An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

Cost-effectivness in a DRG system for two-step exchange of infected total joint arthroplasty

The costs related to the treatment of infected total joint arthroplasties represent an ever groving burden to the society. Different patient-adapted therapeutic options like débridement and retention, 1- or 2-step exchange can be used. If a 2-step exchange is used we have to consider short (2-4 weeks) or long (>4-6 weeks) interval treatment. The Swiss DRG (Diagnose related Groups) determines the reimboursement the hopsital receives for the treatment of an infected total arthroplasty. The review assesses the cost-effectiveness of hospitalisation practices linked to surgical treatment in the two-stage exchange of a prosthetic-joint infection. The aim of this retrospectiv study is to compare the economical impact between a short (2 to 4 weeks) versus a long (6 weeks and above) interval during a two-satge procedure to determine the financial impact. Retrospectiv study of the patients with a two-stage procedure for a hip or knee prosthetic joint infection at CHUV hospital Lausanne (Switzerland) between 2012 and 2013. The review analyses the correlation between the interval length and the length of the hospital stay as well as with the costs and revenues per hospital stay. In average there is a loss of 40′000 Euro per hospitalisation for the treatment of prosthetic joint infection. Revenues never cover all the costs, even with a short interval procedure. This economical loss increases with the length of the hospital stay if a long-term intervall is choosen. The review explores potential for improvement in reimbourement practices and hospitalisation practices in the current Swiss healthcare setting. There should be alternative setups to decrease the burden of medical costs by a) increase the reimboursment for the treatment of infected total joints or by b) splitting the hospital stay with partners (rapid transfer after first operation from center hospital to level 2 hospital and retransfer for second operation to center) in order to increase revenues.