New functional and biomechanical assessments for the improvement of the surgical navigation systems for joint replacement in the human lower limb

In case of severe osteoarthritis at the knee causing pain, deformity, and loss of stability and mobility, the clinicians consider that the substitution of these surfaces by means of joint prostheses. The objectives to be pursued by this surgery are: complete pain elimination, restoration of the normal physiological mobility and joint stability, correction of all deformities and, thus, of limping. The knee surgical navigation systems have bee developed in computer-aided surgery in order to improve the surgical final outcome in total knee arthroplasty. These systems provide the surgeon with quantitative and real-time information about each surgical action, like bone cut executions and prosthesis component alignment, by mean of tracking tools rigidly fixed onto the femur and the tibia. Nevertheless, there is still a margin of error due to the incorrect surgical procedures and to the still limited number of kinematic information provided by the current systems. Particularly, patello-femoral joint kinematics is not considered in knee surgical navigation. It is also unclear and, thus, a source of misunderstanding, what the most appropriate methodology is to study the patellar motion. In addition, also the knee ligamentous apparatus is superficially considered in navigated total knee arthroplasty, without taking into account how their physiological behavior is altered by this surgery. The aim of the present research work was to provide new functional and biomechanical assessments for the improvement of the surgical navigation systems for joint replacement in the human lower limb. This was mainly realized by means of the identification and development of new techniques that allow a thorough comprehension of the functioning of the knee joint, with particular attention to the patello-femoral joint and to the main knee soft tissues. A knee surgical navigation system with active markers was used in all research activities presented in this research work. Particularly, preliminary test were performed in order to assess the system accuracy and the robustness of a number of navigation procedures. Four studies were performed in-vivo on patients requiring total knee arthroplasty and randomly implanted by means of traditional and navigated procedures in order to check for the real efficacy of the latter with respect to the former. In order to cope with assessment of patello-femoral joint kinematics in the intact and replaced knees, twenty in-vitro tests were performed by using a prototypal tracking tool also for the patella. In addition to standard anatomical and articular recommendations, original proposals for defining the patellar anatomical-based reference frame and for studying the patello-femoral joint kinematics were reported and used in these tests. These definitions were applied to two further in-vitro tests in which, for the first time, also the implant of patellar component insert was fully navigated. In addition, an original technique to analyze the main knee soft tissues by means of anatomical-based fiber mappings was also reported and used in the same tests. The preliminary instrumental tests revealed a system accuracy within the millimeter and a good inter- and intra-observer repeatability in defining all anatomical reference frames. In in-vivo studies, the general alignments of femoral and tibial prosthesis components and of the lower limb mechanical axis, as measured on radiographs, was more satisfactory, i.e. within ±3°, in those patient in which total knee arthroplasty was performed by navigated procedures. As for in-vitro tests, consistent patello-femoral joint kinematic patterns were observed over specimens throughout the knee flexion arc. Generally, the physiological intact knee patellar motion was not restored after the implant. This restoration was successfully achieved in the two further tests where all component implants, included the patellar insert, were fully navigated, i.e. by means of intra-operative assessment of also patellar component positioning and general tibio-femoral and patello-femoral joint assessment. The tests for assessing the behavior of the main knee ligaments revealed the complexity of the latter and the different functional roles played by the several sub-bundles compounding each ligament. Also in this case, total knee arthroplasty altered the physiological behavior of these knee soft tissues. These results reveal in-vitro the relevance and the feasibility of the applications of new techniques for accurate knee soft tissues monitoring, patellar tracking assessment and navigated patellar resurfacing intra-operatively in the contest of the most modern operative techniques. This present research work gives a contribution to the much controversial knowledge on the normal and replaced of knee kinematics by testing the reported new methodologies. The consistence of these results provides fundamental information for the comprehension and improvements of knee orthopedic treatments. In the future, the reported new techniques can be safely applied in-vivo and also adopted in other joint replacements.

Heterogeneous multicore systems for signal processing

This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.

Parallel Architectures for Many-Core Systems-On-Chip in Deep Sub-Micron Technology

Despite the several issues faced in the past, the evolutionary trend of silicon has kept its constant pace. Today an ever increasing number of cores is integrated onto the same die. Unfortunately, the extraordinary performance achievable by the many-core paradigm is limited by several factors. Memory bandwidth limitation, combined with inefficient synchronization mechanisms, can severely overcome the potential computation capabilities. Moreover, the huge HW/SW design space requires accurate and flexible tools to perform architectural explorations and validation of design choices. In this thesis we focus on the aforementioned aspects: a flexible and accurate Virtual Platform has been developed, targeting a reference many-core architecture. Such tool has been used to perform architectural explorations, focusing on instruction caching architecture and hybrid HW/SW synchronization mechanism. Beside architectural implications, another issue of embedded systems is considered: energy efficiency. Near Threshold Computing is a key research area in the Ultra-Low-Power domain, as it promises a tenfold improvement in energy efficiency compared to super-threshold operation and it mitigates thermal bottlenecks. The physical implications of modern deep sub-micron technology are severely limiting performance and reliability of modern designs. Reliability becomes a major obstacle when operating in NTC, especially memory operation becomes unreliable and can compromise system correctness. In the present work a novel hybrid memory architecture is devised to overcome reliability issues and at the same time improve energy efficiency by means of aggressive voltage scaling when allowed by workload requirements. Variability is another great drawback of near-threshold operation. The greatly increased sensitivity to threshold voltage variations in today a major concern for electronic devices. We introduce a variation-tolerant extension of the baseline many-core architecture. By means of micro-architectural knobs and a lightweight runtime control unit, the baseline architecture becomes dynamically tolerant to variations.