Simulation of Clinical PET Studies for the Assessment of Quantification Methods

On this PhD thesis we developed a methodology for evaluating the robustness of SUV measurements based on MC simulations and the generation of novel databases of simulated studies based on digital anthropomorphic phantoms. This methodology has been applied to different problems related to quantification that were not previously addressed. Two methods for estimating the extravasated dose were proposed andvalidated in different scenarios using MC simulations. We studied the impact of noise and low counting in the accuracy and repeatability of three commonly used SUV metrics (SUVmax, SUVmean and SUV50). The same model was used to study the effect of physiological muscular uptake variations on the quantification of FDG-PET studies. Finally, our MC models were applied to simulate 18F-fluorocholine (FCH) studies. The aim was to study the effect of spill-in counts from neighbouring regions on the quantification of small regions close to high activity extended sources

Objective Assessment of Image Quality: Extension of Numerical Observer Models to Multidimensional Medical Imaging Studies

Encompassing with fields on engineering and medical image quality, this dissertation proposes a novel framework for diagnostic performance evaluation based on objective image-quality assessment, an important step in the development of new imaging devices, acquisitions, or image-processing techniques being used for clinicians and researchers. The objective of this dissertation is to develop computational modeling tools that allow comprehensive evaluation of task-based assessment including clinical interpretation of images regardless of image dimensionality. Because of advances in the development of medical imaging devices, several techniques have improved image quality where the format domain of the outcome images becomes multidimensional (e.g., 3D+time or 4D). To evaluate the performance of new imaging devices or to optimize various design parameters and algorithms, the quality measurement should be performed using an appropriate image-quality figure-of-merit (FOM). Classical FOM such as bias and variance, or mean-square error, have been broadly used in the past. Unfortunately, they do not reflect the fact that the average performance of the principal agent in medical decision-making is frequently a human observer, nor are they aware of the specific diagnostic task. The standard goal for image quality assessment is a task-based approach in which one evaluates human observer performance of a specified diagnostic task (e.g. detection of the presence of lesions). However, having a human observer performs the tasks is costly and time-consuming. To facilitate practical task-based assessment of image quality, a numerical observer is required as a surrogate for human observers. Previously, numerical observers for the detection task have been studied both in research and industry; however, little research effort has been devoted toward development of one utilized for multidimensional imaging studies (e.g., 4D). Limiting the numerical observer tools that accommodate all information embedded in a series of images, the performance assessment of a particular new technique that generates multidimensional data is complex and limited. Consequently, key questions remain unanswered about how much the image quality improved using these new multidimensional images on a specific clinical task. To address this gap, this dissertation proposes a new numerical-observer methodology to assess the improvement achieved from newly developed imaging technologies. This numerical observer approach can be generalized to exploit pertinent statistical information in multidimensional images and accurately predict the performance of a human observer over the complexity of the image domains. Part I of this dissertation aims to develop a numerical observer that accommodates multidimensional images to process correlated signal components and appropriately incorporate them into an absolute FOM. Part II of this dissertation aims to apply the model developed in Part I to selected clinical applications with multidimensional images including: 1) respiratory-gated positron emission tomography (PET) in lung cancer (3D+t), 2) kinetic parametric PET in head-and-neck cancer (3D+k), and 3) spectral computed tomography (CT) in atherosclerotic plaque (3D+e). The author compares the task-based performance of the proposed approach to that of conventional methods, evaluated based on a broadly-used signal-known-exactly /background-known-exactly paradigm, which is in the context of the specified properties of a target object (e.g., a lesion) on highly realistic and clinical backgrounds. A realistic target object is generated with specific properties and applied to a set of images to create pathological scenarios for the performance evaluation, e.g., lesions in the lungs or plaques in the artery. The regions of interest (ROIs) of the target objects are formed over an ensemble of data measurements under identical conditions and evaluated for the inclusion of useful information from different complex domains (i.e., 3D+t, 3D+k, 3D+e). This work provides an image-quality assessment metric with no dimensional limitation that could help substantially improve assessment of performance achieved from new developments in imaging that make use of high dimensional data

Development and assessment of estimate methods for internal dosimetry using PET/CT

The aim of this thesis was to assess and develop internal dose calculations methods in diagnostic and therapeutic nuclear medicine procedures to patients undergone PET/CT explorations. Towards this objective, the accuracy and precision of different classical methods commonly used to estimate internal dosimetry were investigated. Biodistribution studies were used in order to compare these methods. The main study aspects included region-of-interest (ROI) delineation methods, reconstruction algorithms, scatter correction and radiopharmaceutical's biokinetic. Optimization of internal dosimetry in this thesis was completed with the development of a Monte Carlo (MC) technique for estimating the patient-specific PET/CT dosimetry. The development of a mathematical model using MC techniques allowed us to have a gold standard to which compare classical techniques and study the aspects discussed previously. It was observed that effective dose (ED) estimations were sensitive to whichever delineation ROI method was applied. Furthermore, it was perceived that the biokinetics of the radioligand also influences in the ED estimation. On the other hand, similar quantitative accuracy was found regarding image reconstruction (FBP and OSEM) and scatter correction methods studied (FSC and SSC). Analysis of the impact of inter- and intra-operator variability in dose estimations revealed higher reproducibility in 3D methods in comparison with 2D planar method. The last one, showed the highest interoperator variability, which implies an overestimation of the ED. In this dissertation, specific routines were developed to be applied with the MC code PENELOPE/penEasy to perform individualized internal dosimetry estimations. Voxel-level absorbed dose maps which include self- and cross-irradiation doses were generated from the morphological and functional patient images. Further parameters such as cumulative organ dose, maximum and minimum voxel organ values, volume of the organ and dose-volume histograms of interest were reported. The model implemented was applied to a theoretical study using simulated PET images of a voxelized Zubal phantom. The results were benchmarked with the ones obtained using the OLINDA/EXM software. The comparison was in good agreement for those organs were both phantoms considered (Zubal and the reference one in OLINDA/EXM) were close. Undoubtedly, the implementation of a patient-specific internal dosimetry method not only leads to an improvement in diagnostic examinations where the risk could be quantified, but also NM therapy could become more effective in terms that patients receiving an optimal care.L'objectiu d'aquesta tesi va ser avaluar i desenvolupar mètodes de càlcul de dosis interna en procediments de diagnòstic i terapèutics de medicina nuclear per a pacients sotmesos a exploracions PET / TC. Amb aquest objectiu, es va investigar l'exactitud i la precisió dels diferents mètodes clàssics utilitzats habitualment per estimar la dosimetria interna. Es van utilitzar estudis de biodistribució per comparar aquests mètodes. Els principals aspectes d'estudi incloïen mètodes de delimitació de la regió d'interès (ROI), algoritmes de reconstrucció, correcció de dispersió i biocinètiques de radiofàrmacs. L'optimització de la dosimetria interna en aquesta tesi es va completar amb el desenvolupament d'una tècnica de Monte Carlo (MC) per a estimar la dosimetria PET / TC específica del pacient. El desenvolupament d'un model matemàtic amb tècniques de MC ens va permetre tenir una referència amb la que comparar les tècniques clàssiques i estudiar els aspectes descrits anteriorment. Es va observar que les estimacions de la dosi efectiva (DE) eren sensibles a qualsevol mètode de delimitació de la ROI aplicada. A més a més, es va percebre que la biocinètica del radiolligand també influeix en l'estimació de la DE. D'altra banda, es va trobar una exactitud quantitativament similar pel que fa a la reconstrucció d'imatges (FBP i OSEM) i els mètodes de correcció de dispersió estudiats (FSC i SSC). L'anàlisi de l'impacte de la variabilitat entre operadors i intra-operadors en les estimacions de dosis va mostrar una major reproductibilitat en els mètodes 3D en comparació amb el mètode planar 2D. Aquest últim, va mostrar la màxima variabilitat entre operadors, la qual cosa implica una sobreestimació de la DE. En aquesta tesi, es van desenvolupar rutines específiques per aplicar-les amb el codi MC PENELOPE / penEasy per a realitzar estimacions de dosimetria interna individualitzades. Es van generar mapes de dosis absorbida a nivell de voxel que incloïen dosis d? autoirradiació i irradiació creuada a partir de les imatges morfològiques i funcionals del pacient. Es van reportar altres paràmetres d?interès com la dosi d'òrgan acumulada, els valors màxims i mínims de l'òrgan i del vòxel, el volum de l'òrgan i els histogrames de dosi-volum. El model implementat es va aplicar a un estudi teòric mitjançant imatges simulades de PET d'un maniquí de Zubal voxelitzat. Els resultats es van comparar amb els obtinguts mitjançant el programa OLINDA / EXM. Es va observar un bon acord per a aquells òrgans semblants entre el maniquí de Zubal i el maniquí de referència del software OLINDA/EXM. Sens dubte, la implementació d'un mètode de dosimetria interna específic per al pacient no només condueix a una millora en les exploracions de diagnòstic on es pot quantificar el risc d?irradiació, sinó que la teràpia amb medicina nuclear podria ser més eficaç en termes que els pacients rebin un tractament òptim.Postprint (published version

Improving resolution for the Siemens 3T MR-BrainPET

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2015A tomografia por emissão de positrões (acrónimo em inglês: PET) consiste numa técnica imagiológica não invasiva que permite obter informação in vivo sobre a distribuição espácio-temporal das moléculas. Antes da aquisição de imagem é necessário que um radiofármaco seja administrado ao paciente para que posteriormente este se distribua ao longo do corpo de acordo com a estrutura química e a fisiologia da pessoa. O PET é uma modalidade de imagem médica que se destaca pela aquisição de informação fisiológica. No entanto a informação anatómica fornecida por esta técnica é bastante escassa. Para contrariar esta limitação foi proposta a fusão do PET com outra modalidade que permitisse este tipo de informação: tomografia computorizada (acrónimo em inglês: CT) ou ressonância magnética nuclear (acrónimo em inglês: MRI). Inicialmente a fusão das duas imagens médicas não permitia a aquisição simultânea, baseando-se no co-registo das imagens adquiridas. Contudo, devido a vários erros causados pelas diferenças no posicionamento do paciente, foi proposto o desenvolvimento de sistemas híbridos que permitem a aquisição simultânea das diferentes imagens. Em 1998 foi proposto o primeiro sistema hídrico (com PET), PET/CT. Como técnicas de CT envolvem radiação ionizante e apresentam um reduzido contraste entre os tecidos moles, o PET/CT foi recentemente substituído por PET/MRI, permitindo a conjugação de informação molecular do PET com informação anatómica, funcional e estrutural da MRI. No entanto, esta fusão apresentou algumas dificuldades, como por exemplo os detetores e a eletrónica do PET serem sensíveis aos campos magnéticos da MRI. Entretanto foram desenvolvidos os fotodíodos de avalanche (acrónimo em inglês: APD) permitindo a construção dos sistemas híbridos PET/MRI. O BrainPET foi o primeiro sistema híbrido de PET/MRI, existindo apenas quatro scanners em todo o mundo. O scanner 3TMR-BrainPET, desenvolvido pela Siemens Medical Solution Inc., foi construído para imagiologia cerebral. Este scanner permite a aquisição de imagens PET com alta resolução (3 mm). Alguns exames médicos como o PET apresentam uma aquisição muito longa (aproximadamente 1 hora), tornando-se difícil para o paciente permanecer imóvel durante toda a aquisição. Por conseguinte, na maioria dos casos, o movimento torna-se inevitável, introduzindo artefactos na imagem e consequentemente degradando-a. Assim, torna-se fundamental corrigir este movimento para assegurar a qualidade ótima das imagens, oferecendo a perspetiva de melhorar o diagnóstico e o tratamento. Ao longo dos anos foram propostos diversos métodos de correção do movimento. Uns corrigem-no no domínio da imagem, corrigindo apenas o movimento entre as frames mas não o que ocorre dentro de cada uma delas, e outros no domínio dos eventos, em que a correção do movimento consegue ser mais precisa uma vez que é feita diretamente nos eventos adquiridos. No contexto PET/MRI, ambas as imagens, PET e MRI, podem ser utilizadas para estimar o movimento e posteriormente corrigi-lo. Nesta tese focar-nos-emos apenas na correção do movimento da cabeça que é considerado um movimento rígido e os parâmetros que o representam, três rotações e três translações de acordo com os três eixos Cartesianos (x, y e z), podem ser estimados utilizando algoritmos de registo de imagens. Este trabalho apresenta e testa um software de código aberto que dispõe desses algoritmos de dados multidimensionais, o Insight Toolkit (ITK), permitindo a estimação do movimento no domínio da imagem. O ITK já foi aplicado, com sucesso, em estudos de correções do movimento em modalidades técnicas de imagem, tanto para movimentos rígidos como deformáveis, que é o caso do movimento provocado pela respiração ou pelo batimento cardíaco. Relativamente à metodologia aplicada neste trabalho, inicialmente foram adquiridas imagens MPRAGE (imagens adquiridas com MRI) com o intuito de descobrir o alcance máximo do movimento da cabeça dentro das bobines do scanner. De seguida foram simulados quatro alcances diferentes: 1, 5, 10 e 30 de translação (mm) e de rotação (º) considerando os três eixos (x, y e z). Com o objetivo de testar a versatilidade do software, estas simulações foram realizadas em diversos tipos de imagens como, imagens clinicas, [18F]-FDG (imagem adquirida com PET) e EPI (imagem adquirida com MRI), e imagens de fantomas simulados, fantoma Utah e fantoma cerebral. Ao longo da dissertação foram realizados diversos estudos, como por exemplo, o estudo da influência da estatística de aquisição e do número de iterações do método de reconstrução de imagem na estimação do movimento. A estatística de aquisição influencia qualitativamente as imagens de PET, uma vez que quanto maior a estatística menor é o ruido. Ao mesmo tempo esta também é influenciada pelo número de iterações, visto que à medida que se aumenta o número de iterações o ruído da imagem aumenta, no entanto quando a imagem contém um número de iterações menor esta apresenta um bias maior. O ITK estima o movimento a partir de uma comparação de valores de intensidade das imagens, por conseguinte estas alterações qualitativas na imagem levam a diferentes estimações dos parâmetros do mesmo movimento simulado. Como um dos objetivos da tese consiste em verificar se o ITK pode ser utilizado para estimar o movimento no Instituto Forschungszentrum Juelich (FZJ), foram, adicionalmente, testadas imagens de cinco exames diferentes adquiridos rotineiramente no scanner 3TMR-BrainPET deste instituto. Em todas as imagens o movimento foi estimado utilizando o ITK. Este software apresenta um método iterativo para estimação do movimento. O ITK necessita de duas imagens de input, uma imagem fixa e uma imagem movida, enquanto o output deste software consiste em três translações e três rotações de acordo com os eixos cartesianos (transformada de Euler) que correspondem aos parâmetros do movimento rígido da cabeça. Ulteriormente, para corrigir esses movimentos, foram aplicadas transformadas inversas nas imagens afetadas pelo movimento. Estas transformadas podem ser aplicadas por outro programa, como por exemplo o PRESTO (PET REconstruction Software Toolkit), um software de reconstrução constituído por bibliotecas desenvolvidas em programação C++. Neste trabalho, utilizou-se o PRESTO para a aplicação das transformadas, na correção do movimento e na simulação dos fantomas e dos movimentos nas imagens. Atualmente o FZJ utiliza um software diferente do ITK para corrigir o movimento, o PMOD (PMOD Technologies Ltd, Zurique, Suíça). No entanto este apresenta algumas limitações, como por exemplo, o facto de ser um software comercial e este não poder ser incorporado no script de reconstrução, sendo necessário um processo adicional trabalhoso, ao contrário do ITK que permite que a correção do movimento seja feita automaticamente durante a reconstrução, corrigindo o movimento diretamente nas linhas de resposta (acrónimo em inglês: LORs). Adicionalmente o PMOD requer um utilizador com conhecimento prévio sobre o software para conseguir manuseá-lo. Para confirmar a viabilidade do ITK e verificar se este pode substituir o PMOD na correção do movimento no instituto, foi feita uma comparação entre os resultados dos dois software. Os resultados obtidos revelaram-se muito semelhantes, exceto quando se utiliza imagens de PET com baixa estatística ou imagens com grandes movimentos. Como as imagens sem correção de atenuação apresentam maior diferença de intensidades entre as fronteiras do objeto em estudo e o fundo da imagem, pensou-se na hipótese de os parâmetros do movimento obtidos pelo ITK ou pelo PMOD poderem apresentar erros menores utilizando imagens sem correção de atenuação. Ao mesmo tempo, como a correção do movimento atualmente no instituto está a ser realizada depois da reconstrução, um mapa de atenuação errado (mapa que não considera o movimento) está a ser aplicado à imagem. Neste sentido, o impacto do mapa de atenuação aplicado às imagens afetadas pelo movimento foi também estudado nesta dissertação. Os maiores erros foram encontrados quando se utilizou imagens sem correção de atenuação. Os bons resultados do PMOD revelaram-se mais dependentes da aplicação do mapa de atenuação correto. Em conclusão o ITK apresentou melhores resultados que o PMOD e a diferença entre as três imagens testadas pelo ITK não se revelou muito significativa. Com o objetivo de melhorar os resultados obtidos, três métricas diferentes do ITK (Mutual Information, Mean Squares e Normalized Correlation) foram comparadas entre si, aplicando diferentes imagens de PET e de MRI como input. Este teste mostrou que a métrica é um parâmetro altamente dependente do problema que se tenta resolver. A métrica mutual information é a melhor métrica para corrigir o movimento utilizando imagens de diferentes modalidades, enquanto a métrica normalized correlation é a melhor nos estudos com imagens da mesma modalidade. De acordo com todos os resultados obtidos, pode-se afirmar que o ITK é um método viável para a estimação dos parâmetros do movimento rígido e tem capacidades de substituir o PMOD. Esses parâmetros, posteriormente, podem ser utilizados para a correção do movimento no pós-processamento de imagens de PET ou MRI.The Siemens 3TMR-BrainPET scanner is a hybrid system which allows simultaneous acquisition of MRI and PET. There are medical exams that have long acquisition time and then it is inevitable introducing blurring in images. Therefore motion correction strategies are mandatory. In PET/MRI context, both PET and MRI images can be used for this purpose. Head motion is considered as rigid motion and the motion parameters can be estimated with image registration algorithms. In this thesis a software which has available these algorithms, Insight Toolkit (ITK), will be presented and tested. First MPRAGE images were acquired to check the maximum motion range inside the scanner head coil during acquisition. Therefore four motion ranges were simulated in translation and rotation with respect to the three Cartesian axes. Testing the software versatility, these simulations were realized in different images: simulated and clinical data. Several studies were made with these images e.g. the influence of statistics and number of iterations in motion estimation. Additionally images from five different exams performed in FZJ were also used. The motion was estimated by ITK. The ITK output is three translations and three rotations which correspond to the rigid motion parameters. Subsequently, to correct the motion, inverse transformations were applied in moved images. Actually FZJ uses other software, PMOD (PMOD Technologies Ltd, Zurich, Switzerland) to motion correction. For the purpose of confirm the viability of ITK and to verify if it can replace the PMOD, ITK results were compared with PMOD results. Other tests were made with the aim to improve the results such as study the impact of the attenuation map in motion estimation and the comparison between ITK results using three different metrics. According to results, ITK is a viable method of motion parameter estimation which can be used for PET or MRI post-processing motion correction

Using PET/MRI to Assess Hepatic Radioembolization of Yttrium-90 Microspheres

Radioembolization of yttrium-90 (Y-90) microspheres is used to treat primary and secondary cancers in the liver. Though this therapy has existed for decades, the treatment is not well optimized from treatment planning to post-procedural assessment. Recently, there has been a surge to utilize the small positron yield from the radioactive decay of Y-90 for post-radioembolization positron emission tomography (PET) imaging of the microsphere activity distribution. These images provide promise for dosimetry assessment, identifying extrahepatic uptake and possible under-dosed lesions that may benefit from subsequent therapy. However, due to the low positron statistics and high flux of Bremsstrahlung radiation, PET imaging of Y-90 presents with its own unique set of challenges. In this work, we optimized the PET imaging acquisition and reconstruction parameters when imaging with a hybrid PET/MRI scanner to offer the most accurate images for quantitative dosimetric applications. We then tested the variability of imaging Y-90 with PET across multiple institutions in a world-wide phantom study in preparation for a multi-institutional phase I/II clinical trial. Lastly, we determined the clinical utility of using Y-90 PET-based dosimetry to predict clinical outcomes and assess how well it correlates with pre-treatment imaging

Investigation and Correction for the Partial Volume Spill in Effects in Positron Emission Tomography

Positron emission tomography (PET) imaging has a wide applicability in oncology, cardiology and neurology. However, a major drawback when imaging very active regions such as the bladder and the bone is the spill in effect, leading to inaccurate quantification and obscured visualisation of nearby lesions. Therefore, this thesis aims at investigating and correcting for the spill in effect from high activity regions to the surroundings, as a function of activity in the hot region, lesion size and location, system resolution as well as application of post-filtering, using the background correction technique. This thesis involved analytical simulations for the digital XCAT2 phantom, and validation acquiring data from NEMA phantoms and patient datasets with the GE Signa PET/MR and Siemens Biograph mMR/mCT scanners. Reconstructions were done using the ordered subset expectation maximisation (OSEM) algorithm. Dedicated point spread function (OSEM+PSF) and the background correction (OSEM+PSF+BC) were incorporated into the reconstruction for spill in correction. For region of interest (ROI) analysis, a semi-automated ellipsoidal ROIs were drawn on the exact location of the lesions, and these were used to extract the standardized uptake value (SUV). The bias, recovery coefficient (RC), coefficient of variation (CoV) and contrast-to-noise ratio (CNR) were computed from the SUVs, and these were used as figures of merit to compare the performances of all the reconstruction algorithms. The thesis revealed that: (i) lesions within 15-20 mm from the hot region are predominantly affected by the spill in effect, leading to an increased bias and impaired lesion visualisation within the region; (ii) the spill in effect is further influenced by the ROI selection, increasing activity in the hot region, reduced resolution and application of post-filter; (iii) the spill in effect is more evident for the SUVmax than the SUVmean; (iv) for proximal lesions (within 2 voxels around the hot region), PSF has no major improvement over OSEM because of the spill in effect, coupled with the Gibbs effect; (v) with OSEM+PSF+BC, the spill in contribution from the hot region was removed in all cases (irrespective of ROI-selection, proximity of lesion to hot source, or application of post-filter), thereby facilitating stability in quantification and enhancing the contrast in lesions with low uptake. This thesis therefore concludes that the BC technique is effective in correcting for the spill in effect from hot regions to surrounding regions of interest. It is also robust to ROI-induced errors and post-filtering

Impact of motion compensation and partial volume correction for ¹⁸F-NaF PET/CT imaging of coronary plaque

Recent studies have suggested that ¹⁸F-NaF-PET enables visualization and quantification of plaque micro-calcification in the coronary tree. However, PET imaging of plaque calcification in the coronary arteries is challenging because of the respiratory and cardiac motion as well as partial volume effects. The objective of this work is to implement an image reconstruction framework, which incorporates compensation for respiratory as well as cardiac motion (MoCo) and partial volume correction (PVC), for cardiac ¹⁸F-NaF PET imaging in PET/CT. We evaluated the effect of MoCo and PVC on the quantification of vulnerable plaques in the coronary arteries. Realistic simulations (Biograph TPTV, Biograph mCT) and phantom acquisitions (Biograph mCT) were used for these evaluations. Different uptake values in the calcified plaques were evaluated in the simulations, while three "plaque-type" lesions of 36, 31 and 18 mm³ were included in the phantom experiments. After validation, the MoCo and PVC methods were applied in four pilot NaF-PET patient studies. In all cases, the MoCo-based image reconstruction was performed using the STIR software. The PVC was obtained from a local projection (LP) method, previously evaluated in preclinical and clinical PET. The results obtained show a significant increase of the measured lesion-to-background ratios (LBR) in the MoCo+PVC images. These ratios were further enhanced when using directly the tissue-activities from the LP method, making this approach more suitable for the quantitative evaluation of coronary plaques. When using the LP method on the MoCo images, LBR increased between 200% and 1119% in the simulated data, between 212% and 614% in the phantom experiments and between 46% and 373% in the plaques with positive uptake observed in the pilot patients. In conclusion, we have built and validated a STIR framework incorporating MoCo and PVC for ¹⁸NaF PET imaging of coronary plaques. First results indicate an improved quantification of plaque-type lesions

Improving Quantification in Lung PET/CT for the Evaluation of Disease Progression and Treatment Effectiveness

Positron Emission Tomography (PET) allows imaging of functional processes in vivo by measuring the distribution of an administered radiotracer. Whilst one of its main uses is directed towards lung cancer, there is an increased interest in diffuse lung diseases, for which the incidences rise every year, mainly due to environmental reasons and population ageing. However, PET acquisitions in the lung are particularly challenging due to several effects, including the inevitable cardiac and respiratory motion and the loss of spatial resolution due to low density, causing increased positron range. This thesis will focus on Idiopathic Pulmonary Fibrosis (IPF), a disease whose aetiology is poorly understood while patient survival is limited to a few years only. Contrary to lung tumours, this diffuse lung disease modifies the lung architecture more globally. The changes result in small structures with varying densities. Previous work has developed data analysis techniques addressing some of the challenges of imaging patients with IPF. However, robust reconstruction techniques are still necessary to obtain quantitative measures for such data, where it should be beneficial to exploit recent advances in PET scanner hardware such as Time of Flight (TOF) and respiratory motion monitoring. Firstly, positron range in the lung will be discussed, evaluating its effect in density-varying media, such as fibrotic lung. Secondly, the general effect of using incorrect attenuation data in lung PET reconstructions will be assessed. The study will compare TOF and non-TOF reconstructions and quantify the local and global artefacts created by data inconsistencies and respiratory motion. Then, motion compensation will be addressed by proposing a method which takes into account the changes of density and activity in the lungs during the respiration, via the estimation of the volume changes using the deformation fields. The method is evaluated on late time frame PET acquisitions using ¹⁸F-FDG where the radiotracer distribution has stabilised. It is then used as the basis for a method for motion compensation of the early time frames (starting with the administration of the radiotracer), leading to a technique that could be used for motion compensation of kinetic measures. Preliminary results are provided for kinetic parameters extracted from short dynamic data using ¹⁸F-FDG

Attenuation correction of myocardial perfusion scintigraphy images without transmission scanning

Attenuation correction is essential for reliable interpretation of emission tomography; however the use of transmission measurements to generate attenuation maps is limited by availability of equipment and potential mismatches between the transmission and emission measurements. This work investigates the possibility of estimating an attenuation map using measured scatter data without a transmission scan. A scatter model has been developed that predicts the distribution of photons which have been scattered once. The scatter model has been used as the basis of a maximum likelihood gradient ascent method (SMLGA) to estimate an attenuation map from measured scatter data. The SMLGA algorithm has been combined with an existing algorithm using photopeak data to estimate an attenuation map (MLAA) in order to obtain a more accurate attenuation map than using either algorithm alone. Iterations of the SMLGA-MLAA algorithm are alternated with iterations of the MLEM algorithm to estimate the activity distribution. Initial tests of the algorithm were performed in 2 dimensions using idealised data before extension to 3 dimensions. The basic algorithm has been tested in 3 dimensions using projection data simulated using a Monte Carlo simulator with software phantoms. All soft tissues within the body have similar attenuation characteristics and so only a small number of different values are normally present. A Level-Set technique to restrict the attenuation map to a piecewise constant function has therefore been investigated as a potential way to improve the quality of the reconstructed attenuation map. The basic SMLGA-MLAA algorithm contains a number of assumptions; the effect of these has been investigated and the model extended to include the effect of photons which are scattered more than once and scatter correction of the photopeak. The effect of different phantom shapes and activity distributions has been assessed and the final algorithm tested using data acquired using a physical phantom