Automatic image analysis of C-arm Computed Tomography images for ankle joint surgeries

Open reduction and internal fixation is a standard procedure in ankle surgery for treating a fractured fibula. Since fibula fractures are often accompanied by an injury of the syndesmosis complex, it is essential to restore the correct relative pose of the fibula relative to the adjoining tibia for the ligaments to heal. Otherwise, the patient might experience instability of the ankle leading to arthritis and ankle pain and ultimately revision surgery. Incorrect positioning referred to as malreduction of the fibula is assumed to be one of the major causes of unsuccessful ankle surgery. 3D C-arm imaging is the current standard procedure for revealing malreduction of fractures in the operating room. However, intra-operative visual inspection of the reduction result is complicated due to high inter-individual variation of the ankle anatomy and rather based on the subjective experience of the surgeon. A contralateral side comparison with the patient’s uninjured ankle is recommended but has not been integrated into clinical routine due to the high level of radiation exposure it incurs. This thesis presents the first approach towards a computer-assisted intra-operative contralateral side comparison of the ankle joint. The focus of this thesis was the design, development and validation of a software-based prototype for a fully automatic intra-operative assistance system for orthopedic surgeons. The implementation does not require an additional 3D C-arm scan of the uninjured ankle, thus reducing time consumption and cumulative radiation dose. A 3D statistical shape model (SSM) is used to reconstruct a 3D surface model from three 2D fluoroscopic projections representing the uninjured ankle. To this end, a 3D SSM segmentation is performed on the 3D image of the injured ankle to gain prior knowledge of the ankle. A 3D convolutional neural network (CNN) based initialization method was developed and its outcome was incorporated into the SSM adaption step. Segmentation quality was shown to be improved in terms of accuracy and robustness compared to the pure intensity-based SSM. This allows us to overcome the limitations of the previously proposed methods, namely inaccuracy due to metal artifacts and the lack of device-to-patient orientation of the C-arm. A 2D-CNN is employed to extract semantic knowledge from all fluoroscopic projection images. This step of the pipeline both creates features for the subsequent reconstruction and also helps to pre-initialize the 3D-SSM without user interaction. A 2D-3D multi-bone reconstruction method has been developed which uses distance maps of the 2D features for fast and accurate correspondence optimization and SSM adaption. This is the central and most crucial component of the workflow. This is the first time that a bone reconstruction method has been applied to the complex ankle joint and the first reconstruction method using CNN based segmentations as features. The reconstructed 3D-SSM of the uninjured ankle can be back-projected and visualized in a workflow-oriented manner to procure clear visualization of the region of interest, which is essential for the evaluation of the reduction result. The surgeon can thus directly compare an overlay of the contralateral ankle with the injured ankle. The developed methods were evaluated individually using data sets acquired during a cadaver study and representative clinical data acquired during fibular reduction. A hierarchical evaluation was designed to assess the inaccuracies of the system on different levels and to identify major sources of error. The overall evaluation performed on eleven challenging clinical datasets acquired for manual contralateral side comparison showed that the system is capable of accurately reconstructing 3D surface models of the uninjured ankle solely using three projection images. A mean Hausdorff distance of 1.72 mm was measured when comparing the reconstruction result to the ground truth segmentation and almost achieved the high required clinical accuracy of 1-2 mm. The overall error of the pipeline was mainly attributed to inaccuracies in the 2D-CNN segmentation. The consistency of these results requires further validation on a larger dataset. The workflow proposed in this thesis establishes the first approach to enable automatic computer-assisted contralateral side comparison in ankle surgery. The feasibility of the proposed approach was proven on a limited amount of clinical cases and has already yielded good results. The next important step is to alleviate the identified bottlenecks in the approach by providing more training data in order to further improve the accuracy. In conclusion, the new approach presented gives the chance to guide the surgeon during the reduction process, improve the surgical outcome while avoiding additional radiation exposure and reduce the number of revision surgeries in the long term

Pinning down loosened prostheses : imaging and planning of percutaneous hip refixation

This thesis examines how computer software can be used to analyse medical images of an aseptically loosening hip prosthesis, and subsequently to plan and guide a minimally invasive cement injection procedure to stabilize the prosthesis. We addressed the detection and measurement of periprosthetic bone lesions from CT image volumes. Post-operative CTs of patients treated at our institution were analysed. We developed tissue classification algorithms that automatically label periprosthetic bone, cement and fibrous interface tissue. An existing particle-based multi-material meshing algorithm was adapted for improved Finite Element model creation. We then presented HipRFX, a proof-of-concept software tool for planning and guidance during percutaneous cement refixation procedures.Advanced School for Computing and Imaging (ASCI), Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Stichting Anna Fonds, Technologiestichting STWUBL - phd migration 201

Reconstruction 3D personnalisée de la colonne vertébrale à partir d'images radiographiques non-calibrées

Les systèmes de reconstruction stéréo-radiographique 3D -- La colonne vertébrale -- La scoliose idiopathique adolescente -- Évolution des systèmes de reconstruction 3D -- Filtres de rehaussement d'images -- Techniques de segmentation -- Les méthodes de calibrage -- Les méthodes de reconstruction 3D -- Problématique, hypothèses, objectifs et méthode générale -- Three-dimensional reconstruction of the scoliotic spine and pelvis from uncalibrated biplanar X-ray images -- A versatile 3D reconstruction system of the spine and pelvis for clinical assessment of spinal deformities -- Simulation experiments -- Clinical validation -- A three-dimensional retrospective analysis of the evolution of spinal instrumentation for the correction of adolescent idiopathic scoliosis -- Auto-calibrage d'un système à rayons-X à partir de primitives de haut niveau -- Segmentation de la colonne vertébrale -- Approche hiérarchique d'auto-calibrage d'un système d'acquisition à rayons-X -- Personalized 3D reconstruction of the scoliotic spine from hybrid statistical and X-ray image-based models -- Validation protocol

Segmentation de l'articulation de la hanche à partir de radiographies biplanes en utilisant une approche multi-structures

En produisant une paire de radiographies orthogonales en position debout, le système EOS, beaucoup moins irradiant que le CT scan, offre la possibilité de reconstruire en 3D des structures osseuses. Pour reconstruire une structure osseuse à partir de radiographies biplanes, les contours extraits dans les images sont associés à des informations a priori 3D. Ce mémoire porte sur l’extraction simultanée de contours des deux structures adjacentes de l’articulation de la hanche : la tête fémorale et le cotyle. Cette tâche est ardue, notamment à cause du bruit élevé, du faible contraste et de la superposition de structures. Nous avons adopté une approche multi-structures permettant de segmenter simultanément deux contours correspondant chacun à une structure. La méthode proposée requiert une initialisation manuelle au niveau de la tête fémorale par le tracé d’un cercle pour extraire et localiser la région de l’articulation. Le processus de segmentation s’applique sur cette région qui est transformée dans un espace redressé, où les deux contours recherchés correspondent à deux chemins alignés. Les arêtes verticales sont détectées dans l’image redressée par un opérateur du gradient horizontal. Deux images de gradient de signe opposé sont générées, dans lesquelles la frontière de chaque structure est représentée par un chemin. Un volume redressé est construit en combinant ces deux images, permettant d’unir les deux chemins en un seul. Pour cela, un algorithme de recherche d’un chemin minimal 3D dans un volume a été développé. Les contraintes inter-structures sont imposées durant la recherche. La projection du chemin obtenu donne deux chemins distincts et labellisés qui sont transformés dans l’espace de l'image originale pour récupérer ainsi le contour de chaque structure. Nous avons appliqué cette méthode sur 100 images radiographiques du membre inférieur, contenant chacune deux articulations de hanche, acquises dans les directions frontale, oblique et latérale. L’évaluation de la précision a donné une erreur globale point-contour RMS±ÉT de 1,27±0.79 mm pour la tête fémorale et 1.26±0.74 mm pour le cotyle. Pour la répétabilité, nous avons obtenu en moyenne 80% de différences locales au-dessous de 1 mm. Les résultats révèlent que la méthode est précise, mais elle dépend aussi de la complexité de l'image segmentée et de la présence ou non d’une pathologie, notamment la coxarthrose. Ce travail servira certainement à améliorer le processus de la reconstruction en termes de précision

Quantification of knee extensor muscle forces: a multimodality approach

Given the growing interest of using musculoskeletal (MSK) models in a large number of clinical applications for quantifying the internal loading of the human MSK system, verification and validation of the model’s predictions, especially at the knee joint, have remained as one of the biggest challenges in the use of the models as clinical tools. This thesis proposes a methodology for more accurate quantification of knee extensor forces by exploring different experimental and modelling techniques that can be used to enhance the process of verification and validation of the knee joint model within the MSK models for transforming the models to a viable clinical tool. In this methodology, an experimental protocol was developed for simultaneous measurement of the knee joint motion, torques, external forces and muscular activation during an isolated knee extension exercise. This experimental protocol was tested on a cohort of 11 male subjects and the measurements were used to quantify knee extensor forces using two different MSK models representing a simplified model of the knee extensor mechanism and a previously-developed three-dimensional MSK model of the lower limb. The quantified knee extensor forces from the MSK models were then compared to evaluate the performance of the models for quantifying knee extensor forces. The MSK models were also used to investigate the sensitivity of the calculated knee extensor forces to key modelling parameters of the knee including the method of quantifying the knee centre of rotation and the effect of joint translation during motion. In addition, the feasibility of an emerging ultrasound-based imaging technique (shear wave elastography) for direct quantification of the physiologically-relevant musculotendon forces was investigated. The results in this thesis showed that a simplified model of the knee can be reliably used during a controlled planar activity as a computationally-fast and effective tool for hierarchical verification of the knee joint model in optimisation-based large-scale MSK models to provide more confidence in the outputs of the models. Furthermore, the calculation of knee extensor muscle forces has been found to be sensitive to knee joint translation (moving centre of rotation of the knee), highlighting the importance of this modelling parameter for quantifying physiologically-realistic knee muscle forces in the MSK models. It was also demonstrated how the movement of the knee axis of rotation during motion can be used as an intuitive tool for understanding the functional anatomy of the knee joint. Moreover, the findings in this thesis indicated that the shear wave elastography technique can be potentially used as a novel method for direct quantification of the physiologically-relevant musculotendon forces for independent validation of the predictions of musculotendon forces from the MSK models.Open Acces

High-Resolution Quantitative Cone-Beam Computed Tomography: Systems, Modeling, and Analysis for Improved Musculoskeletal Imaging

This dissertation applies accurate models of imaging physics, new high-resolution imaging hardware, and novel image analysis techniques to benefit quantitative applications of x-ray CT in in vivo assessment of bone health. We pursue three Aims: 1. Characterization of macroscopic joint space morphology, 2. Estimation of bone mineral density (BMD), and 3. Visualization of bone microstructure. This work contributes to the development of extremity cone-beam CT (CBCT), a compact system for musculoskeletal (MSK) imaging. Joint space morphology is characterized by a model which draws an analogy between the bones of a joint and the plates of a capacitor. Virtual electric field lines connecting the two surfaces of the joint are computed as a surrogate measure of joint space width, creating a rich, non-degenerate, adaptive map of the joint space. We showed that by using such maps, a classifier can outperform radiologist measurements at identifying osteoarthritic patients in a set of CBCT scans. Quantitative BMD accuracy is achieved by combining a polyenergetic model-based iterative reconstruction (MBIR) method with fast Monte Carlo (MC) scatter estimation. On a benchtop system emulating extremity CBCT, we validated BMD accuracy and reproducibility via a series of phantom studies involving inserts of known mineral concentrations and a cadaver specimen. High-resolution imaging is achieved using a complementary metal-oxide semiconductor (CMOS)-based x-ray detector featuring small pixel size and low readout noise. A cascaded systems model was used to performed task-based optimization to determine optimal detector scintillator thickness in nominal extremity CBCT imaging conditions. We validated the performance of a prototype scanner incorporating our optimization result. Strong correlation was found between bone microstructure metrics obtained from the prototype scanner and µCT gold standard for trabecular bone samples from a cadaver ulna. Additionally, we devised a multiresolution reconstruction scheme allowing fast MBIR to be applied to large, high-resolution projection data. To model the full scanned volume in the reconstruction forward model, regions outside a finely sampled region-of-interest (ROI) are downsampled, reducing runtime and cutting memory requirements while maintaining image quality in the ROI