L’ostéoporose est définie par une diminution de la masse osseuse et une altération de la structure osseuse. L’évaluation de l’architecture de l’os trabéculaire vertébral est un des enjeux majeurs de recherche actuels visant à la caractérisation des modifications du tissu osseux liées au vieillissement. Par ailleurs, le traitement de la fracture vertébrale ostéoporotique par vertébroplastie a démontré son efficacité. Le ciment actuel utilisé pour la vertébroplastie est le polyméthylméthacrylate. Ce ciment est efficace pour stabiliser la vertèbre et diminuer la douleur mais il existe une toxicité pour les tissus mous avoisinant, notamment la moelle en cas de fuite, et des inquiétudes quant au risque de fracture des vertèbres adjacentes. De nouveaux ciments biointégrables du type ciments phosphocalciques supplémentés en bisphosphonates pourraient avoir leur place à l’avenir dans le traitement des vertèbres.Notre travail de thèse s’est inscrit dans un projet pluridisciplinaire de recherche sur les altérations de la structure de l’os trabéculaire vertébral, reposant sur une analyse en imagerie médicale et une étude biomécanique, et sur le développement d’un nouveau ciment phosphocalcique supplémenté en bisphosphonates.L’ensemble de nos résultats pourra nous permettre :-D’améliorer la prédiction du risque de fracture vertébrale ostéoporotique-D’optimiser les nouveaux ciments biointégrables / The current definition of osteoporosis is a low bone mass associated with a microarchitecture deterioration. Vertebral trabecular bone microarchitecture assessment is an important research topic aiming at the characterization of the modifications of the bone tissue bound to ageing. On the other hand, the vertebral fracture treatment by vertebroplasty is known to be effective. Currently the cement used in vertebroplasty is the polymethylmetacrylate (PMMA). This cement stabilizes the vertebral fracture and decreases the pain, but there are a toxicity for nearby soft tissues, in particular spinal marrow in case of leakage, and concerns as for the risk of fracture of the neighboring vertebrae. In the future, new biointegrable calcium phosphate cement supplemented in bisphosphonate could be used in the vertrebrae treatment.Our work was based on a multidisciplinary project which aimed firstly at evaluating trabecular vertebral bone microarchitecture using medical imaging and biomechanical testing in this crucial anatomical region, secondly at developing a new calcium phosphate cement supplemented in bisphosphonate. Our results may lead to:- improve the fracture risk prediction in osteoporotic vertebra- improve the new biointegrable cements

Les effets des agents anti-ostéoporotiques sur le tissu osseux sont évalués au niveau de la crête iliaque (CI) mais les réponses aux traitements peuvent varier selon le site osseux. Le but de cette étude était de comprarer les effets de l’acide zolérodronique (ZOL) et du tériparatide (TPTD) au niveau de la crête iliaque et de la vertèbre lombaire L1 (VL1) chez la brebis âgée. Le ZOL a induit une forte diminution du remodelage osseux et une augmentation des microendommagements au niveau des deux sites et une modification des crosslinks du collagène surtout au niveau de l’os cortical de la CI. Trois mois de TPTD ont augmenté le remodelage osseux uniquement au niveau de la VL1. En conclusion, les délais et les amplitudes de réponses au ZOL ou au TPTD diffèrent entre la CI et la VL1 chez la brebis. Ces résultats montrent l’importance de prendre en compte le site osseux pour évaluer les effets des agents anti-ostéoporotiques / The effects of anti-osteoporotic agents on bone tissue are evaluated on iliac crest (IC) but the answers to treatments may vary according to the skeletal site. The purpose of this study was to compare the effect of zoledronic acid (ZOL) and teriparatide (TPTD) on IC and lumbar vertebrae (LV1) in ewes. ZOL has induced a high decrease of bone remodeling, an increase in microdamages in both sites and a modification of collagen crosslinks mainly in cortical bone of IC. Three months of TPTD has increased the bone remodeling only in LV1. In conclusion, the delays and the magnitudes of responses to ZOL or to TPTD differ between IC and LV1 in ewes. These results show that the distinction of bone sites to study the early effects of antiosteoporotic therapies appears meaningful

This thesis deals with stress strain analysis of an aortic abdominal aneurysm (AAA) and the influence of its contact with the spine on the extreme wall stress. The influence was tested on the idealized geometry, as well as on ten patient specific geometries obtained from computer tomography (CT-A) scans. Hyperelastic constitutive models were used for the AAA wall and intraluminal thrombus (ILT) tissue description. The prestress algorithm was used for reconstruction of the unloaded geometry to get more trustworthy results against the geometry from CT which was obtained under the blood pressure. Statistical analysis was used for the results evaluation. The maximal increase of peak wall stress was as high as 81 %.

This master's thesis focuses on detection of pathological vertebrae in spinal CT utilized by machine learning. Theoretical part describes anatomy of the spine and occurrence of pathologies in CT image data, contains an overview of existing methods intended for automated detection of pathological vertebrae. Practical part devotes to design a computer aided detection systems to identify pathological vertebrae and to classify a type of pathology. Designed classification system is based on using neural network, which performs classification step and on principal component analysis (PCA), which is used to reducing the original number of observation features. For completing this task were used real data. Conclusion contains evaluation of obtained results.

The aim of this work was the development of algorithms for detection segmentation and classification of difficult to define bone metastatic cancerous lesions from spinal CT image data. For this purpose, the patient database was created and annotated by medical experts. Successively, three methods were proposed and developed; the first of them is based on the reworking and combination of methods developed during the preceding project phase, the second method is a fast variant based on the fuzzy k-means cluster analysis, the third method uses modern machine learning algorithms, specifically deep learning of convolutional neural networks. Further, an approach that elaborates the results by a subsequent random forest based meta-analysis of detected lesion candidates was proposed. The achieved results were objectively evaluated and compared with results achieved by algorithms published by other authors. The evaluation was done by two objective methodologies, technical voxel-based and clinical object-based ones. The achieved results were subsequently evaluated and discussed.