Gliomas are the most common primary tumors of the central nervous system believed to arise from glial cells. Invasive growth and inherent propensity for malignant progression make gliomas incurable despite extensive treatment. I have developed a life-like orthotopic glioma model and used this and other in vivo models to study basic mechanisms of glioma development and treatment. Previous studies had indicated that experimental gliomas could arise from glial stem cells and astrocytes. The present thesis describes the making and characterization of a novel mouse model, Ctv-a, where gliomas are induced from oligodendrocyte progenitor cells (OPCs). Our study shows that OPCs have the capacity to give rise to gliomas and suggests in light of previous data that the differentiation state of the cell of origin affects tumor malignancy. CDKN2A encodes p16INK4a and p14ARF (p19Arf in mouse) commonly inactivated in malignant glioma. Their roles in experimental glioma have been extensively studied and both proteins have tumor suppressor functions in glial stem cells and astrocytes. Here, we demonstrate that p19Arf only could suppress gliomagenesis in OPCs while p16Ink4a had no tumor suppressive effect. Functional DNA repair is pivotal for maintaining genome integrity, eliminating unsalvageable cells and inhibiting tumorigenesis. We have studied how RAD51, a central protein of homology-directed repair, affected experimental glioma development and have found that expression of RAD51 may protect against genomic instability and tumor development. Angiogenesis, the formation of new blood vessels from pre-existing ones, is a central feature of malignant progression in glioma. Antiangiogenic treatment by inhibition of vascular endothelial growth factor receptor signaling is used in the clinic for treatment of some cancers. We have investigated the effect of an alternative antiangiogenic protein, histidine-rich glycoprotein (HRG), on glioma development and found that HRG could inhibit the formation of malignant gliomas and completely prevent the formation of glioblastoma.

Medical imagery is increasingly evolving towards higher resolution and throughput. The increasing volume of data and the usage of multiple and often novel imaging modalities necessitates the use of mathematical and computational techniques for quicker, more accurate and more robust analysis of medical imagery. The fields of computer vision and machine learning provide a rich set of techniques that are useful in medical image analysis, in tasks ranging from segmentation to classification and population analysis, notably by integrating the qualitative knowledge of experts in anatomy and the pathologies of various disorders and making it applicable to the analysis of medical imagery going forward. The object of the proposed research is exactly to explore various computer vision and machine learning methods with a view to the improved analysis of multiple modalities of brain and cardiac imagery, towards enabling the clinical goals of studying schizophrenia, brain tumors (meningiomas and gliomas in particular) and cardiovascular disorders. In the first project, a framework is proposed for the segmentation of tubular, branched anatomical structures. The framework uses the tubular surface model which yields computational advantages and further incorporates a novel automatic branch detection algorithm. It is successfully applied to the segmentation of neural fiber bundles and blood vessels. In the second project, a novel population analysis framework is built using the shape model proposed as part of the first project. This framework is applied to the analysis of neural fiber bundles towards the detection and understanding of schizophrenia. In the third and final project, the use of mass spectrometry imaging for the analysis of brain tumors is motivated on two fronts, towards the offline classification analysis of the data, as well as the end application of intraoperative detection of tumor boundaries. SVMs are applied for the classification of gliomas into one of four subtypes towards application in building appropriate treatment plans, and multiple statistical measures are studied with a view to feature extraction (or biomarker detection). The problem of intraoperative tumor boundary detection is formulated as a detection of local minima of the spatial map of tumor cell concentration which in turn is modeled as a function of the mass spectra, via regression techniques.

Patients and methods: Malignant supratentorial glioma (anaplastic astrocytoma, oligoastrocytoma, oligodendroglioma and glioblastoma incl. gliosarcoma), age 16-70y, KPS 50-100. Postoperative randomization to chemotherapy with either BCNU (B) (80 mg/m2 x 3 every 6 weeks) alone or additional VM 26 (V) (50 mg/m2 x 3 every 6 weeks) starting concomitant with radiotherapy. Central histopathological review was required. Primary endpoints were survival time (ST) and progression free survival (PFS) . In addition confirmative analysis of prognostic factors and their interaction with therapy was performed. Results: Eligible: 501 of 522 randomized pts: 82% WHO grade IV gliomas, 18% grade III gliomas. 57% male, mean KPS 74, mean age 50.9 years. The high incidence of lung toxicity – with a cumulative risk of 19% during the first year - was alarming. Survival was not significantly different ( median 50.3 (B) versus 52.4 (V) (weeks), but an increase in long term survivors was observed (18 months: 29% B, 34% V, 5 years 5% B, 12% V) and PFS showed a significant difference with a median of 31.4 (B) versus 34.3 (V) weeks. Qualitative interaction between KPS and therapy (p < 0.01) was demonstrated: pts with a KPS ≥ 70 benefited from additional VM26, those with reduced KPS < 70 did better with BCNU-monotherapy. Conclusion: Adding VM26 to BCNU is effective in the chemotherapy of malignant gliomas. Because of the demonstrated interaction with therapy performance status, not tumor grade is the crucial factor to determine application and aggressiveness of chemotherapy. With risk adapted therapy a significant proportion of patients even with glioblastoma survive for years in good general condition. BCNU should be replaced by an equipotent alkylans to avoid the unacceptable high rate of lung toxicity.

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Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

La mentalisation, ou la capacité d’élaborer des hypothèses sur les états mentaux d’autrui, a fait l’objet de nombreuses études durant les 20 dernières années dans le champ des neurosciences sociales. Toutefois, les bases neurales de cette fonction particulièrement complexe restent mal comprises, notamment en termes de connectivité structurale. Récemment, une organisation anatomo-fonctionnelle en double voie a été proposée. Selon ce modèle, les aspects réflexifs, inférentiels, de la mentalisation seraient sous-tendus par le faisceau cingulaire. Les aspects préréflexifs, identificatoires, seraient médiés, quant à eux, par le complexe faisceau arqué/partie latérale du faisceau longitudinal supérieur (FLS). L’objectif général de ce travail est d’apporter des données originales sur l’organisation anatomo-fonctionnelle du réseau neural impliqué dans la mentalisation basée sur les visages. Pour ce faire, nous avons utilisé comme modèle physiopathologique d’étude le gliome diffus de bas grade. Cette tumeur cérébrale primitive s’avère particulièrement intéressante pour l’étude du rôle de la substance blanche dans la cognition et ce pour deux raisons : (i) les cellules tumorales se propagent préférentiellement le long des fibres blanches ; (ii) l’exérèse chirurgicale est souvent réalisée en condition éveillée avec cartographie fonctionnelle peropératoire pour permettre d’identifier, et ainsi de préserver, les structures fonctionnelles, notamment de substance blanche.Dans une première étude, grâce aux stimulations électriques peropératoires, nous avons pu identifier un vaste réseau cortico-sous-cortical impliqué dans la mentalisation. L’analyse des déconnexions induites par les stimulations de la substance blanche nous a permis de mettre clairement en évidence, et ce pour la première fois, le rôle du faisceau occipito-frontal inférieur (FOFI) tout en confirmant celui du FLS. Dans une deuxième étude, en utilisant des techniques de cartographie lésionnelle chez des patients ayant été opérés, nous avons démontré que les troubles permanents, non compensables, de la mentalisation étaient expliqués par l’atteinte du faisceau arqué. Enfin, dans une dernière étude, en combinant l’imagerie par résonance magnétique fonctionnelle de repos (IRMfr) et les sites corticaux démasqués pendant la chirurgie, nous avons pu générer de véritables cartographies fonctionnelles du réseau cortical de la mentalisation, très similaires à celles observées en imagerie fonctionnelle classique.De façon générale, nos découvertes suggèrent que la mentalisation basée sur les visages reposerait sur l’intégrité d’au moins deux faisceaux associatifs de substance blanche. Elles permettent également de valider l’utilisation combinée de l’IRMfr et des stimulations corticales en tant qu’approche originale pour cartographier les réseaux neurocognitifs.En plus de ces considérations fondamentales, nos résultats ont des implications cliniques, notamment pour la cartographie fonctionnelle peropératoire. Ils permettent en outre de mieux comprendre les pathologies cérébrales caractérisées par un trouble de la mentalisation et une atteinte des voies de substance blanche. / Mentalizing, or the ability of human beings to make assumptions about other people’s mental states, has been the subject of many studies over the last 20 years. The neural bases and especially the white matter connectivity of this complex cognitive function is still poorly understood. Recently, an anatomo-functional organization into two neural pathways has been proposed. According to this model, it is assumed that the reflective, inferential aspects of mentalizing is underpinned by the cingulum. The reflexive, identificatory aspects of mentalizing are thought to be mediated, for their part, by the arcuate fascicle and the lateral part of the superior longitudinal fascicle. The main purpose of this scientific work is to provide original data on the anatomo-functional organization of the neural network involved in the face-based mentalizing. We used as a pathophysiological study model diffuse low-grade gliomas. These primary brain tumors are particularly interesting for the study of the functional role of the white matter for two reasons: (i) the tumor cells propagate preferentially along the white matter fibers; (ii) the surgical resection is often performed in awake condition with intraoperative functional mapping to identify, and thus to preserve functional structures, including the white matter.In our first study, using intraoperative electrical stimulation, we were able to identify a large cortico-subcortical mentalizing network. The analysis of the disconnections induced by the stimulation of the white matter allowed us to clearly highlight, for the first time, the role of the inferior fronto-occipital fascicle. We also confirmed the already established role of the superior longitudinal fascicle in mentalizing. In a second study, using lesion mapping analyses in patients operated on for a diffuse low-grade glioma, we demonstrated that the long-term, non-compensatory mentalizing deficit was explained by the involvement of the arcuate fascicle. Finally, in a third study combining resting-state functional MRI and the cortical sites unmasked during surgery, we were able to identify a large cortical mentalizing networks, which were very similar to those identified by classical task-based functional imaging.In general, our findings suggest that the face-based mentalizing would require the integrity of at least two associative white matter fascicles. They also validate the combined use of resting-state functional MRI and direct cortical stimulations as an original approach to map neurocognitive networks.In addition to these fundamental considerations, our results have also clinical implications, especially regarding the intraoperative functional mapping. They also provide a better understanding of brain pathologies characterized by both mentalizing deficit and white matter impairment.

Low-grade gliomas (LGGs) constitute a major challenge for health care because of their location and nature. LGGs are often found in eloquent areas, and their infiltrative growth cause neurological reorganization, which complicates the mapping of important functions. Awake surgery in combination with direct electrical stimulation (DES) and intraoperative tests is a relatively new method for mapping the brain's functional limits, thus eliminating as much of the tumor as possible while maintaining important functions. At present there is no available intraoperative test for semantic processing in Swedish. Tests of specific linguistic abilities improves the specificity of mapping which reduces post-operative linguistic impairments. Intraoperative tests can thus contribute to increased quality of life in the patient group. This study was based on the Dutch Lingusistic Intraoperative Protocol (DuLIP) test battery to create a Swedish version of the subtest semantic odd word out (SOWO). SOWO tests semantic processing via lexical reading. The adjusted and extended version of SOWO was tested during a pilot trial on 26 standard-language people. The study has resulted in a new semantic intraoperative test in Swedish that will be clinically examined at University Hospital in Uppsala. Hopefully, the new test contributes to better treatment options for patients with LGG. / Lågmaligna tumörer (LGG) utgör en stor utmaning för vården på grund av deras lokalisation och karaktär. LGG återfinns ofta i elokventa områden och deras infiltrativa växtsätt orsakar neurologisk omorganisering, vilket komplicerar kartläggning av viktiga funktioner. Vakenkirurgi i kombination med direkt elektrisk stimulering (DES) och intraoperativa tester är en relativt ny metod för att kartlägga hjärnans funktionella gränser och därmed kunna avlägsna så stor del av tumören som möjligt samtidigt som viktiga funktioner kan bevaras. I dagsläget finns det inget tillgängligt intraoperativt test för semantisk bearbetning på svenska. Tester av specifika lingvistiska förmågor förbättrar specificiteten av kartläggningen vilket minskar postoperativa språkliga nedsättningar. Intraoperativa tester kan därmed bidra till ökad livskvalitet hos patientgruppen. Denna studie har utgått från det nederländska testbatteriet Dutch Lingusistic Intraoperative Protocol (DuLIP) för att skapa en svensk version av deltestet semantic odd word out (SOWO). SOWO testar semantisk bearbetning via lexikal läsning. Den anpassade och utökade versionen av SOWO pilottestades på 26 normalspråkiga personer. Studien har resulterat i ett nytt semantiskt intraoperativt test på svenska som ska prövas kliniskt på Akademiska sjukhuset i Uppsala. Förhoppningsvis bidrar det nya testet till bättre behandlingsmöjligheter för patienter med LGG.

Les travaux présentés dans le cadre de cette thèse traitent de la modélisation mathématique de la croissance tumorale. La première partie de cette thèse traite de l’estimation des paramètres. Plus précisément, il s’agit de déterminer la vascularisation d’une tumeur à partir de sa dynamique. Pour cela, nous générons à partir d’un modèle d’équations aux dérivées partielles l’évolution en temps de la densité de cellules tumorales. Ensuite, nous résolvons des problèmes inverses afin de retrouver la densité de vascularisation correspondante. Nous montrons que la vascularisation estimée permet de prédire efficacement la croissance future de la tumeur. Dans un second temps, nous introduisons une classe de modèles pour la croissance de gliomes qui sont adaptés à la fois aux gliomes de bas grades et aux glioblastomes multiformes. Afin de tenir compte des spécificités des gliomes, le modèle prend en considération le caractère infiltrant de ce type de tumeur ainsi que l’hétérogénéité, l’anisotropie et la géométrie du cerveau. Nos modèles permettent d’étudier l’efficacité des traitements anti-angiogéniques et de la comparer à celle d’un traitement qui inhiberait la capacité d’invasion de gliomes. Les modèles ont été implémentés en 2D et en 3D dans des géométries réalistes obtenues grâce à un atlas. / This thesis deals with mathematical modeling of tumor growth. Firstly, we present a parameter estimation method. More precisely, it consists in recovering the position of the tumor blood vessel, starting from imaging. The first step is to design a particular vascularization, then we compute the tumor growth with this blood-vessel network by using a model based on partial differential equations and hence we try to recover the initial vascularization solving the inverse problem. We show that the estimated vasculature could be used to efficiently predict the future tumor growth. In the second part of this thesis, we introduce a class of models dedicated to glioma, adapted both to low grade and multiform glioblastoma. In order to take into account their specificities, we include mainly two effects in the model : on the one hand, the infiltrate behaviors of gliomas, and on the other hand, the impact of brain heterogeneity, of brain anisotropy and of brain geometry on the tumor growth. Our models allow us to evaluate the efficiency of anti-angiogenic drugs and to compare it with the effect of drugs inhibiting the invasion ability of glioma. The models have been implemented in 2D and 3D in actual geometry provided by an atlas.

La néoangiogenèse tumorale est un élément pronostique de l’évolution de nombreux cancers. L’intégrine alphaVbeta3 ainsi que la métalloprotéase matricielle 9 (MMP-9), sont des marqueurs de ce processus. Leur ciblage offre la perspective d’une information diagnostique pour la détection précoce, l’évaluation de l’agressivité de pathologies et la sélection de patients répondeurs aux nouvelles thérapies anti-angiogéniques. Dans ce contexte, notre travail s’attèle à mettre au point les techniques nécessaires à la caractérisation de radiotraceurs. Des modèles de tumeurs richement néovascularisées ont été sélectionnés : le mélanome malin et le gliome malin. Nous nous sommes dans un premier temps intéressés à la détection de l’intégrine alphaVbeta3. Un traceur technétié, le 99mTc-DTPA-bis-c(RGDfK) a servi de support à la validation de nos techniques d’analyse. Cette méthodologie d’évaluation a ensuite été adaptée à des projets collaboratifs. L’étude du 18F-ribofuranose-RGD est réalisée avec le Centre de Recherche en Cancérologie de Toulouse (INSERM UMR 1037) et l’Institut des Sciences Moléculaires (CNRS UMR 5255). Un radioligand de la MMP-9, l’111In- DOTA-F3B, fait l’objet d’un partenariat avec l’ARNA (ARN : Régulations Naturelle et Artificielle, INSERM UMR 869) et l’Institut Lumière Matière (CNRS UMR 5306). Le composé technétié a démontré une bonne affinité et spécificité pour alphaVbeta3. In vivo, chez l’animal, les radioligands technétiés et fluorés ont permis l’identification de tumeurs alphaVbeta3 positives. L’111In-DOTA-F3B a, quant à lui, permis la visualisation de tumeurs chez l’animal et sur coupes tissulaires. Ces traceurs constituent une piste intéressante pour l’imagerie de la néoangiogenèse tumorale. / Tumor neoangiogenesis is a predictive element of the evolution of numerous cancers. AlphaVbeta3 integrin and matrix metalloprotease 9 (MMP-9) are markers of tumor neoangiogenesis. Their targeting appears of great interest either for early detection, aggressiveness staging of the disease or for selection of responders to new-targeted therapies. In this context, our objective is to develop methodologies needed for radiotracers characterization. Tracers have been investigated in different tumor models for which vascularization is very important: melanoma and glioma. First of all 99mTc-DTPA-bis-c(RGDfK) has been assessed in our laboratory and helped us to develop analytical methods. These methodologies were used in different partnership, the evaluation of 18F-ribofuranose-RGD targeting alphaVbeta3 with INSERM UMR 1037 and CNRS UMR 5255, and 111In-DOTA-F3B for molecular imaging of MMP-9 with INSERM UMR 869 and CNRS UMR 5306.The technetium peptide has demonstrated good affinity and specificity for alphaVbeta3. In vivo analysis in mice showed that both tracers were able to identify some alphaVbeta3-positive tumors. 111In-DOTA-F3B allowed us to detect hMMP-9 positive tumors in mice and in tumor tissue sections. In conclusion, these tracers still require to be investigated but represent promising tracers for tumor neoangiogenesis.

Cette thèse s'intéresse au développement de méthodes automatiques pour la segmentation et la synthèse d'images par résonance magnétique de tumeurs cérébrales. La principale perspective clinique de la segmentation des gliomes est le suivi de la vitesse d'expansion diamétrique dans le but d'adapter les solutions thérapeutiques. A cette fin, la thèse formalise au moyen de modèles graphiques probabilistes des approches de segmentation multi-atlas fondées sur l'appariement de blocs de voxels. Un premier modèle probabiliste prolonge à la segmentation automatique de régions cérébrales pathologiques les approches multi-atlas classiques de segmentation de structures anatomiques. Une approximation de l'étape de marginalisation remplace la notion de fenêtre de recherche locale par un tamisage par atlas et par étiquette. Un modèle de détection de gliomes fondé sur un a priori spatial et des critères de pré-sélection de blocs de voxels permettent d'obtenir des temps de calcul compétitifs malgré un appariement non local. Ce travail est validé et comparé à l'état de l'art sur des bases de données publiques. Un second modèle probabiliste, symétrique au modèle de segmentation, simule des images par résonance magnétique de cas pathologiques, à partir d'une unique segmentation. Une heuristique permet d'estimer le maximum a posteriori et l'incertitude du modèle de synthèse d'image. Un appariement itératif des blocs de voxels renforce la cohérence spatiale des images simulées. Le réalisme des images simulées est évalué avec de vraies IRM et des simulations de l'état de l'art. Le raccordement d'un modèle de croissance de tumeur permet de créer des bases d'images annotées synthétiques. / This thesis focuses on the development of automatic methods for the segmentation and synthesis of brain tumor Magnetic Resonance images. The main clinical perspective of glioma segmentation is growth velocity monitoring for patient therapy management. To this end, the thesis builds on the formalization of multi-atlas patch-based segmentation with probabilistic graphical models. A probabilistic model first extends classical multi-atlas approaches used for the segmentation of healthy brains structures to the automatic segmentation of pathological cerebral regions. An approximation of the marginalization step replaces the concept of local search windows with a stratification with respect to both atlases and labels. A glioma detection model based on a spatially-varying prior and patch pre-selection criteria are introduced to obtain competitive running times despite patch matching being non local. This work is validated and compared to state-of-the-art algorithms on publicly available datasets. A second probabilistic model mirrors the segmentation model in order to synthesize realistic MRI of pathological cases, based on a single label map. A heuristic method allows to solve for the maximum a posteriori and to estimate uncertainty of the image synthesis model. Iterating patch matching reinforces the spatial coherence of synthetic images. The realism of our synthetic images is assessed against real MRI, and against outputs of the state-of-the-art method. The junction of a tumor growth model to the proposed synthesis approach allows to generate databases of annotated synthetic cases.