar aim. Results – The results of this study obtained via examination of several kinetic models, data and partial volume correction steps aimed at narrowing down the selected approaches and accounting the apparently most robust method for the higher-level analysis and the statistical examination. However, through neither of the steps any result represented a significant support for the H1 hypothesis in this study. The low signal to noise ratio of the PET imaging data with the utilized radioligand and the diffusivity of the TSPO in the MS brain, along with the complexity of quantification caused by the polymorphism genotype and the affinity binding of the radiotracer in MS brains and blood plasma are the greatest obstacles challenging the analysis of the PET-MR imaging data in the pathological studies of the MS in vivo

Imaging Neuroinflammation in Progressive Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system CNS), where inflammation and neurodegeneration lead to irreversible neuronal damage. In MS, a dysfunctional immune system causes auto‐reactive lymphocytes to migrate into CNS where they initiate an inflammatory cascade leading to focal demyelination, axonal degeneration and neuronal loss. One of the hallmarks of neuronal injury and neuroinflammation is the activation of microglia. Activated microglia are found not only in the focal inflammatory lesions, but also diffusely in the normal‐appearing white matter (NAWM), especially in progressive MS. The purine base, adenosine is a ubiquitous neuromodulator in the CNS and also participates in the regulation of inflammation. The effect of adenosine mediated via adenosine A2A receptors has been linked to microglial activation, whereas modulating A2A receptors may exert neuroprotective effects. In the majority of patients, MS presents with a relapsing disease course, later advancing to a progressive phase characterised by a worsening, irreversible disability. Disease modifying treatments can reduce the severity and progression in relapsing MS, but no efficient treatment exists for progressive MS. The aim of this research was to investigate the prevalence of adenosine A2A receptors and activated microglia in progressive MS by using in vivo positron emission tomography (PET) imaging and [11C]TMSX and [11C](R)‐PK11195 radioligands. Magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI) was performed to evaluate structural brain damage. Non‐invasive input function methods were also developed for the analyses of [11C]TMSX PET data. Finally, histopathological correlates of [11C](R)‐PK11195 radioligand binding related to chronic MS lesions were investigated in post‐mortem samples of progressive MS brain using autoradiography and immunohistochemistry. [11C]TMSX binding to A2A receptors was increased in NAWM of secondary progressive MS (SPMS) patients when compared to healthy controls, and this correlated to more severe atrophy in MRI and white matter disintegration (reduced fractional anisotropy, FA) in DTI. The non‐invasive input function methods appeared as feasible options for brain [11C]TMSX images obviating arterial blood sampling. [11C](R)‐PK11195 uptake was increased in the NAWM of SPMS patients when compared to patients with relapsing MS and healthy controls. Higher [11C](R)‐PK11195 binding in NAWM and total perilesional area of T1 hypointense lesions was associated with more severe clinical disability, increased brain atrophy, higher lesion load and reduced FA in NAWM in the MS patients. In autoradiography, increased perilesional [11C](R)‐PK11195 uptake was associated with increased microglial activation identified using immunohistochemistry. In conclusion, brain [11C]TMSX PET imaging holds promise in the evaluation of diffuse neuroinflammation in progressive MS. Being a marker of microglial activation, [11C](R)‐ PK11195 PET imaging could possibly be used as a surrogate biomarker in the evaluation of the neuroinflammatory burden and clinical disease severity in progressive MS.Siirretty Doriast

A non compartmental method for functional quantitative imaging with Positron Emission Tomography and irreversible tracers

In dynamic Positron Emission Tomography (PET) studies the term "Spectral Analysis" indicates a time-invariant single input/single output model, used for the data quantification [Cunningham and Jones, 1993]. Despite the name and its common use in the engineering field, SA does not indicate an analysis in the frequency domain but, instead, it represents a method from which the radioactivity concentration measured with PET can be related to the underlying physiological processes of the investigated system. SA is so-called, because it provides a “spectrum” of the kinetic components from which it is possible to derive a large variety of physiological parameters, depending on the characteristics of the analyzed tracers. In the last years SA has been widely used with a large number of PET tracers to study brain and non brain tissues, demonstrating to be a very flexible method. Differently from the most used PET quantification approaches, like the compartmental modelling [Godfrey, 1982] or the graphical methods [Patlak, 1983; Logan et al., 1990], SA can be applied to homogeneous as well as to heterogeneous kinetic tissues without any specific compartmental model assumptions. This characteristic makes it a high informative investigative tool especially for the analysis of novel PET tracers. The most critical aspect of SA is related to its sensitivity to the presence of noise in the data. This characteristic makes SA not properly indicated for the application to low signal-to-noise ratio (SNR) data [Turkheimer et al., 1994]. During the past several years, several solutions have been introduced to improve the robustness of SA in the presence of noise. The most famous example is represented by rank-shaping spectral analysis (RS) [Turkheimer et al., 2003]. However, even if RS has been shown to be a precise and accurate quantification method, its applicability is limited to tracers with reversible uptake. This is a severe restriction if we consider that one of the most used PET tracer for clinical research, 18F-Fluorodeoxyglucose ([18F]FDG), is irreversible. In this work we present SAIF, (Spectral Analysis with Iterative Filter), a SA-based method for the quantification of PET data investigated with irreversible-uptake tracers. SAIF has been designed in order to maintain the main advantages of SA but providing a superior robustness to measurement noise. The final aim was to create a reliable and flexible PET quantification tool, offering a valid alternative to standard methodologies for functional quantitative imaging with PET and irreversible tracers. The organization of this thesis is as follows: Chapter 1 offers a brief introduction to PET technique and its quantification methods. A comparison between compartmental modelling approaches and graphical methods is also presented, in order to provide the operative context in which SA is located. Chapter 2 contains the mathematical formalization of the SA model. Standard and filtered SA versions are presented with particular attention to novelty elements introduced by SAIF. In Chapter 3 and Chapter 4, SAIF will be tested with brain and non brain PET data. Several datasets obtained by using different PET tracers are considered. As an example for brain tissue quantification, SAIF application to L-[1-11C]Leucine and [11C]SCH442416 data is presented. For non brain tissues, instead, analysis of three datasets is reported: 1) [18F]FDG PET studies applied to skeletal leg muscle, 2) [18F]FLT PET studies applied to breast cancer patients and 3) [18F]FDG PET studies applied to normal control and acute lung injury patients. For each dataset SAIF results are compared with those provided by already validated methods and used in the literature as reference for the quantification. This analysis allows to compare SAIF performances with those offered by the current state of the art. Chapter 5 investigates the conditioning of the kinetic heterogeneity to PET quantification. The relationship between this problem, the spatial resolution of the imaging technique and the noise level of the data is also considered. This aspect is a critical point for PET quantification because when it is not taken into account it can lead to heavily biased results. Particular attention is given to how SAIF addresses this issue. In Chapter 6 we present SAKE, a software application in-house developed which implements the major SA algorithms. SAKE manages the whole process of PET quantification: from data pre–processing to the result analysis. No other program or additional tool is required. Chapter 7 discusses the most relevant criticalities of the SA approach and of SAIF method in particular. Considerable attention is given to the definition of the setting algorithm as well as to the model assumptions used by SAIF to describe the data. In Chapter 8 an overall discussion is presented with a conclusive summary about strengths and weakness of SAIF method. The appendix of the thesis is dedicated to the some additional works, not directly related to the main argument of this PhD project, but of interest for the PET field. This research concerns 1) the development of voxelwise quantification methods for [11C](R)Rolipram PET data, 2)the use of non linear mixed effects modelling for plasma metabolite correction, and 3) the evaluation of the sensitivity of PET receptor occupancy studies to the experimental design

Exploiting MRI information for improved kinetic modelling of dynamic PET data

Kinetic analysis of dynamic PET data requires an accurate estimation of the concen- tration of the available tracer in blood plasma, also known as the arterial input function (AIF). The gold standard method to determine the AIF involves serial blood sampling and is avoided in practice due to its invasiveness. An image derived input function (IDIF) can be a blood-free alternative but its accuracy is limited due to partial volume (PV) effects caused by the restricted spatial resolution of PET scanners. Furthermore, IDIFs are not accurate when metabolite products are present in the blood. Magnetic resonance imaging (MRI) can provide complementary information to PET with high spatial resolution and excellent soft tissue contrast. Furthermore, dynamic MRI techniques can be reliably used to measure the AIF, the concentration of contrast agent in plasma, due to their high temporal resolution. The underlying aim of this research is to improve IDIF estimation in PET, utilising spatial and temporal information from MRI. An IDIF measurement method was developed which involves segmentation of carotid arteries from MR angiography images and uses a practical PVC method to correct for PV effects. It was demonstrated that the IDIFs can be used to compute the cerebral metabolic rate of glucose in the brain with no significant difference compared to arterial sampling. The simultaneous estimation method (SIME) is an alternative technique used to estimate the AIF by fitting time activity curves derived from multiple regions. Due to its computational complexity, SIME is usually complemented with blood samples. In this work, we observed that the early part of an image derived blood curve or an MRI derived AIF could provide prior knowledge regarding the AIF. This was incorporated into SIME to make more accurate kinetic parameter estimations and to perform blood-free analysis of tracers with metabolites

Imaging p-glycoprotein function: prediction of treatment response in mesial temporal lobe epilepsy

Background: Overexpression of multidrug efflux transporters at the blood–brain barrier, such as P-glycoprotein (Pgp), might contribute to pharmacoresistance by reducing target-site concentrations of antiepileptic drugs (AEDs). We assessed Pgp activity in vivo in patients with mesial temporal lobe epilepsy (mTLE). / Methods: Fourteen pharmacoresistant mTLE patients with unilateral hippocampal sclerosis (HS), three patients with pharmacoresistant epilepsy due to focal cortical dysplasia (FCD), eight seizure-free mTLE patients and 13 healthy controls underwent baseline PET scans with the Pgp substrate (R)- [¹¹C]verapami (VPM). Pharmacoresistant mTLE patients and healthy controls underwent a second VPM PET scan following infusion of the Pgp-inhibitor tariquidar (TQD). The transfer rate constant from plasma to brain, K1, was estimated using a single-tissue compartment model with a VPM-in-plasma arterial input function. Analysis was performed on the first 10min of dynamic data containing limited radiolabeled metabolites. Regions were defined automatically using a brain atlas (ROI analysis), and ratios of VPM-K1 values were calculated between a reference region (parietal cortex) and target regions. Parametric maps of VPM-K1 were also generated using generalised linear least squares and was used for SPM voxel-based analysis. For the voxel-based analysis at baseline we created VPM PET images corrected for differences in whole brain radiotracer uptake. Furthermore, we compared VPM PET scans with epileptic tissues removed during epilepsy surgery and measured peripheral markers of Pgp function: PBMC ABCB1 mRNA, ABCB1 polymorphism and S100B. / Findings: The ROI analysis revealed differences in VPM metabolism between mTLE patients and healthy controls which is caused by AED-mediated hepatic cytochrome P450 enzyme induction in mTLE patients requiring images to be normalised for global brain differences. When using ROI analysis and normalised VPM ratios there was no difference in VPM-K1 ratios in pharmacoresistant compared to seizure-free mTLE patients or healthy controls. The ROI analysis after partial Pgp-inhibition with TQD showed attenuated global increases of VPM brain uptake in pharmacoresistant mTLE patients compared to healthy controls but there where no regional differences. The voxel-based analysis at baseline revealed that pharmacoresistant mTLE patients had reduced VPM uptake compared to seizure-free mTLE patients and healthy controls in ipsi- and contralateral temporal lobes. Higher Pgp activity was associated with higher seizure frequency. After Pgp-inhibition with TQD pharmacoresistant mTLE patients had reduced increases of VPM brain uptake in the whole brain and ipsilateral hippocampus, implicating Pgp overactivity in the epileptogenic hippocampus. The difference in percentage change in VPM brain uptake after Pgp-inhibition with TQD inversely correlated with the difference in percentage area of Pgp immunopositive labeling in pharmacoresistant mTLE patients who underwent epilepsy surgery. Pharmacoresistant epilepsy patients with FCD had reduced VPM brain uptake in close proximity to the area of FCD but also extending to other ipsilateral regions. There were no differences in peripheral markers of Pgp function between the three groups. Our results support the hypothesis of Pgp overactivity in pharmacoresistant epilepsy

Paramètres de conception optimaux pour maximiser le rapport contraste à bruit pour scanners TEP avec temps de vol

Abstract : Time-of-flight (TOF) positron emission tomography (PET) scanners improve contrast-tonoise ratio (CNR) that translates into reducing the scan time or the required injected dose. During the past years, TOF PET has evolved towards temporal resolutions of the order of 200 ps, corresponding to a spatial uncertainty of 30 mm along the line of response (LOR) defined by the two annihilation photons. Although this location uncertainty is sufficient to improve the effective sensitivity of clinical scanners, resolving small size tissues such as a lymph node, or small animal organs would require the timing performance to be less than 50 ps to resolve objects smaller than ⇠ 10 mm. A coincidence time resolution around 10 ps would even allow to avoid tomographic reconstruction of PET images. Obtaining good image performance in PET demands tackling simultaneously all image quality parameters, including spatial resolution, sensitivity, and CNR. However, this involves difficult trade-offs as studies have demonstrated that choices made at the design level for the detector configuration may enhance some image quality parameters but are then detrimental to others. It is therefore mandatory to identify and carefully investigate the factors contributing to the CNR, one of the most important parameter for image quality. One such factor is the choice of crystal thickness that affects coincidence time resolution and thus CNR. Although improved coincidence time resolution increases the chance of small lesion detectability, trade-offs should be studied to find an optimum compromise maximizing the image performance. The motivation underlying this research is to determine the limit where TOF adds gain in small animal PET imaging and also investigate trade-offs between crystal length, timing resolution, and sensitivity to find the optimum image quality. These trade-offs target the coincidence time resolution improvement to enhance CNR performance without compromising the other parameters of image quality. It is demonstrated that a coincidence time resolution of 100 ps is the threshold where TOF starts to improve the image performance of a small animal scanner. In addition, it is shown that the crystal thickness can be reduced by 19 % without loss on the imaging performance. A model is also proposed that describes the CNR performance with a relatively high level of confidence at early stages of the design, and can be used as a guide to design the future generation of scanners. This is followed by introducing a new phantom purposely designed to study TOF benefits and impacts on lesion detectability for PET scanners.Les scanners de tomographie d’émission par positrons (TEP) par temps de vol (TdV) augmentent le rapport contraste à bruit (RCB) en réduisant le bruit de fond. Ceci se traduit par un temps d’acquisition plus court ou une dose réduite. Au cours des années, la TEP-TdV a évolué vers des résolutions temporelles de l’ordre de 200 ps, ce qui correspond à une incertitude spatiale de 30 mm. Bien que cela soit suffisant pour améliorer la sensibilité effective des scanners cliniques, résoudre des petites structures comme les ganglions lymphatiques, ou des organes de petits animaux nécessite des résolutions temporelles inférieures à 50 ps pour résoudre un objet inférieur à ∼ 10 mm. Une résolution temporelle de 10 mm permettrait même d’éviter la reconstruction tomographique des images TEP. L’obtention d’une bonne performance d’image en TEP nécessite d’aborder simultanément tous les paramètres de qualité d’image, y compris la résolution spatiale, la sensibilité et le RCB. Cependant, il est peu probable que cela se produise, car des études ont démontré que les choix de conception du détecteur peuvent favoriser certains paramètres de qualité d’image, mais en dégrader d’autres. On doit donc cibler les facteurs contribuant au RCB, l’un des paramètres importants de la qualité d’image. Un de ces facteurs est le choix de l’épaisseur du cristal qui affecte la résolution temporelle et donc, le RCB. Bien qu’une résolution temporelle améliorée augmente la détectabilité des petites lésions, on doit étudier les compromis afin de trouver un point d’équilibre offrant à la meilleure performance d’image possible. La motivation de cette recherche est de déterminer la limite à partir de laquelle le TdV améliore la qualité de l’imagerie des petits animaux et également, d’étudier les compromis nécessaires entre la longueur des cristaux, la résolution temporelle et la sensibilité pour atteindre la qualité d’image optimale. Ces compromis ciblent l’amélioration de la résolution temporelle pour améliorer les performances du RCB sans compromettre les autres paramètres de qualité d’image. Ces travaux démontrent qu’une résolution temporelle de 100 ps est le seuil à partir duquel le TdV améliore le performance RBC de l’imagerie des petits animaux. De plus, ils montrent que le volume du cristal peut être réduit de 19 % sans détériorer l’image. Un modèle est également proposé pour prédire le RCB avec un niveau de confiance relativement élevé et il peut être utilisé comme guide pour concevoir la prochaine génération de scanners. L’introduction d’une nouvelle mire élaborée pour étudier les avantages et les impacts du TdV sur la détectabilité des lésions pour les scanners TdV est par la suite présentée

Improved Quantitative Methods for Multiple Neuropharmacological Non-Invasive Brain PET Studies.

Positron emission tomography (PET) is a medical imaging modality offering a powerful tool for brain research by mapping of in vivo neuropharmacological functions such as metabolism, enzyme activity, and neuroreceptor binding site density and occupancy. Quantification in brain-PET can be classified into: 1) accurate quantification of radiotracer distribution such that image values are proportional to the radiotracer concentration in tissue, and 2) accurate quantification of the pharmacological state of the system-of-interest. This thesis addresses both these aspects for functional neuroreceptor imaging studies of the living brain. Traditional brain PET studies have at least two primary limitations. First, they measure only a single neuropharmacological aspect in isolation, which is often insufficient for characterizing a neurological condition. Second, data acquisition is accompanied by the invasive arterial blood sampling for measuring the input function to the system-of-interest. The motivation for this thesis was to address both these limitations, which led to the development of quantitative methods for multiple neuropharmacological PET studies performed without blood sampling. One such experimental design investigated was a dual-measurement intervention study where the system-of-interest is perturbed with the intent of changing the subject’s pharmacological status and system parameters are estimated both pre- and post-intervention. Second was a dual-tracer study where two radiotracers targeting two different neuropharmacological systems were injected closely in time in the same study. A major challenge in analyzing multiple pharmacological PET studies is the statistical noise-induced bias and variance in the parameter estimates. Methods developed in this thesis reduced almost all the bias (>90%) in the intervention studies with a corresponding improvement in precision. Parameter estimates for dual-tracer studies were obtained with inter-subject regions-of-interest means within ±10% of those obtained from single-tracer scans without appreciable increase in variance. The thesis also addresses inter-scanner PET image variability, a major confound in multi-center studies used to investigate disease progression. Since various PET centers have scanners with different hardware and software, systematic differences exist in multi-center data. This thesis develops a framework to reduce the inter-scanner PET image variability before pooling multi-center data for analysis. The methods developed reduced variability in phantom scans from different sites by approximately 50%.Ph.D.Biomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61729/1/adjoshi_1.pd

Small animal PET imaging using GATE Monte Carlo simulations : Implementation of physiological and metabolic information

Tese de doutoramento, (Engenharia Biomédica e Biofísica), Universidade de Lisboa, Faculdade de Ciências, 2010O rato/ratinho de laboratório é o modelo animal de escolha para o estudo dos processos fundamentais associados a determinadas patologias, como o cancro. Esta escolha deve-se a uma gama de factores que incluem uma grande homologia genética com o Homem. Assim sendo o rato/ratinho é amplamente utilizado em laboratórios por todo o Mundo para estudo dos processos celulares básicos associados á doença e à terapia. A comunidade laboratorial tem, nos últimos anos, desenvolvido um grande interesse pela imagiologia não-invasiva destes animais. De entre as diversas tecnologias de imagem aplicadas aos estudosin vivo de pequenos animais, a Tomografia por Emissão de Positrões (PET) permite obter informação sobre a distribuição espacial e temporal de moléculas marcadas com átomo emissor de positrões, de forma não invasiva. Os traçadores utilizados para obter esta “imagem molecular” são administrados em baixas quantidades, de tal forma que os processos biológicos que envolvem concentrações da ordem do nano molar, ou mesmo inferiores, podem ser determinadas sem perturbar o processo em estudo. Muitas combinações de diferentes moléculas com diferentes radionúclidos permitem traçar uma gama de caminhos moleculares específicos (e.g. processos biológicos de receptores e síntese de transmissores em caminhos de comunicação em células, processos metabólicos e expressão genética). A imagem pode ser executada repetidamente antes e depois de intervenções permitindo o uso de cada animal como o seu próprio controlo biológico. A investigação já realizada em curso que aplicam a PET ao estudos de pequenos animais, tem permitido compreender, entre outras coisas, a evolução de determinadas doenças e suas potenciais terapias. Contudo, existem algumas dificuldades de implementação desta técnica já que a informação obtida está condicionada pelos fenómenos físicos associados à interacção da radiação com a matéria, pelos instrumentos envolvidos na obtenção da informação e pela própria fisiologia do animal (por exemplo o seu movimento fisiológico). De facto, a fiabilidade da quantificação das imagens obtidas experimentalmente, em sistemas PET dedicados aos pequenos animais, é afectada ao mesmo tempo pelos limites de desempenho dos detectores (resolução espacial e em energia, sensibilidade, etc.), os efeitos físicos como a atenuação e a dispersão, que perturbam a reconstrução da imagem, e os efeitos fisiológicos (movimentos do animal). Na prática estes efeitos são corrigidos com métodos de correcção específicos com a finalidade de extrair parâmetros quantitativos fiáveis. Por outro lado, as características fisiológicas dos animais a estudar e a necessidade da existência de animais disponíveis, são factores adicionais de complexidade. Recentemente, tem sido dedicada alguma atenção aos efeitos resultantes dos movimentos fisiológicos, nomeadamente do movimento respiratório, na qualidade das imagens obtidas no decurso de um exame PET. Em particular, no caso do estudo dos tumores do pulmão (algo infelizmente muito frequente em humanos), o movimento fisiológico dos pulmões é uma fonte de degradação das imagens PET, podendo comprometer a sua resolução e o contraste entre regiões sãs e doentes deste orgão. A precisão quantitativa na determinação da concentração de actividade e dos volumes funcionais fica assim debilitada, sendo por vezes impedida a localização, detecção e quantificação do radiotraçador captado nas lesões pulmonares. De modo a conseguir diminuir estes efeitos, existe a necessidade de melhor compreender a influência deste movimento nos resultados PET. Neste contexto, as simulações Monte Carlo são um instrumento útil e eficaz de ajuda à optimização dos componentes dos detectores existentes, à concepção de novos detectores, ao desenvolviBaseados em modelos matemáticos dos processos físicos, químicos e, sempre que possível, biológicos, os métodos de simulação Monte Carlo são, desde há muito, uma ferramenta privilegiada para a obtenção de informação fiável da previsão do comportamento de sistemas complexos e por maioria de razão, para uma sua melhor compreensão. No contexto da Imagiologia Molecular, a plataforma de simulação Geant4 Application for Tomographic Emission (GATE), validada para as técnicas de imagem de Medicina Nuclear, permite a simulação por Monte Carlo dos processos de obtenção de imagem. Esta simulação pode mesmo ser feita quando se pretende estudar a distribuição de emissores de positrões cuja localização varia ao longo do tempo. Adicionalmente, estas plataformas permitem a utilização de modelos computacionais para modelar a anatomia e a fisiologia dos organismos em estudo mediante a utilização de uma sua representação digital realista denominada de fantôma. A grande vantagem na utilização destes fantômas relaciona-se com o facto de conhecermos as suas características geométricas (“anatómicas”) e de podermos controlar as suas características funcionais (“fisiológicas”). Podemos assim obter padrões a partir dos quais podemos avaliar e aumentar a qualidade dos equipamentos e técnicas de imagem. O objectivo do presente trabalho consiste na modelação e validação de uma plataforma de simulação do sistema microPET® FOCUS 220, usado em estudos de PET para pequenos animais, utilizando a plataforma de simulação GATE. A metodologia adoptada procurou reproduzir de uma forma realista, o ambiente de radiação e factores instrumentais relacionados com o sistema de imagem, assim como o formato digital dos dados produzidos pelo equipamento. Foram usados modelos computacionais, obtidos por segmentação de imagem de exames reais, para a avaliação da quantificação das imagens obtidas. Os resultados obtidos indicam que a plataforma produz resultados reprodutíveis, adequados para a sua utilização de estudos de pequenos animais em PET. Este objectivo foi concretizado estudando os efeitos combinados do tamanho das lesões, do rácio de concentração de actividade lesão-para-fundo e do movimento respiratório na recuperação de sinal de lesões esféricas localizadas no pulmão em imagens PET de pequenos animais. Para este efeito, foi implementada no código GATE uma representação digital em 4D de um ratinho de corpo inteiro (o fantôma MOBY). O MOBY permitiu reproduzir uma condição fisiológica que representa a respiração em condição de "stress", durante um exame típico de PET pequeno animal, e a inclusão de uma lesão esférica no pulmão tendo em conta o movimento da mesma. Foram realizadas um conjunto de simulações estáticas e dinâmicas usando 2-Deoxy-[18F]fluoro-D-glucose (FDG) tendo em consideração diferentes tamanhos das lesões e diferentes captações deste radiofármaco. O ruído da imagem e a resolução temporal foram determinadas usando imagens 3D e 4D. O rácio sínal-para-ruído (SNR), o rácio contraste-para-ruído (CNR), a relação lesão-fundo (target-to-background activity concentration ratio- TBR), a recuperação de contraste (CR) e a recuperação de volume (VR) foram também avaliados em função do tamanho da lesão e da actividade captada. Globalmente, os resultados obtidos demonstram que a perda de sinal depende tanto do tamanho da lesão como da captação de actividade na lesão. Nas simulações estáticas, onde não foi simulado movimento, os coeficientes de recuperação foram influenciados pelo efeito de volume parcial para os tamanhos mais reduzidos de lesão. Além disso, o aumento do contraste na lesão produz um aumento significativo no desvio padrão da média de sinal recuperado resultando numa diminuição no CNR e no SNR. Também concluímos que o movimento respiratório diminui significativamente a recuperação do sinal e que esta perda depende principalmente do tamanho da lesão. A melhor resolução temporal e resolução espacial foram obtidas nas simulações estáticas, onde não existia movimento envolvido. Os resultados simulados mostram que o efeito de volume parcial é dominante nas lesões mais pequenas devido à resolução espacial do sistema FOCUS, tanto nas imagens estáticas como nas dinâmicas. Além disso, para concentrações baixas de radiofármaco existe uma dificuldade inerente em quantificar a recuperação de sinal nas lesões comprometendo a análise quantitativa dos dados obtidos.Organ motion has become of great concern in medical imaging only recently. Respiratory motion is one source of degradation of PET images. Respiratory motion may lead to image blurring, which may result in reduced contrast and quantitative accuracy in terms of recovered activity concentration and functional volumes. Consequently, the motion of lungs hinders the localization, detection, and the quantification of tracer uptake in lung lesions. There is, therefore, a need to better understand the effects of this motion on PET data outcome. Medical imaging methods and devices are commonly evaluated through computer simulation. Computer generated phantoms are used to model patient anatomy and physiology, as well as the imaging process itself. A major advantage of using computer generated phantoms in simulation studies is that the anatomy and physiological functions of the phantom are known, thus providing a gold standard from which to evaluate and improve medical imaging devices and techniques. In this thesis, are presented the results of a research studied the combined effects of lesion size, lesion-to-background activity concentration ratio and respiratory motion on signal recovery of spherical lesions in small animal PET images using Monte Carlo simulation. Moreover, background activity is unavoidable and it causes significant noise and contrast loss in PET images. For these purposes, has been used the Geant4 Application for Tomographic Emission (GATE) Monte Carlo platform to model the microPET®FOCUS 220 system. Additionaly, was implemented the digital 4D Mouse Whole-Body (MOBY) phantom into GATE. A physiological “stress breathing” condition was created for MOBY in order to reproduce the respiratory mouse motion during a typical PET examination. A spherical lung lesion was implemented within this phantom and its motion also modelled. Over a complete respiratory cycle of 0.37 s was retrieved a set of 10 temporal frames (including the lesion movement) generated in addition to a non-gated data set. Sets of static (non-gated data) and dynamic (gated data) 2-Deoxy-[18F]fluoro-D-glucose (FDG) simulations were performed considering different lesion sizes and different activity uptakes. Image noise and temporal resolution were determined on 3D and 4D images. Signal-to-Noise Ratio (SNR), Contrast-to-Noise Ratio (CNR), Target-to-Background activity concentration Ratio (TBR), Contrast Recovery (CR) and Volume Recovery (VR) were also evaluated as a function of lesion size and activity uptake. Globally, the results obtained show that signal loss depends both on lesion size and lesion activity uptake. In the non-gated data, where was no motion included (perfect motion correction), the recovery coefficients were influenced by the partial volume effect for the smallest lesion size. Moreover, the increased lesion contrast produces a significant increase on the standard deviation of the mean signal recover. This led to a decrease in CNR and SNR. In addition, respiratory motion significantly deteriorates signal recovery and this loss depends mainly of the lesion size. Best temporal resolution (volume recovery) and spatial resolution was given by the non-gated data, where no motion is involved. The simulated results show that the partial volume effect is dominant for small objects due to limited FOCUS system resolution in both 3D and 4D PET images. In addition, lower activity concentrations significantly deteriorates the lesion signal recovery compromising quantitative analysis.Fundação para a Ciência e a Tecnologia (FCT) under grant nº SFRH/BD/22723/200