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Analysis of variance --- Estimation theory --- Analysis of variance. --- Estimation theory.
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The ability to non- invasively monitor tumor oxygenation and perfusion would be of great benefit in the design of treatment protocols in cancer therapy. Indeed, tumor cells in regions of poor perfusion are hypoxic and hence radioresistant. Moreover, the delivery of chemotherapeutic drugs will also depend on the state of the tumor vasculature.
Two types of hypoxia exist in tumors, namely chronic or diffusion-limited hypoxia and acute or perfusion limited hypoxia. The first one develops as a result of the more rapid expansion of tumor cells rather than the supporting vasculature, so that many tumor cells reside in areas largely inaccessible to O2. The second type of hypoxia develops as a result of substantial instability in microregional red cell flux which leads to changes in the partial pressure of oxygen in the surrounding tissue. It contributes to tumor progression and metastasis by providing repeated exposure of tumor cells to hypoxia-reoxygenation injuries. Moreover, acute hypoxia has proved to be of crucial importance as it adversely affects the sensitivity of the tumor to radiation and to chemotherapeutic agents. Up to now, there are no existing methods that are able to provide a non invasive mapping of the region with unstable flow.
In this study, the technique called functional Magnetic Resonance Imaging (fMRI), using gradient recalled echo sequences which are sensitive to local variations in the magnetic field, is used in order to map spatial and temporal changes of tumor oxygenation and/or blood flow which are associated to the perfusion limited hypoxia phenomenon. A voxel by voxel analysis is then realised using an in-house program based on the IDLTM software.
We demonstrated the feasibility of the method to differentiate the « physiological noise » in tumors from the noise due to scanner instabilities. The results show spontaneous fluctuations (betwen 0,00056 Hz and 0,0056 Hz) which occupy up to 56 % of the tumor surface with an average value of 28%. Tumor fluctuating voxels can be classify into two types in function of their frequencies and their spatial dependence: the first one consists in sequential signal increases and decreases and is observed in isolated voxels. The second one is a very low profound drop and concerned clusters of neighboring voxels. This study also reveals that fluctuations zones are not temporally constant. Among the two tested drugs (Nicotinamide and Pentoxifylline), only the nicotinamide induced a decrease in the percentage of fluctuations inside several tumors.
In conclusion, fMRI method provides a non-invasive measurement to detect spontaneous blood flow/ oxygen fluctuations in tumors. In the future, it could enable the clinician to optimize treatment protocols in cancer therapy La caractérisation de l’oxygénation et de la perfusion tumorales serait d’une aide précieuse pour l’élaboration de traitements anticancéreux. En effet, les cellules tumorales se trouvant au sein de régions peu perfusées sont hypoxiques et dès lors radiorésistantes. De plus, la distribution des substances chimiothérapeutiques est également influencée par la structure et la fonctionnalité des vaisseaux.
Deux types d’hypoxies tumorales existent : l’hypoxie chronique ou limitée par la diffusion de l’O2 et l’hypoxie aiguë ou limitée par la perfusion. Le premier type est dû à une prolifération trop rapide des cellules tumorales par rapport à la croissance vasculaire, conduisant ainsi à des régions tumorales où la quantité d’O2 est faible, voire nulle. Le deuxième type est quant à lui lié à des instabilités micro régionales de flux sanguin conduisant ainsi à des variations de pression partielle en O2 dans les tissus avoisinants. Ce dernier type contribue de manière importante au pouvoir pathogène de la tumeur, notamment en favorisant la croissance tumorale et les métastases ainsi qu’en modifiant la sensibilité tumorale aux radiations ionisantes et aux agents chimiothérapeutiques. Jusqu’à présent, aucune technique n’est capable de fournir, de façon non-invasive, une cartographie des régions tumorales ayant un flux instable.
Dans cette étude, la technique utilisée est l’Imagerie par Résonance Magnétique fonctionnelle (IRMf), basée sur des séquences gradient d’écho sensibles aux variations locales de champ magnétique. Elle permet la mise en évidence, à la fois dans le domaine spatial et temporel, des fluctuations de flux sanguin et/ou d’oxygénation liées au phénomène d’hypoxie aiguë dans la tumeur. Une analyse pixel par pixel est alors réalisée avec un programme informatique spécialement conçu pour détecter les pixels fluctuants.
L’étude réalisée met en évidence la capacité de la méthode à différentier les fluctuations physiologiques intra tumorales du bruit lié aux instabilités de l’imageur. Les résultats montrent que les fluctuations (comprises entre 0,00056 Hz et 0,0056 Hz) peuvent occuper jusqu’à 56% de la surface tumorale et en occupent en moyenne 28%. Les pixels fluctuants au sein de la tumeur sont classés en deux groupes en fonction de leur fréquence et de leur distribution spatiale: le premier consiste en des augmentations et des diminutions d’intensité de signal et est observé au niveau de pixels isolés. Le second est une diminution lente de l’intensité et concerne un ensemble de pixels. Cette étude révèle également que les zones de fluctuations ne sont pas constantes dans le temps. Parmi les deux substances pharmacologiques testées (Nicotinamide and Pentoxifylline), seule la nicotinamide a induit une diminution du pourcentage de fluctuations au sein de plusieurs tumeurs.
En conclusion, l’IRMf est une technique de mesure non-invasive qui permet la détection de fluctuations spontanées de flux sanguin et/ou d’O2 au sein des tumeurs. Dans le futur, elle devrait aider le clinicien à optimaliser les protocoles de traitement anticancéreux.
Magnetic Resonance Spectroscopy --- Anoxia --- Analysis of Variance
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Mathematical statistics --- Analysis of variance --- ANOVA (Analysis of variance) --- Variance analysis --- Experimental design
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Mathematical statistics --- Prediction theory --- Analysis of variance --- Analysis of variance. --- Prediction theory.
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This book provides a comprehensive, coherent, and intuitive review of panel data methodologies that are useful for empirical analysis. Substantially revised from the second edition, it includes two new chapters on modeling cross-sectionally dependent data and dynamic systems of equations. Some of the more complicated concepts have been further streamlined. Other new material includes correlated random coefficient models, pseudo-panels, duration and count data models, quantile analysis, and alternative approaches for controlling the impact of unobserved heterogeneity in nonlinear panel data models.
Econometrics --- Panel analysis --- Analysis of variance --- Econometrics. --- Panel analysis. --- Analysis of variance. --- BUSINESS & ECONOMICS --- Business & economics
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Analysis of variance --- Experimental design --- Sampling (Statistics) --- Analysis of variance. --- Experimental design. --- Sampling (Statistics).
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"Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. The new edition includes significant updating, over 300 exercises, stimulating chapter projects and model simulations, inclusion of R subroutines, and a revised text format. The target audience continues to be graduate students and researchers. An author-maintained web site is available with solutions to exercises and a compendium of relevant data sets"--
Analysis of variance --- Mathematics --- ANOVA (Analysis of variance) --- Variance analysis --- Mathematical statistics --- Experimental design
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