Biomechanical validation of computer assisted planning of periacetabular osteotomy: A preliminary study based on finite element analysis

Periacetabular Osteotomy (PAO) is a joint preserving surgical intervention intended to increase femoral head coverage and thereby to improve stability in young patients with hip dysplasia. Previously, we developed a CT-based, computer-assisted program for PAO diagnosis and planning, which allows for quantifying the 3D acetabular morphology with parameters such as acetabular version, inclination, lateral center edge (LCE) angle and femoral head coverage ratio (CO). In order to verify the hypothesis that our morphology-based planning strategy can improve biomechanical characteristics of dysplastic hips, we developed a 3D finite element model based on patient-specific geometry to predict cartilage contact stress change before and after morphology-based planning. Our experimental results demonstrated that the morphology-based planning strategy could reduce cartilage contact pressures and at the same time increase contact areas. In conclusion, our computer-assisted system is an efficient tool for PAO planning.

Computer Assisted Diagnosis and Treatment Planning of Femoroacetabular Impingement (FAI)

Femoroacetabular impingement (FAI) is a dynamic conflict of the hip defined by a pathological, early abutment of the proximal femur onto the acetabulum or pelvis. In the past two decades, FAI has received increasing focus in both research and clinical practice as a cause of hip pain and prearthrotic deformity. Anatomical abnormalities such as an aspherical femoral head (cam-type FAI), a focal or general overgrowth of the acetabulum (pincer-type FAI), a high riding greater or lesser trochanter (extra-articular FAI), or abnormal torsion of the femur have been identified as underlying pathomorphologies. Open and arthroscopic treatment options are available to correct the deformity and to allow impingement-free range of motion. In routine practice, diagnosis and treatment planning of FAI is based on clinical examination and conventional imaging modalities such as standard radiography, magnetic resonance arthrography (MRA), and computed tomography (CT). Modern software tools allow three-dimensional analysis of the hip joint by extracting pelvic landmarks from two-dimensional antero-posterior pelvic radiographs. An object-oriented cross-platform program (Hip2Norm) has been developed and validated to standardize pelvic rotation and tilt on conventional AP pelvis radiographs. It has been shown that Hip2Norm is an accurate, consistent, reliable and reproducible tool for the correction of selected hip parameters on conventional radiographs. In contrast to conventional imaging modalities, which provide only static visualization, novel computer assisted tools have been developed to allow the dynamic analysis of FAI pathomechanics. In this context, a validated, CT-based software package (HipMotion) has been introduced. HipMotion is based on polygonal three-dimensional models of the patient’s pelvis and femur. The software includes simulation methods for range of motion, collision detection and accurate mapping of impingement areas. A preoperative treatment plan can be created by performing a virtual resection of any mapped impingement zones both on the femoral head-neck junction, as well as the acetabular rim using the same three-dimensional models. The following book chapter provides a summarized description of current computer-assisted tools for the diagnosis and treatment planning of FAI highlighting the possibility for both static and dynamic evaluation, reliability and reproducibility, and its applicability to routine clinical use.

Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering

Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.

Denoising Your Monte Carlo Renders: Recent Advances in Image Space-Adaptive Sampling and Reconstruction

With the ongoing shift in the computer graphics industry toward Monte Carlo rendering, there is a need for effective, practical noise-reduction techniques that are applicable to a wide range of rendering effects and easily integrated into existing production pipelines. This course surveys recent advances in image-space adaptive sampling and reconstruction algorithms for noise reduction, which have proven very effective at reducing the computational cost of Monte Carlo techniques in practice. These approaches leverage advanced image-filtering techniques with statistical methods for error estimation. They are attractive because they can be integrated easily into conventional Monte Carlo rendering frameworks, they are applicable to most rendering effects, and their computational overhead is modest.

Computer simulations of sample preconcentration in carrier-free systems and isoelectric focusing in microchannels using simple ampholytes.

In this work, electrophoretic preconcentration of protein and peptide samples in microchannels was studied theoretically using the 1D dynamic simulator GENTRANS, and experimentally combined with MS. In all configurations studied, the sample was uniformly distributed throughout the channel before power application, and driving electrodes were used as microchannel ends. In the first part, previously obtained experimental results from carrier-free systems are compared to simulation results, and the effects of atmospheric carbon dioxide and impurities in the sample solution are examined. Simulation provided insight into the dynamics of the transport of all components under the applied electric field and revealed the formation of a pure water zone in the channel center. In the second part, the use of an IEF procedure with simple well defined amphoteric carrier components, i.e. amino acids, for concentration and fractionation of peptides was investigated. By performing simulations a qualitative description of the analyte behavior in this system was obtained. Neurotensin and [Glu1]-Fibrinopeptide B were separated by IEF in microchannels featuring a liquid lid for simple sample handling and placement of the driving electrodes. Component distributions in the channel were detected using MALDI- and nano-ESI-MS and data were in agreement with those obtained by simulation. Dynamic simulations are demonstrated to represent an effective tool to investigate the electrophoretic behavior of all components in the microchannel.

Monte-Carlo simulation of Callisto's exosphere

We model Callisto's exosphere based on its ice as well as non-ice surface via the use of a Monte-Carlo exosphere model. For the ice component we implement two putative compositions that have been computed from two possible extreme formation scenarios of the satellite. One composition represents the oxidizing state and is based on the assumption that the building blocks of Callisto were formed in the protosolar nebula and the other represents the reducing state of the gas, based on the assumption that the satellite accreted from solids condensed in the jovian sub-nebula. For the non-ice component we implemented the compositions of typical CI as well as L type chondrites. Both chondrite types have been suggested to represent Callisto's non-ice composition best. As release processes we consider surface sublimation, ion sputtering and photon-stimulated desorption. Particles are followed on their individual trajectories until they either escape Callisto's gravitational attraction, return to the surface, are ionized, or are fragmented. Our density profiles show that whereas the sublimated species dominate close to the surface on the sun-lit side, their density profiles (with the exception of H and H-2) decrease much more rapidly than the sputtered particles. The Neutral gas and Ion Mass (NIM) spectrometer, which is part of the Particle Environment Package (PEP), will investigate Callisto's exosphere during the JUICE mission. Our simulations show that NIM will be able to detect sublimated and sputtered particles from both the ice and non-ice surface. NIM's measured chemical composition will allow us to distinguish between different formation scenarios. (C) 2015 Elsevier Inc. All rights reserved.