Estimating vadose zone hydraulic properties using ground penetrating radar: The impact of prior information

A number of geophysical methods, such as ground-penetrating radar (GPR), have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, the stochastic inversion of such data within a coupled geophysical-hydrological framework may allow for the effective estimation of vadose zone hydraulic parameters and their corresponding uncertainties. A critical issue in stochastic inversion is choosing prior parameter probability distributions from which potential model configurations are drawn and tested against observed data. A well chosen prior should reflect as honestly as possible the initial state of knowledge regarding the parameters and be neither overly specific nor too conservative. In a Bayesian context, combining the prior with available data yields a posterior state of knowledge about the parameters, which can then be used statistically for predictions and risk assessment. Here we investigate the influence of prior information regarding the van Genuchten-Mualem (VGM) parameters, which describe vadose zone hydraulic properties, on the stochastic inversion of crosshole GPR data collected under steady state, natural-loading conditions. We do this using a Bayesian Markov chain Monte Carlo (MCMC) inversion approach, considering first noninformative uniform prior distributions and then more informative priors derived from soil property databases. For the informative priors, we further explore the effect of including information regarding parameter correlation. Analysis of both synthetic and field data indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when we combine these data with a realistic, informative prior.

Which prior knowledge? Quantification of in vivo brain 13C MR spectra following 13C glucose infusion using AMARES.

The recent developments in high magnetic field 13C magnetic resonance spectroscopy with improved localization and shimming techniques have led to important gains in sensitivity and spectral resolution of 13C in vivo spectra in the rodent brain, enabling the separation of several 13C isotopomers of glutamate and glutamine. In this context, the assumptions used in spectral quantification might have a significant impact on the determination of the 13C concentrations and the related metabolic fluxes. In this study, the time domain spectral quantification algorithm AMARES (advanced method for accurate, robust and efficient spectral fitting) was applied to 13 C magnetic resonance spectroscopy spectra acquired in the rat brain at 9.4 T, following infusion of [1,6-(13)C2 ] glucose. Using both Monte Carlo simulations and in vivo data, the goal of this work was: (1) to validate the quantification of in vivo 13C isotopomers using AMARES; (2) to assess the impact of the prior knowledge on the quantification of in vivo 13C isotopomers using AMARES; (3) to compare AMARES and LCModel (linear combination of model spectra) for the quantification of in vivo 13C spectra. AMARES led to accurate and reliable 13C spectral quantification similar to those obtained using LCModel, when the frequency shifts, J-coupling constants and phase patterns of the different 13C isotopomers were included as prior knowledge in the analysis.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

Comparison of quantiferon-TB gold with tuberculin skin test for detecting latent tuberculosis infection prior to liver transplantation.

Screening for latent tuberculosis infection (LTBI) is recommended prior to organ transplantation. The Quantiferon-TB Gold assay (QFT-G) may be more accurate than the tuberculin skin test (TST) in the detection of LTBI. We prospectively compared the results of QFT-G to TST in patients with chronic liver disease awaiting transplantation. Patients were screened for LTBI with both the QFT-G test and a TST. Concordance between test results and predictors of a discordant result were determined. Of the 153 evaluable patients, 37 (24.2%) had a positive TST and 34 (22.2%) had a positive QFT-G. Overall agreement between tests was 85.1% (kappa= 0.60, p < 0.0001). Discordant test results were seen in 12 TST positive/QFT-G negative patients and in 9 TST negative/QFT-G positive patients. Prior BCG vaccination was not associated with discordant test results. Twelve patients (7.8%), all with a negative TST, had an indeterminate result of the QFT-G and this was more likely in patients with a low lymphocyte count (p = 0.01) and a high MELD score (p = 0.001). In patients awaiting liver transplantation, both the TST and QFT-G were comparable for the diagnosis of LTBI with reasonable concordance between tests. Indeterminate QFT-G result was more likely in those with more advanced liver disease.

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

Body fluid and tissue analysis using filter paper sampling support prior to LC-MS/MS: application to fatal overdose with colchicine

Because of the various matrices available for forensic investigations, the development of versatile analytical approaches allowing the simultaneous determination of drugs is challenging. The aim of this work was to assess a liquid chromatography-tandem mass spectrometry (LC-MS/MS) platform allowing the rapid quantification of colchicine in body fluids and tissues collected in the context of a fatal overdose. For this purpose, filter paper was used as a sampling support and was associated with an automated 96-well plate extraction performed by the LC autosampler itself. The developed method features a 7-min total run time including automated filter paper extraction (2 min) and chromatographic separation (5 min). The sample preparation was reduced to a minimum regardless of the matrix analyzed. This platform was fully validated for dried blood spots (DBS) in the toxic concentration range of colchicine. The DBS calibration curve was applied successfully to quantification in all other matrices (body fluids and tissues) except for bile, where an excessive matrix effect was found. The distribution of colchicine for a fatal overdose case was reported as follows: peripheral blood, 29 ng/ml; urine, 94 ng/ml; vitreous humour and cerebrospinal fluid, < 5 ng/ml; pericardial fluid, 14 ng/ml; brain, < 5 pg/mg; heart, 121 pg/mg; kidney, 245 pg/mg; and liver, 143 pg/mg. Although filter paper is usually employed for DBS, we report here the extension of this alternative sampling support to the analysis of other body fluids and tissues. The developed platform represents a rapid and versatile approach for drug determination in multiple forensic media.

Reply to Budowle, Ge, Chakraborty and Gill-King: use of prior odds for missing persons identifications

Prior probabilities represent a core element of the Bayesian probabilistic approach to relatedness testing. This letter opinions on the commentary 'Use of prior odds for missing persons identifications' by Budowle et al. (2011), published recently in this journal. Contrary to Budowle et al. (2011), we argue that the concept of prior probabilities (i) is not endowed with the notion of objectivity, (ii) is not a case for computation and (iii) does not require new guidelines edited by the forensic DNA community - as long as probability is properly considered as an expression of personal belief. Please see related article: http://www.investigativegenetics.com/content/3/1/3

Clinical predictors of prophylaxis use prior to the onset of acute venous thromboembolism in hospitalized patients SWIss Venous ThromboEmbolism Registry (SWIVTER).

BACKGROUND: We investigated clinical predictors of appropriate prophylaxis prior to the onset of venous thromboembolism (VTE). METHODS: In 14 Swiss hospitals, 567 consecutive patients (306 medical, 261 surgical) with acute VTE and hospitalization < 30 days prior to the VTE event were enrolled. RESULTS: Prophylaxis was used in 329 (58%) patients within 30 days prior to the VTE event. Among the medical patients, 146 (48%) received prophylaxis, and among the surgical patients, 183 (70%) received prophylaxis (P < 0.001). The indication for prophylaxis was present in 262 (86%) medical patients and in 217 (83%) surgical patients. Among the patients with an indication for prophylaxis, 135 (52%) of the medical patients and 165 (76%) of the surgical patients received prophylaxis (P < 0.001). Admission to the intensive care unit [odds ratio (OR) 3.28, 95% confidence interval (CI) 1.94-5.57], recent surgery (OR 2.28, 95% CI 1.51-3.44), bed rest > 3 days (OR 2.12, 95% CI 1.45-3.09), obesity (OR 2.01, 95% CI 1.03-3.90), prior deep vein thrombosis (OR 1.71, 95% CI 1.31-2.24) and prior pulmonary embolism (OR 1.54, 95% CI 1.05-2.26) were independent predictors of prophylaxis. In contrast, cancer (OR 1.06, 95% CI 0.89-1.25), age (OR 0.99, 95% CI 0.98-1.01), acute heart failure (OR 1.13, 95% CI 0.79-1.63) and acute respiratory failure (OR 1.19, 95% CI 0.89-1.59) were not predictive of prophylaxis. CONCLUSIONS: Although an indication for prophylaxis was present in most patients who suffered acute VTE, almost half did not receive any form of prophylaxis. Future efforts should focus on the improvement of prophylaxis for hospitalized patients, particularly in patients with cancer, acute heart or respiratory failure, and in the elderly.