Automated correction of improperly rotated diffusion gradient orientations in diffusion weighted MRI

Ensuring one is using the correct gradient orientations in a diffusion MRI study can be a challenging task. As different scanners, file formats and processing tools use different coordinate frame conventions, in practice, users can end up with improperly oriented gradient orientations. Using such wrongly oriented gradient orientations for subsequent diffusion parameter estimation will invalidate all rotationally variant parameters and fiber tractography results. While large misalignments can be detected by visual inspection, small rotations of the gradient table (e.g. due to angulation of the acquisition plane), are much more difficult to detect. In this work, we propose an automated method to align the coordinate frame of the gradient orientations with that of the corresponding diffusion weighted images, using a metric based on whole brain fiber tractography. By transforming the gradient table and measuring the average fiber trajectory length, we search for the transformation that results in the best global ‘connectivity’. To ensure a fast calculation of the metric we included a range of algorithmic optimizations in our tractography routine. To make the optimization routine robust to spurious local maxima, we use a stochastic optimization routine that selects a random set of seed points on each evaluation. Using simulations, we show that our method can recover the correct gradient orientations with high accuracy and precision. In addition, we demonstrate that our technique can successfully recover rotated gradient tables on a wide range of clinically realistic data sets. As such, our method provides a practical and robust solution to an often overlooked pitfall in the processing of diffusion MRI.     

Alcohol consumption and mortality: a dose-response analysis in terms of time

PurposeLow-to-moderate alcohol consumption is associated with decreased mortality. However, many aspects of this association are still debated. Our aim was to complement available information by conducting a dose-response analysis of the association between alcohol consumption and survival time.MethodsIn a Swedish population-based cohort of 67,706 middle-aged and elderly men and women, frequency and amount of drinking were assessed through a self-administrated questionnaire. During 15 years of follow-up, 13,323 participants died. Differences in survival (10th percentile differences, PDs) according to levels of alcohol consumption were estimated using Laplace regression.ResultsWe found evidence of nonlinearity between alcohol consumption and survival. Among women, we observed a rapid increase in survival up to 6 g/d of alcohol consumption (0.5 drinks/d) where survival was 17 months longer (PD = 17 months, 95% confidence interval, 10 to 24). After this peak, higher alcohol consumption was progressively associated with shorter survival. Among men, survival improved up to 15 g/d (1.5 drinks/d) where we observed a PD of 15 months (95% confidence interval, 8 to 22).ConclusionsLow alcohol consumption was associated with improved survival up to 1.5 years for women with an average consumption of 0.5 drinks per day and to 1.3 years for men with an average consumption of 1.5 drinks per day.     

Accurate confidence limits for stratified clinical trials

For stratified 2 × 2 tables, standard approximate confidence limits can perform poorly from a strict frequentist perspective, even for moderate‐sized samples, yet they are routinely used. In this paper, I show how to use importance sampling to compute highly accurate limits in reasonable time. The methodology is very general and simple to implement, and orders of magnitude are faster than existing alternatives. Copyright © 2013 John Wiley & Sons, Ltd.     

Effect of Refractive Index of Substrate on Fabrication and Optical Properties of Hybrid Au-Ag Triangular Nanoparticle Arrays

In this study, the nanosphere lithography (NSL) method was used to fabricate hybrid Au-Ag triangular periodic nanoparticle arrays. The Au-Ag triangular periodic arrays were grown on different substrates, and the effect of the refractive index of substrates on fabrication and optical properties was systematically investigated. At first, the optical spectrum was simulated by the discrete dipole approximation (DDA) numerical method as a function of refractive indexes of substrates and mediums. Simulation results showed that as the substrates had the refractive indexes of 1.43 (quartz) and 1.68 (SF5 glass), the nanoparticle arrays would have better refractive index sensitivity (RIS) and figure of merit (FOM). Simulation results also showed that the peak wavelength of the extinction spectra had a red shift when the medium’s refractive index n increased. The experimental results also demonstrated that when refractive indexes of substrates were 1.43 and 1.68, the nanoparticle arrays and substrate had better adhesive ability. Meanwhile, we found the nanoparticles formed a large-scale monolayer array with the hexagonally close-packed structure. Finally, the hybrid Au-Ag triangular nanoparticle arrays were fabricated on quartz and SF5 glass substrates and their experiment extinction spectra were compared with the simulated results.     

Principles of Physics in Surgery: The Laws of Mechanics and Vectors Physics for Surgeons—Part 2

In this sequel, to an earlier article, we discuss the laws of Mechanics, Thermodynamics and Vectors as they apply to soft and bony tissues. These include the Laplace’s Law as applied to colonic perforation, compression therapy, parturition, variceal rupture, disc herniations etc. The Pascal’s Law finds use in hernia repair and the Heimlich maneuver. Trigonometrically derived components of forces, acting after suturing, show ways to reduce cut-through; the thickness and the bite of suture determines the extent of tissue reaction. The heating effect of current explains the optimum gap between the prongs of a bipolar cautery and the use of law of transfer of heat in determining relation between healthy wound healing and ambient temperature.     

Estimation of Population Pharmacokinetic Parameters of Saquinavir in HIV Patients with the MONOLIX Software

In nonlinear mixed-effects models, estimation methods based on a linearization of the likelihood are widely used although they have several methodological drawbacks. Kuhn and Lavielle (Comput. Statist. Data Anal. 49:1020–1038 (2005)) developed an estimation method which combines the SAEM (Stochastic Approximation EM) algorithm, with a MCMC (Markov Chain Monte Carlo) procedure for maximum likelihood estimation in nonlinear mixed-effects models without linearization. This method is implemented in the Matlab software MONOLIX which is available at http://www.math.u-psud.fr/~lavielle/monolix/logiciels. In this paper we apply MONOLIX to the analysis of the pharmacokinetics of saquinavir, a protease inhibitor, from concentrations measured after single dose administration in 100 HIV patients, some with advance disease. We also illustrate how to use MONOLIX to build the covariate model using the Bayesian Information Criterion. Saquinavir oral clearance (CL/F) was estimated to be 1.26 L/h and to increase with body mass index, the inter-patient variability for CL/F being 120%. Several methodological developments are ongoing to extend SAEM which is a very promising estimation method for population pharmacockinetic/pharmacodynamic analyses.     

Relationship of quantitative structure and pharmacokinetics in fluoroquinolone antibacterials

AIM: To study the relationship between quantitative structure and pharmacokinetics (QSPkR) of fluoroquinolone antibacterials. METHODS: The pharmacokinetic (PK) parameters of oral fluoroquinolones were collected from the litera- ture. These pharmacokinetic data were averaged, 19 compounds were used as the training set, and 3 served as the test set. Genetic function approximation (GFA) module of Cerius2 software was used in QSPkR analysis. RESULTS: A small volume and large polarizability and surface area of substituents at C-7 contribute to a large area under the curve (AUC) for fluoroquinolones. Large polarizability and small volume of substituents at N-1 contribute to a long half life elimination. CONCLUSION: QSPkR models can contribute to some fluoroquinolones antibacterials with excellent pharmacokinetic properties.     

Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures

Hierarchical learning models are ubiquitously employed in information science and data engineering. The structure makes the posterior distribution complicated in the Bayes method. Then, the prediction including construction of the posterior is not tractable though advantages of the method are empirically well known. The variational Bayes method is widely used as an approximation method for application; it has the tractable posterior on the basis of the variational free energy function. The asymptotic behavior has been studied in many hierarchical models and a phase transition is observed. The exact form of the asymptotic variational Bayes energy is derived in Bernoulli mixture models and the phase diagram shows that there are three types of parameter learning. However, the approximation accuracy or interpretation of the transition point has not been clarified yet. The present paper precisely analyzes the Bayes free energy function of the Bernoulli mixtures. Comparing free energy functions in these two Bayes methods, we can determine the approximation accuracy and elucidate behavior of the parameter learning. Our results claim that the Bayes free energy has the same learning types while the transition points are different.     

A Highly Scalable Boundary Integral Equation and Walk-on-Spheres (BIE-WOS) Method for the Laplace Equation with Dirichlet Data

In this paper, we study a highly scalable communication-free parallel domain boundary decomposition algorithm for the Laplace equation based on a hybrid method combining boundary integral equations and walk-on-spheres (BIE-WOS)method, which provides a numerical approximation of the Dirichlet-to-Neumann(DtN) mapping for the Laplace equation. The BIE-WOS is a local method on theboundary of the domain and does not require a structured mesh, and only needs acovering of the domain boundary by patches and a local mesh for each patch for a local BIE. A new version of the BIE-WOS method with second kind integral equations isintroduced for better error controls. The effect of errors from the Feynman-Kac formulabased path integral WOS method on the overall accuracy of the BIE-WOS method isanalyzed for the BIEs, especially in the calculation of the right hand sides of the BIEs.For the special case of flat patches, it is shown that the second kind integral equationof BIE-WOS method can be simplified where the local BIE solutions can be given inclosed forms. A key advantage of the parallel BIE-WOS method is the absence of communications during the computation of the DtN mapping on individual patches ofthe boundary, resulting in a complete independent computation using a large numberof cluster nodes. In addition, the BIE-WOS has an intrinsic capability of fault tolerance for exascale computations. The nearly linear scalability of the parallel BIE-WOSmethod on a large-scale cluster with 6400 CPU cores is verified for computing the DtNmapping of exterior Laplace problems with Dirichlet data for several domains.