Modélisation pharmacocinétique en tomographie d'émission par positrons en utilisant la technique des ondelettes

Dans le cadre de ce travail de recherche, les objectifs étaient de mettre en oeuvre et de valider la technique des ondelettes dans la modélisation pharmacocinétique chez le rat par tomographie d'émission par positrons (TEP). En TEP, le métabolisme du glucose dans l'organe étudié est mesuré en injectant un analogue du glucose, le fluorodéoxyglucose ([indice supérieur 18]FDG). La quantité de radioactivité injectée est mesurée dans le plasma sanguin en fonction du temps et constitue la courbe d'entrée, tandis que la radioactivité mesurée dans les tissus à l'aide de la TEP constitue la réponse des tissus. Avec la courbe d'entrée et l'intensité de la radioactivité dans les tissus telle que mesurée par le tomographe, le métabolisme du glucose est calculé à l'aide d'un modèle mathématique compartimental. Ce calcul se fait habituellement sur des images reconstruites filtrées ou itérées. Cependant, ces images filtrées ont perdu la résolution spatiale ou contiennent encore du bruit dû à la faible dose de radioactivité injectée ou le temps restreint de la mesure. Dans ce travail, nous proposons la technique des ondelettes basée sur des algorithmes de compression et de filtrage qui s'avèrent performants et faciles à utiliser. De plus, à partir des images filtrées et compressées par les ondelettes, nous calculons le métabolisme du glucose pixel par pixel, afin de générer une image appelée l'image paramétrique qui permet une visualisation du métabolisme du glucose dans les différentes structures d'un organe. Nous avons appliqué la technique des ondelettes autant sur les images que sur les projections, c'est-à-dire directement sur les matrices de projections avant de reconstruire les images pour éviter le filtrage des mesures et les opérations de reconstruction. Les ondelettes ont l'avantage de réduire les matrices et de grouper les intensités des pixels, procurant une meilleure statistique, donc plus de précision, et par conséquent une meilleure qualité des images paramétriques. La technique des ondelettes a été introduite également pour la correction du volume partiel en imagerie TEP. L'effet du volume partiel survient lorsque la radioactivité des structures, dont la taille est inférieure à la résolution spatiale du tomographe, est sous-estimée. La méthode des ondelettes continues représente une alternative aux méthodes habituellement utilisées, basées sur les informations anatomiques qui proviennent de l'imagerie par résonance magnétique (IRM) ou de tomodensitométrie (TDM). L'approche des ondelettes continues consiste à caractériser les différentes structures par le couple échelle et position. En utilisant ces informations fournies par les ondelettes, toutes les intensités sous-estimées des petites structures sont rehaussées, ce qui permet d'améliorer la détection des lésions et des tumeurs en imagerie TEP. En conclusion, le travail de cette thèse démontre l'avantage de l'utilisation des ondelettes dans le calcul des paramètres physiologiques à partir des images et des sinogrammes TEP mesurés avec le [indice supérieur 18]FDG chez le rat. Enfin, les résultats obtenus sur les images avec les ondelettes ont montré moins de variation, moins de bruit tout en préservant la résolution spatiale. L'application de la transformée en ondelettes continues dans la correction de l'effet du volume partiel pour les images TEP en utilisant l'ondelette appropriée a montré le potentiel des ondelettes pour localiser les différentes structures permettant une bonne correction et une meilleure qualité d'image

Improvements in the registration of multimodal medical imaging : application to intensity inhomogeneity and partial volume corrections

Alignment or registration of medical images has a relevant role on clinical diagnostic and treatment decisions as well as in research settings. With the advent of new technologies for multimodal imaging, robust registration of functional and anatomical information is still a challenge, particular in small-animal imaging given the lesser structural content of certain anatomical parts, such as the brain, than in humans. Besides, patient-dependent and acquisition artefacts affecting the images information content further complicate registration, as is the case of intensity inhomogeneities (IIH) showing in MRI and the partial volume effect (PVE) attached to PET imaging. Reference methods exist for accurate image registration but their performance is severely deteriorated in situations involving little images Overlap. While several approaches to IIH and PVE correction exist these methods still do not guarantee or rely on robust registration. This Thesis focuses on overcoming current limitations af registration to enable novel IIH and PVE correction methods.El registre d'imatges mèdiques té un paper rellevant en les decisions de diagnòstic i tractament clíniques així com en la recerca. Amb el desenvolupament de noves tecnologies d'imatge multimodal, el registre robust d'informació funcional i anatòmica és encara avui un repte, en particular, en imatge de petit animal amb un menor contingut estructural que en humans de certes parts anatòmiques com el cervell. A més, els artefactes induïts pel propi pacient i per la tècnica d'adquisició que afecten el contingut d'informació de les imatges complica encara més el procés de registre. És el cas de les inhomogeneïtats d'intensitat (IIH) que apareixen a les RM i de l'efecte de volum parcial (PVE) característic en PET. Tot i que existeixen mètodes de referència pel registre acurat d'imatges la seva eficàcia es veu greument minvada en casos de poc solapament entre les imatges. De la mateixa manera, també existeixen mètodes per la correcció d'IIH i de PVE però que no garanteixen o que requereixen un registre robust. Aquesta tesi es centra en superar aquestes limitacions sobre el registre per habilitar nous mètodes per la correcció d'IIH i de PVE

PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques

Historically, anatomical CT and MR images were used to delineate the gross tumour volumes (GTVs) for radiotherapy treatment planning. The capabilities offered by modern radiation therapy units and the widespread availability of combined PET/CT scanners stimulated the development of biological PET imaging-guided radiation therapy treatment planning with the aim to produce highly conformal radiation dose distribution to the tumour. One of the most difficult issues facing PET-based treatment planning is the accurate delineation of target regions from typical blurred and noisy functional images. The major problems encountered are image segmentation and imperfect system response function. Image segmentation is defined as the process of classifying the voxels of an image into a set of distinct classes. The difficulty in PET image segmentation is compounded by the low spatial resolution and high noise characteristics of PET images. Despite the difficulties and known limitations, several image segmentation approaches have been proposed and used in the clinical setting including thresholding, edge detection, region growing, clustering, stochastic models, deformable models, classifiers and several other approaches. A detailed description of the various approaches proposed in the literature is reviewed. Moreover, we also briefly discuss some important considerations and limitations of the widely used techniques to guide practitioners in the field of radiation oncology. The strategies followed for validation and comparative assessment of various PET segmentation approaches are described. Future opportunities and the current challenges facing the adoption of PET-guided delineation of target volumes and its role in basic and clinical research are also addresse

Understanding Neural Networks in Awake Rat by Resting-State Functional MRI: A Dissertation

Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive neuroimaging technique that utilizes spontaneous low-frequency fluctuations of blood-oxygenation-level dependent (BOLD) signals to examine resting-state functional connectivity in the brain. In the past two decades, this technique has been increasingly utilized to investigate properties of large-scale functional neural networks as well as their alterations in various cognitive and disease states. However, much less is known about large-scale functional neural networks of the rodent brain, particularly in the awake state. Therefore, we attempted to unveil local and global functional connectivity in awake rat through a combination of seed-based analysis, independent component analysis and graph-theory analysis. In the current studies, we revealed elementary local networks and their global organization in the awake rat brain. We further systematically compared the functional neural networks in awake and anesthetized states, revealing that the rat brain was locally reorganized while maintaining global topological properties from awake to anesthetized states. Furthermore, specific neural circuitries of the rat brain were examined using resting-state fMRI. First anticorrelated functional connectivity between infralimbic cortex and amygdala were found to be evident with different preprocessing methods (global signal regression, regression of ventricular and white matter signal and no signal regression). Secondly the thalamocortical connectivity was mapped for individual thalamic groups, revealing group-specific functional cortical connections that were generally consistent with known anatomical connections in rat. In conclusion, large-scale neural networks can be robustly and reliably studied using rs-fMRI in awake rat, and with this technique we established a baseline of local and global neural networks in the awake rat brain as well as their alterations in the anesthetized condition

Content based retrieval of PET neurological images

Medical image management has posed challenges to many researchers, especially when the images have to be indexed and retrieved using their visual content that is meaningful to clinicians. In this study, an image retrieval system has been developed for 3D brain PET (Position emission tomography) images. It has been found that PET neurological images can be retrieved based upon their diagnostic status using only data pertaining to their content, and predominantly the visual content. During the study PET scans are spatially normalized, using existing techniques, and their visual data is quantified. The mid-sagittal-plane of each individual 3D PET scan is found and then utilized in the detection of abnormal asymmetries, such as tumours or physical injuries. All the asymmetries detected are referenced to the Talairarch and Tournoux anatomical atlas. The Cartesian co- ordinates in Talairarch space, of detected lesion, are employed along with the associated anatomical structure(s) as the indices within the content based image retrieval system. The anatomical atlas is then also utilized to isolate distinct anatomical areas that are related to a number of neurodegenerative disorders. After segmentation of the anatomical regions of interest algorithms are applied to characterize the texture of brain intensity using Gabor filters and to elucidate the mean index ratio of activation levels. These measurements are combined to produce a single feature vector that is incorporated into the content based image retrieval system. Experimental results on images with known diagnoses show that physical lesions such as head injuries and tumours can be, to a certain extent, detected correctly. Images with correctly detected and measured lesion are then retrieved from the database of images when a query pertains to the measured locale. Images with neurodegenerative disorder patterns have been indexed and retrieved via texture-based features. Retrieval accuracy is increased, for images from patients diagnosed with dementia, by combining the texture feature and mean index ratio value

In vivo and in vitro studies of the serotonin 1B receptor in relation to major depressive disorder and treatment with ketamine

Despite the large implications of Major Depressive Disorder (MDD) on disease burden worldwide, current treatment options are suboptimal and a third of patients suffering from this disease do not respond to treatment. Therefore, an unmet need exists for the development of new treatment options and methods to aid appropriate treatment selection in individual patients. Selection of suitable biomarkers and reliable quantification methods are essential steps in this process. In recent research on MDD, more interest has arisen for the serotonin 1B (5-HT1B) receptor and for ketamine as a new antidepressant treatment option. This thesis focuses on the involvement of the 5-HT1B receptor and the related protein p11 in the pathophysiology of MDD and the antidepressant mechanism of action of ketamine. For quantification of 5-HT1B receptor densities, the nuclear imaging techniques Autoradiography (ARG) and Positron Emission Tomography (PET) were used. This work includes the development and application of an improved method for quantification of 5-HT1B receptor binding using PET. Quantification of p11 levels was performed in specific cell populations using Flow Cytometry. In study I, 5-HT1B receptor binding densities and cortical distribution were examined using ARG in anterior cingulate cortex tissue of subjects with MDD, schizophrenia, bipolar disorder and healthy controls. Binding of the radioligand [3H]AZ10419369 in tissue of in total 52 subjects showed no significant differences between the subject groups. A distribution pattern with higher 5-HT1B receptor binding in supragranular layer compared to the infragranular layer was found, which correlated with glutamatergic N-methyl-D-aspartate receptor distribution. Female subjects had lower 5-HT1B receptor densities than male subjects, which was mostly profound in the MDD group. In study II, an improved method was developed for delineation of Volumes of Interest (VOIs) for PET data with the radioligand [11C]AZ10419369. Based on a 3D [3H]AZ10419369 ARG model in post mortem brainstem tissue and literature findings, appropriate VOIs for quantification in PET were selected. Two previously developed semi-automatic VOI delineation methods, based on template or individual data, were evaluated on test-retest data of 8 healthy subjects and showed improved reliability compared to a conventional manual VOI. The VOIs created with PET template data of 52 healthy subjects can be automatically applied to future PET studies measuring 5-HT1B receptor binding in the brainstem. Furthermore, in a randomized placebo-controlled study the effect of ketamine on cerebral [11C]AZ10419369 PET binding (study III) and peripheral p11 protein levels measured with Flow Cytometry (study IV) were examined in patients with Selective Serotonin Reuptake Inhibitor (SSRI) resistant MDD. An increase in 5-HT1B binding in the hippocampus and a decrease in p11 levels in both cytotoxic T cells and T-helper cells populations were seen in the ketamine group (n=20), although both did not differ from changes seen in the placebo group (n=10). Changes in Montgomery-Åsberg Depression Rating Scale (MADRS) score after ketamine treatment correlated significantly with baseline 5-HT1B receptor binding in the ventral striatum and baseline p11 levels in cytotoxic T cells. Future studies should be conducted on the role of 5-HT1B receptors and p11 in the antidepressant mechanism of action of ketamine and should clarify if these proteins could be used as biomarkers to predict ketamine treatment response in subjects with SSRI-resistant MDD