1,721,090 research outputs found
18F-FDG PET/CT en oncologie : contribution \ue0 la caract\ue9risation tumorale par analyse quantitative du signal 18F-FDG PET/CT in oncology: contribution to the tumor characterization using quantitative analysis of the signal
No full textRobustness of intra-tumor 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in esophageal carcinoma
No full textInternational audiencePurpose: Intratumour uptake heterogeneity in PET quantified in terms of textural features for response to therapy has been investigated in several studies, including assessment of their robustness for reconstruction and physiological reproducibility. However, there has been no thorough assessment of the potential impact of preprocessing steps on the resulting quantification and its predictive value. The goal of this work was to assess the robustness of PET heterogeneity in textural features for delineation of functional volumes and partial volume correction (PVC. Methods: This retrospective analysis included 50 patients with oesophageal cancer. PVC of each PET image was performed. Tumour volumes were determined using fixed and adaptive thresholding, and the fuzzy locally adaptive Bayesian algorithm, and heterogeneity was quantified using local and regional textural features. Differences in the absolute values of the image-derived parameters considered were assessed using Bland-Altman analysis. The impact on their predictive value for the identification of patient nonresponders was assessed by comparing areas under the receiver operating characteristic curves. Results: Heterogeneity parameters were more dependent on delineation than on PVC. The parameters most sensitive to delineation and PVC were regional ones (intensity variability and size zone variability), whereas local parameters such as entropy and homogeneity were the most robust. Despite the large differences in absolute values obtained from different delineation methods or after PVC, these differences did not necessarily translate into a significant impact on their predictive value. Conclusion: Parameters such as entropy, homogeneity, dissimilarity (for local heterogeneity characterization) and zone percentage (for regional characterization) should be preferred. This selection is based on a demonstrated high differentiation power in terms of predicting response, as well as a significant robustness with respect to the delineation method used and the partial volume effects
4D reconstruction including radiopharmaceutical modeling in PET/CT imaging
No full textL'imagerie TEP permet de mesurer et visualiser les changements de la distribution biologique des radiopharmaceutiques au sein des organes d'intérêt au court du temps. Ce suivi temporel offre des informations très utiles concernant les processus métaboliques et physiologiques sous-jacents, qui peuvent être extraites grâce à différentes techniques de modélisation cinétique. De plus, un autre avantage de la prise en compte de l'information temporelle dans les acquisitions TEP pour les examens en oncologie thoracique concerne le suivi des mouvements respiratoires. Ces acquisitions permettent de mettre en place des protocoles et des méthodologies visant à corriger leurs effets néfastes à la quantification, et les artefacts associés. L'objectif de ce projet est de développer une méthode de reconstruction permettant de combiner et mettre en oeuvre d'une part les corrections nécessaires à la quantification des données en TEP, et d'autre part la modélisation de la biodistribution du radiotraceur au cours du temps permettant d'obtenir des images paramétriques pour l'oncologie thoracique. Dans un premier temps, une méthodologie de correction des effets de volume partiel intégrant, dans le processus de reconstruction, une déconvolution de Lucy-Richardson associée à un débruitage dans le domaine des ondelettes, a été proposée. Une seconde étude a été consacrée au développement d'une méthodologie combinant une régularisation temporelle des données par l'intermédiaire d'un ensemble de fonctions de base temporelles, avec une méthode de correction des mouvements respiratoires basée sur un modèle élastique. Enfin, dans une troisième étape, le modèle cinétique de Patlak a été intégré dans un algorithme de reconstruction dynamique, et associé à la correction de mouvement afin de permettre la reconstruction directe d'images paramétriques de données thoraciques soumises au mouvement respiratoire. Les paramètres de transformation élastique pour la correction de mouvement ont été calculés à partir des images TEP d'intervalles synchronisés par rapport à l'amplitude de la respiration du patient. Des simulations Monte-Carlo d'un fantôme 4D géométrique avec plusieurs niveaux de statistiques, et du fantôme anthropomorphique NCAT intégrant des courbes d'activités temporelles réalistes pour les différents tissus, ont été réalisées afin de comparer les performances de la méthode de reconstruction paramétrique développée dans ce travail avec une approche 3D standard d'analyse cinétique. L'algorithme proposé a ensuite été testé sur des données cliniques de patients présentant un cancer bronchique non à petites cellules. Enfin, après la validation indépendante de l'algorithme de correction des effets de volume partiel d'une part, et de la reconstruction 4D incorporant la régularisation temporelle d'autre part, sur données simulées et cliniques, ces deux méthodologies ont été associées afin d'optimiser l'estimation de la fonction d'entrée à partir d'une région sanguine des images reconstruites. Les résultats de ce travail démontrent que l'approche de reconstruction paramétrique proposée permet de conserver un niveau de bruit stable dans les régions tumorales lorsque la statistique d'acquisition diminue, contrairement à l'approche d'estimation 3D pour laquelle le niveau de bruit constaté augmente. Ce résultat est intéressant dans l'optique d'une réduction de la durée des intervalles de la reconstruction 4D, permettant ainsi de réduire la durée totale de l'acquisition 4D. De plus, l'utilisation des fonctions d'entrée estimées avec les méthodes de régularisation temporelle proposées ont conduit à améliorer l'estimation des paramètres de Patlak. Enfin, la correction élastique du mouvement amène à une diminution du biais d'estimation des deux paramètres de Patlak, en particulier sur les tumeurs de petites dimensions situées dans des régions sensibles au mouvement respiratoire.Positron emission tomography (PET) is now considered as the gold standard and the main tool for the diagnosis and therapeutic monitoring of oncology patients, especially due to its quantitative aspects. With the advent of multimodal imaging in combined PET and X-ray CT systems, many methodological developments have been proposed in both pre-processing and data acquisition, image reconstruction, as well as post-processing in order to improve the quantification in PET imaging. Another important aspect of PET imaging is its high temporal resolution and ability to perform dynamic acquisitions, benefiting from the high sensitivity achieved with current systems. PET imaging allows measuring and visualizing changes in the biological distribution of radiopharmaceuticals within the organ of interest over time. This time tracking provides valuable information to physicians on underlying metabolic and physiological processes, which can be extracted using pharmacokinetic modeling. The objective of this project is, by taking advantage of dynamic data in PET/CT imaging, to develop a reconstruction method combining in a single process all the correction methodology required to accurately quantify PET data and, at the same time, include a pharmacokinetic model within the reconstruction in order to create parametric images for applications in oncology. In a first step, a partial volume effect correction methodology integrating, within the reconstruction process, the Lucy-Richardson deconvolution algorithm associated with a wavelet-based denoising method has been introduced. A second study focused on the development of a 4D reconstruction methodology performing temporal regularization of the dataset through a set of temporal basis functions, associated with a respiratory motion correction method based on an elastic deformation model. Finally, in a third step, the Patlak kinetic model has been integrated in a dynamic image reconstruction algorithm and associated with the respiratory motion correction methodology in order to allow the direct reconstruction of parametric images from dynamic thoracic datasets affected by the respiratory motion. The elastic transformation parameters derived for the motion correction have been estimated from respiratory-gated PET images according to the amplitude of the patient respiratory cycle. Monte-carlo simulations of two phantoms, a 4D geometrical phantom, and the anthropomorphic NCAT phantom integrating realistic time activity curves for the different tissues, have been performed in order to compare the performances of the proposed 4D parametric reconstruction algorithm with a standard 3D kinetic analysis approach. The proposed algorithm has then been assessed on clinical datasets of several patients with non small cell lung carcinoma. Finally, following the prior validation of the partial volume effect correction algorithm on one hand, and the 4D reconstruction incorporating the temporal regularization on the other hand, on simulated and clinical datasets, these two methodologies have been associated within the 4D reconstruction algorithm in order to optimize the estimation of image derived input functions. The results of this work show that the proposed direct parametric approach allows to maintain a similar noise level in the tumor regions when the statistic decreases, contrary to the 3D estimation approach for which the observed noise level increases. This result suggests interesting perspectives for the reduction of frame duration reduction of 4D reconstruction, allowing a reduction of the total 4D acquisition duration. In addition, the use of input function estimated with the developed temporal regularization methods led to the improvement of the Patlak parameters estimation. Finally, the elastic respiratory motion correction led to a diminution of the estimation bias of both Patlak parameters, in particular for small lesions located in regions affected by the respiratory motion
Valeur pronostique de la TEP-TDM au 18F-FluoroDéoxyGlucose dans les cancers broncho-pulmonaires non à petites cellules non métastatiques (apport de paramètres avancés)
No full textObjectif : La distribution du 18 F-FDG au sein d'une lésion tumorale est un paramètre envisagé depuis peu pour caractériser les lésions en TEP. Plusieurs études ont montré son intérêt pronostique dans différents modèles tumoraux. L'objectif de cette étude est de comparer dans les cancers broncho-pulmonaires non à petites cellules non métastatiques (CBPNPC) la valeur pronostique des facteurs clinico-biologiques usuels et les paramètres dérivés de l'imagerie TEP tels que le volume, l'intensité de fixation et l'hétérogénéité de fixation qu'elle soit appréciée visuellement ou caractérisée avec l'analyse de texture. Matériels et méthodes : 122 patients atteints d'un CBPNPC de stade I à III ont été inclus dans une étude rétrospective de 2008 à 2011 (92 hommes, 30 femmes, âge moyen : 66 ans). Tous les patients avaient bénéficié d'une TEP-TDM au 18F-FDG avant traitement dans le cadre du bilan d'extension. Après le traitement initial, les patients ont été suivis régulièrement de façon usuelle. L'apport pronostique en termes de survie sans progression et de survie globale de 6 paramètres quantitatifs d'hétérogénéité, du SUV max, du volume tumoral métabolique actif (MATV) et du Total Lesion Glycolysis (TLG) a été évalué. L'hétérogénéité a été également appréciée visuellement en aveugle par deux observateurs, en utilisant 3 classes : distribution homogène, intermédiaire et hétérogène. Résultats : L'analyse multi variée montre que le stade TNM (p=0,01) est un facteur prédictif indépendant de la survie globale et sans progression. Certains paramètres d'hétérogénéité quantitative (la déviation standard et l'inhomogénéité) ainsi que le volume tumoral métabolique actif et le TLG sont également prédictifs de la survie et tendent même à être des facteurs pronostiques indépendants. Il existe par ailleurs une bonne concordance inter-observateur pour l'analyse visuelle de l'hétérogénéité tumorale avec une valeur de Kappa pondéré de 0.683. Cette analyse visuelle est également bien corrélée à l'analyse quantitative de la texture des images, mais sa valeur pronostique reste limitée. Conclusion : L'hétérogénéité de la distribution intra tumorale du 18F-FDG en TEP-TDM semble être un facteur pronostique prometteur chez les patients atteints d'un CBPNPC de stade I à III. Son appréciation visuelle semble moins pertinente que l'analyse de texture pour prédire le devenir des patients.POITIERS-BU Médecine pharmacie (861942103) / SudocSudocFranceF
PET Uptake Heterogeneity Quantification for Therapy Response in Oncology: Dependency on Image Pre-processing and Tumor Delineation
No full textInternational audienc
Impact of Delineation and Partial Volume Effects Correction on PET Uptake Heterogeneity Quantification Through Textural Features Analysis for Therapy Response in Oncology
No full textInternational audiencePurpose: characterization of intra tumoral tracer uptake heterogeneity in PET imaging for response to therapy assessment applications in oncology has been investigated in several recent studies. The use of textural features to quantify this heterogeneity has shown promising results for response to therapy prediction. However, there is no study available yet regarding the potential impact of pre-processing steps on the resulting heterogeneity quantification. The goal of this work was therefore to assess the dependency of heterogeneity parameters obtained through textural features on delineation and partial volume effects (PVE) correction (PVC). Methods: fifty patients with esophageal cancer were retrospectively analyzed. PVC of each FDG PET image was performed using iterative deconvolution with wavelet-based denoising. The tumors were delineated using fixed (FT) and adaptive thresholding (AT), and the fuzzy locally adaptive Bayesian (FLAB) algorithm. From the resulting delineations, uptake heterogeneity was quantified using the following features, selected for their reproducibility and robustness: entropy (E), homogeneity (H), dissimilarity (D), intensity variability (IV), size-zone variability (SZV) and high intensity emphasis (HIE). The results obtained with FLAB (the most accurate) on the non-corrected image were chosen as reference. Variability with respect to this reference depending on delineation or PVC was assessed using Bland-Altman analysis. Impact on the associated predictive value regarding the identification on non-responders was assessed by comparing areas under the receiver operating characteristic curves. Results: heterogeneity parameters were more dependent on delineation than PVC. The most sensitive parameters were IV and SZV (90-100% variability). The most independent were E, H and HIE (10-50%). The impact on the corresponding predictive value was not significant, except for SZV and HIE after deconvolution (p<0.04). Conclusion: some heterogeneity parameters were highly sensitive on pre-processing steps, whereas others such as entropy and homogeneity could be derived with high reliability independently on delineation or PVC
Respiratory motion on Functional Imaging in Oncology: a review of the effects and correction methodologies
No full textA number of different parameters inherent in the PET detection process are contributing to a reduction in the
quantitative accuracy of PET images. On the other hand, patient motion during imaging has been shown to cause
significant artefacts leading to reduced image quality and quantitative accyracy. These effects are particularly important
during imaging in thorax and abdomen where physiological motion associated with cardiac, respiratory and GI tract is
significant. Respiratory motion effects in emission tomography imaging lead to a loss of sensitivity in the detection of
disease as a result of the associated blurring. Furthermore, respiration causes significant changes in the volumes and
activity concentrations of tumours predominantly in the lower thorax and upper abdomen, influencing this way the
quantitative accuracy of PET images and subsequently its progress in new application domains such as radiotherapy
treatment planning and therapy monitoring. Research in the area of respiratory motion detection and correction especially for emission tomography applications has grown significantly over the last few years. Proposed methodologies
to correct for the respiratory motion are based on dynamic gated acquisitions. Furthermore image reconstruction
algorithms incorporating respiratory motion compensation have been recently developed. The objectives of this paper
are to present a review of current techniques in respiratory motion correction and detection for emission tomography,
with a particular focus on oncology applications and PET imaging.De nombreux paramètres inhérents à la détection en Tomographie par Emission de Positons (TEP) influent sur
la qualité des images. Le mouvement du patient pendant l'examen produit également d'importants artefacts
qui réduisent la qualité des images. Ces effets sont particulièrement importants lors de l'imagerie du thorax
et de l'abdomen où on ne peut s'affranchir des mouvements physiologiques du coeur et des poumons.
Le mouvement respiratoire produit en particulier un bruit qui réduit la sensibilité de détection des lésions. De
plus, la respiration modifie les volumes et les concentrations d'activité des tumeurs essentiellement dans le
bas du thorax et le haut de l'abdomen, influençant ainsi les données quantitatives des images TEP
reconstruites. La recherche dans le domaine de la détection et de la correction des mouvements respiratoires
pour des applications en tomographie d'émission est très réactive. Les méthodologies généralement
proposées pour corriger le mouvement respiratoire sont basées sur l'utilisation d'acquisitions dynamiques
synchronisées sur la respiration. Néanmoins récemment de nouveaux algorithmes de reconstruction
permettant de compenser les effets du mouvement respiratoire ont vu le jour. Les objectifs de cette étude
sont de faire une revue des méthodologies actuelles dans le domaine de la compensation du mouvement
respiratoire en tomographie d'émission, tout en portant un accent particulier sur les applications oncologiques
et de l'imagerie TEP
PET Uptake Heterogeneity Quantification for Therapy Response in Oncology: Dependency on Image Pre-processing and Tumor Delineation
No full textInternational audienc
Functional tumor shape characterization on baseline 18F FDG PET omages predicts response to concomitant radio chemotherapy in esophageal cancer
No full textInternational audiencePurpose: The development of robust 18F-FDG PET tumor volume delineation methodologies has led to the investigation of several image-derived parameters for tumor characterization, including metabolic tumor volume (MTV), total lesion glycolysis (TLG), and tracer heterogeneity quantification. Their potential clinical value regarding patient outcome (response to therapy and/or survival) prediction has been recently investigated in several cancer models. They have often demonstrated superior value over standard measurements such as SUVmax or SUVpeak. However, the value of shape characterization (SC) parameters has not been extensively investigated as yet. We therefore studied the predictive value of 7 parameters derived from SC of PET image functional tumor activity distributions within the context of esophageal cancer treated by concomitant radio-chemotherapy. Methods: Baseline 18F-FDG PET scans of 50 patients with locally advanced esophageal cancer were retrospectively analyzed. Primary tumors were delineated with the fuzzy locally adaptive bayesian algorithm and 7 features describing the shape of the delineated volumes were extracted. Response to therapy (complete (CR), partial (PR) and non-response (NR)) was evaluated according to RECIST criteria 1 month after the end of treatment. The correlation between SC parameters was assessed using Pearson coefficients and their corresponding predictive value was evaluated with receiver operating characteristic (ROC) curves analysis. Results: 3D surface and MTV were highly correlated (r=0.97). All other SC parameters were moderately correlated (r<0.75). Maximum diameter within the MTV, as well as the smoothness of its surface allowed the identification of NR (vs. PR+CR) or CR (vs. PR+NR) with areas under the ROC curves of 0.78 and 0.80 respectively. Conclusion: Baseline PET image derived parameters characterizing the shape of the functional tumor uptake may help in predicting response to radio-chemotherapy in locally advanced esophageal cancer. Future studies will investigate their potential combination with other parameters previously demonstrated as predictive of response, such as intra-tumor heterogeneity quantificatio
Compliant Secured Specialized Electronic Patient Record Platform
No full textInternational audienceDistributed medical information systems are prone to security flaws at three main different levels: storage, processing and transmission. Among implemented security mechanisms, few con cern intrinsic patien t records multimedia content protection. This art icle presents a S ecured Specialized Electronic Patient Record (SSEPR) based on a JPEG2000- XML structure designed to pr ovide interaction with the Medical Information System (MIS ) security mech anisms and policies. Such SSEPR is an Elect ronic Patient Record (EPR) elementary resource, containing data and information generated by daily practice in a technical medical unit, grouping information that belongs to one patient examination (images, examination data, medical report). Devoted to be handled and shared, it integr ates different security attributes that are used to certify infor mation reliability (information integrity and authenticity), while controlling information access in a compliant MIS. Aiming to be as generic as possible, the presented SSEPR and its platform prototype have been developed in the framework of a nuclear medicine service. Properly defined, EPR security layer can be used to improve security in handling and sharing medical information
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