Avaliação do desempenho de um sistema híbrido de tomografia por emissão de positrões e tomografia computorizada

Mestrado em Medicina Nuclear.

Assessment of statistical iterative reconstructions to optimize CT examination protocols for children and young adults

La tomodensitométrie (CT) est une technique d'imagerie dont l'intérêt n'a cessé de croître depuis son apparition dans le début des années 70. Dans le domaine médical, son utilisation est incontournable à tel point que ce système d'imagerie pourrait être amené à devenir victime de son succès si son impact au niveau de l'exposition de la population ne fait pas l'objet d'une attention particulière. Bien évidemment, l'augmentation du nombre d'examens CT a permis d'améliorer la prise en charge des patients ou a rendu certaines procédures moins invasives. Toutefois, pour assurer que le compromis risque - bénéfice soit toujours en faveur du patient, il est nécessaire d'éviter de délivrer des doses non utiles au diagnostic.¦Si cette action est importante chez l'adulte elle doit être une priorité lorsque les examens se font chez l'enfant, en particulier lorsque l'on suit des pathologies qui nécessitent plusieurs examens CT au cours de la vie du patient. En effet, les enfants et jeunes adultes sont plus radiosensibles. De plus, leur espérance de vie étant supérieure à celle de l'adulte, ils présentent un risque accru de développer un cancer radio-induit dont la phase de latence peut être supérieure à vingt ans. Partant du principe que chaque examen radiologique est justifié, il devient dès lors nécessaire d'optimiser les protocoles d'acquisitions pour s'assurer que le patient ne soit pas irradié inutilement. L'avancée technologique au niveau du CT est très rapide et depuis 2009, de nouvelles techniques de reconstructions d'images, dites itératives, ont été introduites afin de réduire la dose et améliorer la qualité d'image.¦Le présent travail a pour objectif de déterminer le potentiel des reconstructions itératives statistiques pour réduire au minimum les doses délivrées lors d'examens CT chez l'enfant et le jeune adulte tout en conservant une qualité d'image permettant le diagnostic, ceci afin de proposer des protocoles optimisés.¦L'optimisation d'un protocole d'examen CT nécessite de pouvoir évaluer la dose délivrée et la qualité d'image utile au diagnostic. Alors que la dose est estimée au moyen d'indices CT (CTDIV0| et DLP), ce travail a la particularité d'utiliser deux approches radicalement différentes pour évaluer la qualité d'image. La première approche dite « physique », se base sur le calcul de métriques physiques (SD, MTF, NPS, etc.) mesurées dans des conditions bien définies, le plus souvent sur fantômes. Bien que cette démarche soit limitée car elle n'intègre pas la perception des radiologues, elle permet de caractériser de manière rapide et simple certaines propriétés d'une image. La seconde approche, dite « clinique », est basée sur l'évaluation de structures anatomiques (critères diagnostiques) présentes sur les images de patients. Des radiologues, impliqués dans l'étape d'évaluation, doivent qualifier la qualité des structures d'un point de vue diagnostique en utilisant une échelle de notation simple. Cette approche, lourde à mettre en place, a l'avantage d'être proche du travail du radiologue et peut être considérée comme méthode de référence.¦Parmi les principaux résultats de ce travail, il a été montré que les algorithmes itératifs statistiques étudiés en clinique (ASIR?, VEO?) ont un important potentiel pour réduire la dose au CT (jusqu'à-90%). Cependant, par leur fonctionnement, ils modifient l'apparence de l'image en entraînant un changement de texture qui pourrait affecter la qualité du diagnostic. En comparant les résultats fournis par les approches « clinique » et « physique », il a été montré que ce changement de texture se traduit par une modification du spectre fréquentiel du bruit dont l'analyse permet d'anticiper ou d'éviter une perte diagnostique. Ce travail montre également que l'intégration de ces nouvelles techniques de reconstruction en clinique ne peut se faire de manière simple sur la base de protocoles utilisant des reconstructions classiques. Les conclusions de ce travail ainsi que les outils développés pourront également guider de futures études dans le domaine de la qualité d'image, comme par exemple, l'analyse de textures ou la modélisation d'observateurs pour le CT.¦-¦Computed tomography (CT) is an imaging technique in which interest has been growing since it first began to be used in the early 1970s. In the clinical environment, this imaging system has emerged as the gold standard modality because of its high sensitivity in producing accurate diagnostic images. However, even if a direct benefit to patient healthcare is attributed to CT, the dramatic increase of the number of CT examinations performed has raised concerns about the potential negative effects of ionizing radiation on the population. To insure a benefit - risk that works in favor of a patient, it is important to balance image quality and dose in order to avoid unnecessary patient exposure.¦If this balance is important for adults, it should be an absolute priority for children undergoing CT examinations, especially for patients suffering from diseases requiring several follow-up examinations over the patient's lifetime. Indeed, children and young adults are more sensitive to ionizing radiation and have an extended life span in comparison to adults. For this population, the risk of developing cancer, whose latency period exceeds 20 years, is significantly higher than for adults. Assuming that each patient examination is justified, it then becomes a priority to optimize CT acquisition protocols in order to minimize the delivered dose to the patient. Over the past few years, CT advances have been developing at a rapid pace. Since 2009, new iterative image reconstruction techniques, called statistical iterative reconstructions, have been introduced in order to decrease patient exposure and improve image quality.¦The goal of the present work was to determine the potential of statistical iterative reconstructions to reduce dose as much as possible without compromising image quality and maintain diagnosis of children and young adult examinations.¦The optimization step requires the evaluation of the delivered dose and image quality useful to perform diagnosis. While the dose is estimated using CT indices (CTDIV0| and DLP), the particularity of this research was to use two radically different approaches to evaluate image quality. The first approach, called the "physical approach", computed physical metrics (SD, MTF, NPS, etc.) measured on phantoms in well-known conditions. Although this technique has some limitations because it does not take radiologist perspective into account, it enables the physical characterization of image properties in a simple and timely way. The second approach, called the "clinical approach", was based on the evaluation of anatomical structures (diagnostic criteria) present on patient images. Radiologists, involved in the assessment step, were asked to score image quality of structures for diagnostic purposes using a simple rating scale. This approach is relatively complicated to implement and also time-consuming. Nevertheless, it has the advantage of being very close to the practice of radiologists and is considered as a reference method.¦Primarily, this work revealed that the statistical iterative reconstructions studied in clinic (ASIR? and VECO have a strong potential to reduce CT dose (up to -90%). However, by their mechanisms, they lead to a modification of the image appearance with a change in image texture which may then effect the quality of the diagnosis. By comparing the results of the "clinical" and "physical" approach, it was showed that a change in texture is related to a modification of the noise spectrum bandwidth. The NPS analysis makes possible to anticipate or avoid a decrease in image quality. This project demonstrated that integrating these new statistical iterative reconstruction techniques can be complex and cannot be made on the basis of protocols using conventional reconstructions. The conclusions of this work and the image quality tools developed will be able to guide future studies in the field of image quality as texture analysis or model observers dedicated to CT.

High-resolution 3D whole-heart coronary MRA: a study on the combination of data acquisition in multiple breath-holds and 1D residual respiratory motion compensation.

OBJECT: To study a scan protocol for coronary magnetic resonance angiography based on multiple breath-holds featuring 1D motion compensation and to compare the resulting image quality to a navigator-gated free-breathing acquisition. Image reconstruction was performed using L1 regularized iterative SENSE. MATERIALS AND METHODS: The effects of respiratory motion on the Cartesian sampling scheme were minimized by performing data acquisition in multiple breath-holds. During the scan, repetitive readouts through a k-space center were used to detect and correct the respiratory displacement of the heart by exploiting the self-navigation principle in image reconstruction. In vivo experiments were performed in nine healthy volunteers and the resulting image quality was compared to a navigator-gated reference in terms of vessel length and sharpness. RESULTS: Acquisition in breath-hold is an effective method to reduce the scan time by more than 30 % compared to the navigator-gated reference. Although an equivalent mean image quality with respect to the reference was achieved with the proposed method, the 1D motion compensation did not work equally well in all cases. CONCLUSION: In general, the image quality scaled with the robustness of the motion compensation. Nevertheless, the featured setup provides a positive basis for future extension with more advanced motion compensation methods.

Linking supply to demand: the neuronal monocarboxylate transporter MCT2 and the alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionic acid receptor GluR2/3 subunit are associated in a common trafficking process.

MCT2 is the major neuronal monocarboxylate transporter (MCT) that allows the supply of alternative energy substrates such as lactate to neurons. Recent evidence obtained by electron microscopy has demonstrated that MCT2, like alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionic acid (AMPA) receptors, is localized in dendritic spines of glutamatergic synapses. Using immunofluorescence, we show in this study that MCT2 colocalizes extensively with GluR2/3 subunits of AMPA receptors in neurons from various mouse brain regions as well as in cultured neurons. It also colocalizes with GluR2/3-interacting proteins, such as C-kinase-interacting protein 1, glutamate receptor-interacting protein 1 and clathrin adaptor protein. Coimmunoprecipitation of MCT2 with GluR2/3 and C-kinase-interacting protein 1 suggests their close interaction within spines. Parallel changes in the localization of both MCT2 and GluR2/3 subunits at and beneath the plasma membrane upon various stimulation paradigms were unraveled using an original immunocytochemical and transfection approach combined with three-dimensional image reconstruction. Cell culture incubation with AMPA or insulin triggered a marked intracellular accumulation of both MCT2 and GluR2/3, whereas both tumor necrosis factor alpha and glycine (with glutamate) increased their cell surface immunolabeling. Similar results were obtained using Western blots performed on membrane or cytoplasm-enriched cell fractions. Finally, an enhanced lactate flux into neurons was demonstrated after MCT2 translocation on the cell surface. These observations provide unequivocal evidence that MCT2 is linked to AMPA receptor GluR2/3 subunits and undergoes a similar translocation process in neurons upon activation. MCT2 emerges as a novel component of the synaptic machinery putatively linking neuroenergetics to synaptic transmission.

Enhanced compressed sensing recovery with level set normals.

We propose a compressive sensing algorithm that exploits geometric properties of images to recover images of high quality from few measurements. The image reconstruction is done by iterating the two following steps: 1) estimation of normal vectors of the image level curves, and 2) reconstruction of an image fitting the normal vectors, the compressed sensing measurements, and the sparsity constraint. The proposed technique can naturally extend to nonlocal operators and graphs to exploit the repetitive nature of textured images to recover fine detail structures. In both cases, the problem is reduced to a series of convex minimization problems that can be efficiently solved with a combination of variable splitting and augmented Lagrangian methods, leading to fast and easy-to-code algorithms. Extended experiments show a clear improvement over related state-of-the-art algorithms in the quality of the reconstructed images and the robustness of the proposed method to noise, different kind of images, and reduced measurements.

Study of OSEM with different subsets in grating-based X-ray differential phase-contrast imaging.

Impressive developments in X-ray imaging are associated with X-ray phase contrast computed tomography based on grating interferometry, a technique that provides increased contrast compared with conventional absorption-based imaging. A new "single-step" method capable of separating phase information from other contributions has been recently proposed. This approach not only simplifies data-acquisition procedures, but, compared with the existing phase step approach, significantly reduces the dose delivered to a sample. However, the image reconstruction procedure is more demanding than for traditional methods and new algorithms have to be developed to take advantage of the "single-step" method. In the work discussed in this paper, a fast iterative image reconstruction method named OSEM (ordered subsets expectation maximization) was applied to experimental data to evaluate its performance and range of applicability. The OSEM algorithm with different subsets was also characterized by comparison of reconstruction image quality and convergence speed. Computer simulations and experimental results confirm the reliability of this new algorithm for phase-contrast computed tomography applications. Compared with the traditional filtered back projection algorithm, in particular in the presence of a noisy acquisition, it furnishes better images at a higher spatial resolution and with lower noise. We emphasize that the method is highly compatible with future X-ray phase contrast imaging clinical applications.

Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

Medical physicists' implication in radiological diagnostic procedures: results after 1 y of experience.

Since January 2008-de facto 2012-medical physics experts (MPEs) are, by law, to be involved in the optimisation process of radiological diagnostic procedures in Switzerland. Computed tomography, fluoroscopy and nuclear medicine imaging units have been assessed for patient exposure and image quality. Large spreads in clinical practice have been observed. For example, the number of scans per abdominal CT examination went from 1 to 9. Fluoroscopy units showed, for the same device settings, dose rate variations up to a factor of 3 to 7. Quantitative image quality for positron emission tomography (PET)/CT examinations varied significantly depending on the local image reconstruction algorithms. Future work will be focused on promoting team cooperation between MPEs, radiologists and radiographers and on implementing task-oriented objective image quality indicators.

Development of cardiovascular magnetic resonance imaging techniques for improved characterization of atherosclerotic disease

Atherosclerosis is a chronic cardiovascular disease that involves the thicken¬ing of the artery walls as well as the formation of plaques (lesions) causing the narrowing of the lumens, in vessels such as the aorta, the coronary and the carotid arteries. Magnetic resonance imaging (MRI) is a promising modality for the assessment of atherosclerosis, as it is a non-invasive and patient-friendly procedure that does not use ionizing radiation. MRI offers high soft tissue con¬trast already without the need of intravenous contrast media; while modifica¬tion of the MR pulse sequences allows for further adjustment of the contrast for specific diagnostic needs. As such, MRI can create angiographic images of the vessel lumens to assess stenoses at the late stage of the disease, as well as blood flow-suppressed images for the early investigation of the vessel wall and the characterization of the atherosclerotic plaques. However, despite the great technical progress that occurred over the past two decades, MRI is intrinsically a low sensitive technique and some limitations still exist in terms of accuracy and performance. A major challenge for coronary artery imaging is respiratory motion. State- of-the-art diaphragmatic navigators rely on an indirect measure of motion, per¬form a ID correction, and have long and unpredictable scan time. In response, self-navigation (SM) strategies have recently been introduced that offer 100% scan efficiency and increased ease of use. SN detects respiratory motion di¬rectly from the image data obtained at the level of the heart, and retrospectively corrects the same data before final image reconstruction. Thus, SN holds po-tential for multi-dimensional motion compensation. To this regard, this thesis presents novel SN methods that estimate 2D and 3D motion parameters from aliased sub-images that are obtained from the same raw data composing the final image. Combination of all corrected sub-images produces a final image with reduced motion artifacts for the visualization of the coronaries. The first study (section 2.2, 2D Self-Navigation with Compressed Sensing) consists of a method for 2D translational motion compensation. Here, the use of com- pressed sensing (CS) reconstruction is proposed and investigated to support motion detection by reducing aliasing artifacts. In healthy human subjects, CS demonstrated an improvement in motion detection accuracy with simula¬tions on in vivo data, while improved coronary artery visualization was demon¬strated on in vivo free-breathing acquisitions. However, the motion of the heart induced by respiration has been shown to occur in three dimensions and to be more complex than a simple translation. Therefore, the second study (section 2.3,3D Self-Navigation) consists of a method for 3D affine motion correction rather than 2D only. Here, different techniques were adopted to reduce background signal contribution in respiratory motion tracking, as this can be adversely affected by the static tissue that surrounds the heart. The proposed method demonstrated to improve conspicuity and vi¬sualization of coronary arteries in healthy and cardiovascular disease patient cohorts in comparison to a conventional ID SN method. In the third study (section 2.4, 3D Self-Navigation with Compressed Sensing), the same tracking methods were used to obtain sub-images sorted according to the respiratory position. Then, instead of motion correction, a compressed sensing reconstruction was performed on all sorted sub-image data. This process ex¬ploits the consistency of the sorted data to reduce aliasing artifacts such that the sub-image corresponding to the end-expiratory phase can directly be used to visualize the coronaries. In a healthy volunteer cohort, this strategy improved conspicuity and visualization of the coronary arteries when compared to a con¬ventional ID SN method. For the visualization of the vessel wall and atherosclerotic plaques, the state- of-the-art dual inversion recovery (DIR) technique is able to suppress the signal coming from flowing blood and provide positive wall-lumen contrast. How¬ever, optimal contrast may be difficult to obtain and is subject to RR variability. Furthermore, DIR imaging is time-inefficient and multislice acquisitions may lead to prolonged scanning times. In response and as a fourth study of this thesis (chapter 3, Vessel Wall MRI of the Carotid Arteries), a phase-sensitive DIR method has been implemented and tested in the carotid arteries of a healthy volunteer cohort. By exploiting the phase information of images acquired after DIR, the proposed phase-sensitive method enhances wall-lumen contrast while widens the window of opportunity for image acquisition. As a result, a 3-fold increase in volumetric coverage is obtained at no extra cost in scanning time, while image quality is improved. In conclusion, this thesis presented novel methods to address some of the main challenges for MRI of atherosclerosis: the suppression of motion and flow artifacts for improved visualization of vessel lumens, walls and plaques. Such methods showed to significantly improve image quality in human healthy sub¬jects, as well as scan efficiency and ease-of-use of MRI. Extensive validation is now warranted in patient populations to ascertain their diagnostic perfor¬mance. Eventually, these methods may bring the use of atherosclerosis MRI closer to the clinical practice. Résumé L'athérosclérose est une maladie cardiovasculaire chronique qui implique le épaississement de la paroi des artères, ainsi que la formation de plaques (lé¬sions) provoquant le rétrécissement des lumières, dans des vaisseaux tels que l'aorte, les coronaires et les artères carotides. L'imagerie par résonance magné¬tique (IRM) est une modalité prometteuse pour l'évaluation de l'athérosclérose, car il s'agit d'une procédure non-invasive et conviviale pour les patients, qui n'utilise pas des rayonnements ionisants. L'IRM offre un contraste des tissus mous très élevé sans avoir besoin de médias de contraste intraveineux, tan¬dis que la modification des séquences d'impulsions de RM permet en outre le réglage du contraste pour des besoins diagnostiques spécifiques. À ce titre, l'IRM peut créer des images angiographiques des lumières des vaisseaux pour évaluer les sténoses à la fin du stade de la maladie, ainsi que des images avec suppression du flux sanguin pour une première enquête des parois des vais¬seaux et une caractérisation des plaques d'athérosclérose. Cependant, malgré les grands progrès techniques qui ont eu lieu au cours des deux dernières dé¬cennies, l'IRM est une technique peu sensible et certaines limitations existent encore en termes de précision et de performance. Un des principaux défis pour l'imagerie de l'artère coronaire est le mou¬vement respiratoire. Les navigateurs diaphragmatiques de pointe comptent sur une mesure indirecte de mouvement, effectuent une correction 1D, et ont un temps d'acquisition long et imprévisible. En réponse, les stratégies d'auto- navigation (self-navigation: SN) ont été introduites récemment et offrent 100% d'efficacité d'acquisition et une meilleure facilité d'utilisation. Les SN détectent le mouvement respiratoire directement à partir des données brutes de l'image obtenue au niveau du coeur, et rétrospectivement corrigent ces mêmes données avant la reconstruction finale de l'image. Ainsi, les SN détiennent un poten¬tiel pour une compensation multidimensionnelle du mouvement. A cet égard, cette thèse présente de nouvelles méthodes SN qui estiment les paramètres de mouvement 2D et 3D à partir de sous-images qui sont obtenues à partir des mêmes données brutes qui composent l'image finale. La combinaison de toutes les sous-images corrigées produit une image finale pour la visualisation des coronaires ou les artefacts du mouvement sont réduits. La première étude (section 2.2,2D Self-Navigation with Compressed Sensing) traite d'une méthode pour une compensation 2D de mouvement de translation. Ici, on étudie l'utilisation de la reconstruction d'acquisition comprimée (compressed sensing: CS) pour soutenir la détection de mouvement en réduisant les artefacts de sous-échantillonnage. Chez des sujets humains sains, CS a démontré une amélioration de la précision de la détection de mouvement avec des simula¬tions sur des données in vivo, tandis que la visualisation de l'artère coronaire sur des acquisitions de respiration libre in vivo a aussi été améliorée. Pourtant, le mouvement du coeur induite par la respiration se produit en trois dimensions et il est plus complexe qu'un simple déplacement. Par conséquent, la deuxième étude (section 2.3, 3D Self-Navigation) traite d'une méthode de cor¬rection du mouvement 3D plutôt que 2D uniquement. Ici, différentes tech¬niques ont été adoptées pour réduire la contribution du signal du fond dans le suivi de mouvement respiratoire, qui peut être influencé négativement par le tissu statique qui entoure le coeur. La méthode proposée a démontré une amélioration, par rapport à la procédure classique SN de correction 1D, de la visualisation des artères coronaires dans le groupe de sujets sains et des pa¬tients avec maladies cardio-vasculaires. Dans la troisième étude (section 2.4,3D Self-Navigation with Compressed Sensing), les mêmes méthodes de suivi ont été utilisées pour obtenir des sous-images triées selon la position respiratoire. Au lieu de la correction du mouvement, une reconstruction de CS a été réalisée sur toutes les sous-images triées. Cette procédure exploite la cohérence des données pour réduire les artefacts de sous- échantillonnage de telle sorte que la sous-image correspondant à la phase de fin d'expiration peut directement être utilisée pour visualiser les coronaires. Dans un échantillon de volontaires en bonne santé, cette stratégie a amélioré la netteté et la visualisation des artères coronaires par rapport à une méthode classique SN ID. Pour la visualisation des parois des vaisseaux et de plaques d'athérosclérose, la technique de pointe avec double récupération d'inversion (DIR) est capa¬ble de supprimer le signal provenant du sang et de fournir un contraste posi¬tif entre la paroi et la lumière. Pourtant, il est difficile d'obtenir un contraste optimal car cela est soumis à la variabilité du rythme cardiaque. Par ailleurs, l'imagerie DIR est inefficace du point de vue du temps et les acquisitions "mul- tislice" peuvent conduire à des temps de scan prolongés. En réponse à ce prob¬lème et comme quatrième étude de cette thèse (chapitre 3, Vessel Wall MRI of the Carotid Arteries), une méthode de DIR phase-sensitive a été implémenté et testé

Extension of ultrasound Fourier slice Imaging theory to sectorial acquisition

Ultrasound image reconstruction from the echoes received by an ultrasound probe after the transmission of diverging waves is an active area of research because of its capacity to insonify at ultra-high frame rate with large regions of interest using small phased arrays as the ones used in echocardiography. Current state-of-the-art techniques are based on the emission of diverging waves and the use of delay and sum strategies applied on the received signals to reconstruct the desired image (DW/DAS). Recently, we have introduced the concept of Ultrasound Fourier Slice Imaging (UFSI) theory for the reconstruction of ultrafast imaging for linear acquisition. In this study, we extend this theory to sectorial acquisition thanks to the introduction of an explicit and invertible spatial transform. Starting from a diverging wave, we show that the direct use of UFSI theory along with the application of the proposed spatial transform allows reconstructing the insonified medium in the conventional Cartesian space. Simulations and experiments reveal the capacity of this new approach in obtaining competitive quality of ultrafast imaging when compared with the current reference method.

Gamma spectrometry and gamma and X-ray tomography of nuclear fuel

The purpose of gamma spectrometry and gamma and X-ray tomography of nuclear fuel is to determine both radionuclide concentration and integrity and deformation of nuclear fuel. The aims of this thesis have been to find out the basics of gamma spectrometry and tomography of nuclear fuel, to find out the operational mechanisms of gamma spectrometry and tomography equipment of nuclear fuel, and to identify problems that relate to these measurement techniques. In gamma spectrometry of nuclear fuel the gamma-ray flux emitted from unstable isotopes is measured using high-resolution gamma-ray spectroscopy. The production of unstable isotopes correlates with various physical fuel parameters. In gamma emission tomography the gamma-ray spectrum of irradiated nuclear fuel is recorded for several projections. In X-ray transmission tomography of nuclear fuel a radiation source emits a beam and the intensity, attenuated by the nuclear fuel, is registered by the detectors placed opposite. When gamma emission or X-ray transmission measurements are combined with tomographic image reconstruction methods, it is possible to create sectional images of the interior of nuclear fuel. MODHERATO is a computer code that simulates the operation of radioscopic or tomographic devices and it is used to predict and optimise the performance of imaging systems. Related to the X-ray tomography, MODHERATO simulations have been performed by the author. Gamma spectrometry and gamma and X-ray tomography are promising non-destructive examination methods for understanding fuel behaviour under normal, transient and accident conditions.

Performance assessment of the single photon emission microscope: high spatial resolution SPECT imaging of small animal organs

The single photon emission microscope (SPEM) is an instrument developed to obtain high spatial resolution single photon emission computed tomography (SPECT) images of small structures inside the mouse brain. SPEM consists of two independent imaging devices, which combine a multipinhole collimator, a high-resolution, thallium-doped cesium iodide [CsI(Tl)] columnar scintillator, a demagnifying/intensifier tube, and an electron-multiplying charge-coupling device (CCD). Collimators have 300- and 450-µm diameter pinholes on tungsten slabs, in hexagonal arrays of 19 and 7 holes. Projection data are acquired in a photon-counting strategy, where CCD frames are stored at 50 frames per second, with a radius of rotation of 35 mm and magnification factor of one. The image reconstruction software tool is based on the maximum likelihood algorithm. Our aim was to evaluate the spatial resolution and sensitivity attainable with the seven-pinhole imaging device, together with the linearity for quantification on the tomographic images, and to test the instrument in obtaining tomographic images of different mouse organs. A spatial resolution better than 500 µm and a sensitivity of 21.6 counts·s-1·MBq-1 were reached, as well as a correlation coefficient between activity and intensity better than 0.99, when imaging 99mTc sources. Images of the thyroid, heart, lungs, and bones of mice were registered using 99mTc-labeled radiopharmaceuticals in times appropriate for routine preclinical experimentation of <1 h per projection data set. Detailed experimental protocols and images of the aforementioned organs are shown. We plan to extend the instrument's field of view to fix larger animals and to combine data from both detectors to reduce the acquisition time or applied activity.

Rigid body dynamics and Kalman filtering

X-ray computed log tomography has always been applied for qualitative reconstructions. In most cases, a series of consecutive slices of the timber are scanned to estimate the 3D image reconstruction of the entire log. However, the unexpected movement of the timber under study influences the quality of image reconstruction since the position and orientation of some scanned slices can be incorrectly estimated. In addition, the reconstruction time remains a significant challenge for practical applications. The present study investigates the possibility to employ modern physics engines for the problem of estimating the position of a moving rigid body and its scanned slices which are subject to X-ray computed tomography. The current work includes implementations of the extended Kalman filter and an algebraic reconstruction method for fan-bean computer tomography. In addition, modern techniques such as NVidia PhysX and CUDA are used in current study. As the result, it is numerically shown that it is possible to apply the extended Kalman filter together with a real-time physics engine, known as PhysX, in order to determine the position of a moving object. It is shown that the position of the rigid body can be determined based only on reconstructions of its slices. However, the simulation of the body movement sometimes is subject to an error during Kalman filter employment as PhysX is not always able to continue simulating the movement properly because of incorrect state estimation.

Bioimage informatics in STED super-resolution microscopy

Optical microscopy is living its renaissance. The diffraction limit, although still physically true, plays a minor role in the achievable resolution in far-field fluorescence microscopy. Super-resolution techniques enable fluorescence microscopy at nearly molecular resolution. Modern (super-resolution) microscopy methods rely strongly on software. Software tools are needed all the way from data acquisition, data storage, image reconstruction, restoration and alignment, to quantitative image analysis and image visualization. These tools play a key role in all aspects of microscopy today – and their importance in the coming years is certainly going to increase, when microscopy little-by-little transitions from single cells into more complex and even living model systems. In this thesis, a series of bioimage informatics software tools are introduced for STED super-resolution microscopy. Tomographic reconstruction software, coupled with a novel image acquisition method STED< is shown to enable axial (3D) super-resolution imaging in a standard 2D-STED microscope. Software tools are introduced for STED super-resolution correlative imaging with transmission electron microscopes or atomic force microscopes. A novel method for automatically ranking image quality within microscope image datasets is introduced, and it is utilized to for example select the best images in a STED microscope image dataset.

Étude des artefacts en tomodensitométrie par simulation Monte Carlo

En radiothérapie, la tomodensitométrie (CT) fournit l’information anatomique du patient utile au calcul de dose durant la planification de traitement. Afin de considérer la composition hétérogène des tissus, des techniques de calcul telles que la méthode Monte Carlo sont nécessaires pour calculer la dose de manière exacte. L’importation des images CT dans un tel calcul exige que chaque voxel exprimé en unité Hounsfield (HU) soit converti en une valeur physique telle que la densité électronique (ED). Cette conversion est habituellement effectuée à l’aide d’une courbe d’étalonnage HU-ED. Une anomalie ou artefact qui apparaît dans une image CT avant l’étalonnage est susceptible d’assigner un mauvais tissu à un voxel. Ces erreurs peuvent causer une perte cruciale de fiabilité du calcul de dose. Ce travail vise à attribuer une valeur exacte aux voxels d’images CT afin d’assurer la fiabilité des calculs de dose durant la planification de traitement en radiothérapie. Pour y parvenir, une étude est réalisée sur les artefacts qui sont reproduits par simulation Monte Carlo. Pour réduire le temps de calcul, les simulations sont parallélisées et transposées sur un superordinateur. Une étude de sensibilité des nombres HU en présence d’artefacts est ensuite réalisée par une analyse statistique des histogrammes. À l’origine de nombreux artefacts, le durcissement de faisceau est étudié davantage. Une revue sur l’état de l’art en matière de correction du durcissement de faisceau est présentée suivi d’une démonstration explicite d’une correction empirique.