60 research outputs found

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

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    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 patientā€™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 ļ¬rst 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 ļ¬‚uoroscopic 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 ļ¬‚uoroscopic 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 workļ¬‚ow. This is the ļ¬rst time that a bone reconstruction method has been applied to the complex ankle joint and the ļ¬rst reconstruction method using CNN based segmentations as features. The reconstructed 3D-SSM of the uninjured ankle can be back-projected and visualized in a workļ¬‚ow-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 ļ¬bular 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 workļ¬‚ow proposed in this thesis establishes the ļ¬rst 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 identiļ¬ed 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

    Individualised Modelling for Preoperative Planning of Total Knee Replacement Surgery

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    Total knee replacement (TKR) surgery is routinely prescribed for patients with severe knee osteoarthritis to alleviate the pain and restore the kinematics. Although this procedure was proven to be successful in reducing the joint pain, the number of failures and the low patientsā€™ satisfaction suggest that while the number of reoperations is small, the surgery frequently fail to restore the function in full. The main cause are surgical techniques which inadequately address the problem of balancing the knee soft tissues. The preoperative planning technique allows to manufacture subject-specific cutting guides that improves the placement of the prosthesis, however the knee soft tissue is ignored. The objective of this dissertation was to create an optimized preplanning procedure to compute the soft tissue balance along with the placement of the prosthesis to ensure mechanical stability. The dissertation comprises the development of CT based static and quasi-static knee models able to estimate the postoperative length of the collateral lateral ligaments using a dataset of seven TKR patients; In addition, a subject-specific dynamic musculoskeletal model of the lower limb was created using in vivo knee contact forces to perform the same analysis during walking. The models were evaluated by their ability to predict the postoperative elongation using a threshold based on the 10 % of the preoperative length, through which the model detected whether an elongation was acceptable. The results showed that the subject-specific static model is the best solution to be included in the optimized, subject-specific, preoperative planning framework; full order musculoskeletal model allowed to estimate the postoperative length of the ligaments during walking, and at least in principle while performing any other activity. Unlike the current methodology used in clinic this optimized preoperative planning framework might help the surgeon to understand how the position of the TKR affects the knee soft tissue

    Book of Abstracts 15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and 3rd Conference on Imaging and Visualization

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    In this edition, the two events will run together as a single conference, highlighting the strong connection with the Taylor & Francis journals: Computer Methods in Biomechanics and Biomedical Engineering (John Middleton and Christopher Jacobs, Eds.) and Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization (JoĆ£oManuel R.S. Tavares, Ed.). The conference has become a major international meeting on computational biomechanics, imaging andvisualization. In this edition, the main program includes 212 presentations. In addition, sixteen renowned researchers will give plenary keynotes, addressing current challenges in computational biomechanics and biomedical imaging. In Lisbon, for the first time, a session dedicated to award the winner of the Best Paper in CMBBE Journal will take place. We believe that CMBBE2018 will have a strong impact on the development of computational biomechanics and biomedical imaging and visualization, identifying emerging areas of research and promoting the collaboration and networking between participants. This impact is evidenced through the well-known research groups, commercial companies and scientific organizations, who continue to support and sponsor the CMBBE meeting series. In fact, the conference is enriched with five workshops on specific scientific topics and commercial software.info:eu-repo/semantics/draf

    Patient-Specific Modeling Of Adult Acquired Flatfoot Deformity Before And After Surgery

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    The use of computational modeling is an increasingly commonplace technique for the investigation of biomechanics in intact and pathological musculoskeletal systems. Moreover, given the robust and repeatable nature of computer simulation and the prevalence of software techniques for accurate 3-D reconstructions of tissues, the predictive power of these models has increased dramatically. However, there are no patient-specific kinematic models whose function is dictated solely by physiologic soft-tissue constraints, articular shape and contact, and without idealized joint approximations. Moreover, very few models have attempted to predict surgical effects combined with postoperative validation of those predictions. Given this, it is not surprising that the area of foot/ankle modeling has been especially underserved. Thus, we chose to investigate the pre- and postoperative kinematics of Adult Acquired Flatfoot Deformity (AAFD) across a cohort of clinically diagnosed sufferers. AAFD was chosen as it is a chronic and degenerative disease wherein degradation of soft-tissue supporters of the medial arch eventually cause gross malalignment in the mid- and hindfoot, along with significant pain and dysfunction. Also, while planar radiographs are still used to diagnose and stage the disease, it is widely acknowledged that these 2-D measures fail to fully describe the 3-D nature of AAFD. Thus, a population of six patient-specific rigid-body computational models was developed using the commercially available software packages MimicsĀ® and SolidWorksĀ® in order to investigate foot function in patients with diagnosed Stage IIb AAFD. Each model was created from patient-specific sub-millimeter MRI scans, loaded with body weight, individualized muscle forces, and ligament forces, in single leg stance. The predicted model kinematics were validated pre- and postoperatively using clinically utilized radiographic angle distance measures as well as plantar force distributions. The models were then further exploited to predict additional biomechanical parameters such as articular contact force and soft-tissue strain, as well as the effect of hypothetical surgical interventions. Subsequently, kinematic simulations demonstrated that the models were able to accurately predict foot/ankle motion in agreement with their respective patients. Additionally, changes in joint contact force and ligament strain observed across surgical states further elucidate the complex biomechanical underpinnings of foot and ankle function

    Research and technology, 1992

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    Selected research and technology activities at Ames Research Center, including the Moffett Field site and the Dryden Flight Research Facility, are summarized. These activities exemplify the Center's varied and productive research efforts for 1992

    Infective/inflammatory disorders

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