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PubMed1995

A robust single-shot partial sampling scheme.

A method of reducing the amount of data required to reconstruct an image is described. In this scheme, fully sampled low spatial frequency data are acquired up to a given cutoff frequency and above this point, only alternate lines are sampled. Two images are produced, one of low definition and one of high definition but aliased. The proposed algorithm unwraps the aliased data, which are then used to enhance the low pass image, yielding a best estimate of the true image. The reduced sampling technique is shown to afford biological images that are almost indistinguishable from those obtained from a complete data set.

Algorithms↗
PubMed2004

Point spread function mapping with parallel imaging techniques and high acceleration factors: fast, robust, and flexible method for echo-planar imaging distortion correction.

Echo-planar imaging (EPI) is an ultrafast magnetic resonance (MR) imaging technique prone to geometric distortions. Various correction techniques have been developed to remedy these distortions. Here improvements of the point spread function (PSF) mapping approach are presented, which enable reliable and fully automated distortion correction of echo-planar images at high field strengths. The novel method is fully compatible with EPI acquisitions using parallel imaging. The applicability of parallel imaging to further accelerate PSF acquisition is shown. The possibility of collecting PSF data sets with total acceleration factors higher than the number of coil elements is demonstrated. Additionally, a new approach to visualize and interpret distortions in the context of various imaging and reconstruction methods based on the PSF is proposed. The reliable performance of the PSF mapping technique is demonstrated on phantom and volunteer scans at field strengths of up to 4 T.

Artifacts↗
PubMed2005

Pulsed star labeling of arterial regions (PULSAR): a robust regional perfusion technique for high field imaging.

Regional perfusion imaging (RPI) has recently been introduced as a potentially powerful technique to map the perfusion territories of patients with vascular diseases in a fully noninvasive manner. However, this technique suffers from the problems of the transfer insensitive labeling technique upon which it is based. In particular, RPI is very sensitive to magnetic field inhomogeneities, and therefore the definition of the labeled bolus can deteriorate at field strength higher than 1.5 T. Furthermore, the slab-selective triple-pulse postsaturation sequence used originally will also be impaired due to the same problem, rendering RPI unusable at higher field. In this work, an adiabatic-based signal targeting with alternating radiofrequency pulses sequence is proposed as a labeling scheme to solve the problems related to variations in local magnetic field, together with an improved four-pulse water suppression enhanced through T(1) effects technique as a presaturation scheme.

Algorithms↗
PubMed2006

Robust analysis of short echo time (1)H MRSI of human brain.

Short echo time proton MR Spectroscopic Imaging (MRSI) suffers from low signal-to-noise ratio (SNR), limiting accuracy to estimate metabolite intensities. A method to coherently sum spectra in a region of interest of the human brain by appropriate peak alignment was developed to yield a mean spectrum with increased SNR. Furthermore, principal component (PC) spectra were calculated to estimate the variance of the mean spectrum. The mean or alternatively the first PC (PC(1)) spectrum from the same region can be used for quantitation of peak areas of metabolites in the human brain at increased SNR. Monte Carlo simulations showed that both mean and PC(1) spectra were more accurate in estimating regional metabolite concentrations than solutions that regress individual spectra against the tissue compositions of MRSI voxels. Back-to-back MRSI studies on 10 healthy volunteers showed that mean spectra markedly improved reliability of brain metabolite measurements, most notably for myo-inositol, as compared to regression methods.

Adult↗
PubMed2006

Robust quantification of short echo time 1H magnetic resonance spectra using the Padé approximant.

Accurate quantification of in vivo short echo time spectra is hampered by the presence of overlapping peaks and a significant baseline. In this work the Padé approximant in conjunction with Monte Carlo simulation is used to extract peak areas from short echo time 1H spectra. We exploit the fact that the Padé approximant is known to model broad non-Lorentzian signals as arbitrary sums of Lorentzian components to separate baseline components from sharper metabolite signals by combining the Padé approximant with Monte Carlo simulation. The simulation results demonstrate that the Padé approximant-Monte Carlo hybrid analysis is able to separate the metabolite signals from the baseline, while a least squares fitting of a time domain model may result in significant bias of the peak area estimations. For the in vivo data the estimates of the peak areas using the Padé approximant and AMARES compare well, with the exception of the NAA peak at 2.02 ppm. We suggest that the discrepancy may be due to the baseline contamination as supported by the simulation results; however, without an in vivo gold standard this remains difficult to demonstrate.

Adult↗
PubMed2006

Robust fully automated shimming of the human brain for high-field 1H spectroscopic imaging.

Although a variety of methods have been proposed to provide automated adjustment of shim homogeneity, these methods typically fail or require large numbers of iterations in vivo when applied to regions with poor homogeneity, such as the temporal lobe. These limitations are largely due to 1) the limited accuracy of single evolution time measurements when full B0 mapping studies are used, and 2) inaccuracies arising from projection-based methods when the projections pass through regions where the inhomogeneity exceeds the order of the fitted parameters. To overcome these limitations we developed a novel B0 mapping method using multiple evolution times with a novel unwrapping scheme in combination with a user-defined ROI selection tool. We used these methods at 4T on 10 control subjects to obtain high-resolution spectroscopic images of glutamate from the bilateral hippocampi.

Automation↗
PubMed2004

A simple topological representation of protein structure: implications for new, fast, and robust structural classification.

A topological representation of proteins is developed that makes use of two metrics: the Euclidean metric for identifying natural nearest neighboring residues via the Delaunay tessellation in Cartesian space and the distance between residues in sequence space. Using this representation, we introduce a quantitative and computationally inexpensive method for the comparison of protein structural topology. The method ultimately results in a numerical score quantifying the distance between proteins in a heuristically defined topological space. The properties of this scoring scheme are investigated and correlated with the standard Calpha distance root-mean-square deviation measure of protein similarity calculated by rigid body structural alignment. The topological comparison method is shown to have a characteristic dependence on protein conformational differences and secondary structure. This distinctive behavior is also observed in the comparison of proteins within families of structural relatives. The ability of the comparison method to successfully classify proteins into classes, superfamilies, folds, and families that are consistent with standard classification methods, both automated and human-driven, is demonstrated. Furthermore, it is shown that the scoring method allows for a fine-grained classification on the family, protein, and species level that agrees very well with currently established phylogenetic hierarchies. This fine classification is achieved without requiring visual inspection of proteins, sequence analysis, or the use of structural superimposition methods. Implications of the method for a fast, automated, topological hierarchical classification of proteins are discussed.

Amino Acid Sequence↗
PubMed2004

A robust method to detect structural and functional remote homologues.

With currently available sequence data, it is feasible to conduct extensive comparisons among large sets of protein sequences. It is still a much more challenging task to partition the protein space into structurally and functionally related families solely based on sequence comparisons. The ProtoNet system automatically generates a treelike classification of the whole protein space. It stands to reason that this classification reflects evolutionary relationships, both close and remote. In this article, we examine this hypothesis. We present a semiautomatic procedure that singles out certain inner nodes in the ProtoNet tree that should ideally correspond to structurally and functionally defined protein families. We compare the performance of this method against several expert systems. Some of the competing methods incorporate additional extraneous information on protein structure or on enzymatic activities. The ProtoNet-based method performs at least as well as any of the methods with which it was compared. This article illustrates the ProtoNet-based method on several evolutionarily diverse families. Using this new method, an evolutionary divergence scheme can be proposed for a large number of structural and functional related superfamilies.

Computational Biology↗
PubMed2006

Ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry for robust, high-throughput quantitative analysis of an automated metabolic stability assay, with simultaneous determination of metabolic data.

The application of ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC/TOFMS) for high-throughput analysis of a 96-well plate based metabolic stability assay has been investigated. Full-scan data were acquired, with run times of 2.5-3.5 min, from which narrow window extracted ion chromatograms were generated, producing quantitative data for the test compound equivalent to that obtained by high-performance liquid chromatography with tandem mass spectrometric detection on a triple quadrupole instrument (HPLC/MS/MS). Sensitivity and mass accuracy were maintained over the analysis of >300 samples. Additionally, the UPLC/TOFMS datasets obtained gave access to metabolic route information, at no cost in terms of sensitivity for the test compound.

Animals↗
PubMed2001

A simple and robust conductive graphite coating for sheathless electrospray emitters used in capillary electrophoresis/mass spectrometry.

A graphite-polyimide mixture was used as a conductive coating for sheathless electrospray emitters. The coating procedure described is simple and inexpensive compared to previously described methods. An investigation of the stability of the conductive coating carried out by electrochemical methods revealed good performances during oxidative stress. In addition, no decrease in emitter performance was seen during continuous electrospray in the positive electrospray mode for two weeks. Fast capillary electrophoresis with attomole sensitivity demonstrated the excellent performance of the described sheathless interface when used in conjunction with an orthogonal time-of-flight mass spectrometer. The overall simplicity, stability and low cost of this type of sheathless emitter make the described approach highly suitable for any on-column coupling of low flow rate separation techniques to a mass spectrometer.

Journal Article↗
PubMed2002

Highly robust stainless steel tips as microelectrospray emitters.

Tapered stainless steel spray tips for sheathless microelectrospray ionization (microESI) have been developed. The fabrication procedure for the tapered stainless steel tips was optimized using an electropolishing technique followed by removal of the burr. Using the tip as the microESI emitter, a stable ESI spray was obtained at a flow rate of 20 nL/min. The sensitivity of the microESI system was almost two orders greater than that of the conventional ion spray system. The tip was highly stable, and was successfully used for over 1000 h. Moreover, these stainless steel tips were suitable for use with sheathless capillary electrophoresis/mass spectrometry (CE/MS) and capillary liquid chromatography/mass spectrometry (LC/MS) for routine analysis in proteomic and pharmaceutical applications.

Chromatography, Liquid↗
PubMed2003

Robustness of sample size re-estimation procedure in clinical trials (arbitrary populations).

In clinical trials, one of the main questions that is being asked is how many additional observations, if any, are needed beyond those originally planned. In a two-treatment double-blind clinical experiment, one is interested in testing the null hypothesis of equality of the means against one-sided alternative when the common variance sigma2 is unknown. We wish to determine the required total sample size when the error probabilities alpha and beta are specified at a predetermined alternative. Shih provided a two-stage procedure which is an extension of Stein's one-sample procedure, assuming normal response. He estimates sigma2 by the method of maximum likelihood via the EM algorithm and carries out a simulation study in order to evaluate the effective level of significance and the power. The author proposed a closed-form estimator for sigma2 and showed analytically that the difference between the effective and nominal levels of significance is negligible and that the power exceeds 1-beta when the initial sample size is large. Here we consider responses from arbitrary distributions in which the mean and the variance are not functionally related and show that when the initial sample size is large, the conclusions drawn previously by the author still hold. The effective coverage probability of a fixed-width interval is also evaluated. Proofs of certain assertions are deferred to the Appendix.

Clinical Trials as Topic↗
PubMed2004

Estimating treatment effect in the presence of non-compliance measured with error: precision and robustness of data analysis methods.

Non-compliance with the nominal prescribed dosage causes unintended variability in actual drug exposure during clinical trials. In the ideal case that compliance is not a confounder, and it is known--hence actual dosage is known--true dose-response can be validly estimated. Measuring compliance presents a challenge, however. A simulation study of the case that dosage history questionnaires (C(Q)--usually over-optimistic estimates of actual compliance) are available in all subjects enrolled in a clinical trial, but accurate compliance measurements (C--e.g. from electronic medication event monitors), are only available in a (random) fraction of subjects is reported. It reveals that a 'Maximum Penalized Marginal Likelihood' (MPML) method which uses all compliance data, effectively calibrating C(Q) to C, is superior to other methods which use only one compliance measure, or both, or neither (neither = ITT, intention to treat, which assumes actual dosage equals nominal dosage), but do not calibrate. MPML yields the most precise estimates of dose-response over widely varying clinical trial designs, extremes in quality and quantity of compliance information, and a range of drug effect sizes. It is most beneficial when compliance data are sparse and maintains good performance even when its key assumptions are somewhat violated.

Algorithms↗
PubMed2007

Robustness of a multivariate normal approximation for imputation of incomplete binary data.

Multiple imputation has become easier to perform with the advent of several software packages that provide imputations under a multivariate normal model, but imputation of missing binary data remains an important practical problem. Here, we explore three alternative methods for converting a multivariate normal imputed value into a binary imputed value: (1) simple rounding of the imputed value to the nearer of 0 or 1, (2) a Bernoulli draw based on a 'coin flip' where an imputed value between 0 and 1 is treated as the probability of drawing a 1, and (3) an adaptive rounding scheme where the cut-off value for determining whether to round to 0 or 1 is based on a normal approximation to the binomial distribution, making use of the marginal proportions of 0's and 1's on the variable. We perform simulation studies on a data set of 206,802 respondents to the California Healthy Kids Survey, where the fully observed data on 198,262 individuals defines the population, from which we repeatedly draw samples with missing data, impute, calculate statistics and confidence intervals, and compare bias and coverage against the true values. Frequently, we found satisfactory bias and coverage properties, suggesting that approaches such as these that are based on statistical approximations are preferable in applied research to either avoiding settings where missing data occur or relying on complete-case analyses. Considering both the occurrence and extent of deficits in coverage, we found that adaptive rounding provided the best performance.

Adolescent↗
PubMed1993

Robust inference for multivariate survival data.

Multivariate survival data arise when an individual records multiple survival events or when individuals recording single survival events are grouped into clusters. In this paper we propose a new method for the analysis of multivariate survival data. The technique is a synthesis of the Poisson regression formulation for univariate censored survival analysis and the generalized estimating equation approach for obtaining valid variance estimates for generalized linear models in the presence of clustering. When the survival data are clustered, combining the methods provides not only valid estimates for the variances of regression parameters but also estimates of the dependence between survival times. The approach entails specifying parametric models for the marginal hazards and a dependence structure, but does not require specification of the joint multivariate survival distribution. Properties of the methodology are investigated by simulation and through an illustrative example.

Humans↗
PubMed1994

A robust goodness-of-fit test statistic with application to ordinal regression models.

We propose a goodness-of-fit test statistic for linear regression with heterogeneous variance, which is asymptotically chi-square if the given model is correct. The test statistic is computed as a quadratic form of observed minus predicted responses. We apply the method to a linear regression for an ordinal categorical response, the wheezing status of a child (no wheeze, wheeze with cold, wheeze apart from cold) as a function of maternal smoking and city of residence.

Child↗