Stephen W. Provencher

Bio: Stephen W. Provencher is an academic researcher from Max Planck Society. The author has contributed to research in topics: Light scattering & Dynamic light scattering. The author has an hindex of 13, co-authored 14 publications receiving 6219 citations.

Estimation of metabolite concentrations from localized in vivo proton NMR spectra

Abstract: The LCModel method analyzes an in vivo spectrum as a Linear Combination of Model spectra of metabolite solutions in vitro By using complete model spectra, rather than just individual resonances, maximum information and uniqueness are incorporated into the analysis A constrained regularization method accounts for differences in phase, baseline, and lineshapes between the in vitro and in vivo spectra, and estimates the metabolite concentrations and their uncertainties LCModel is fully automatic in that the only input is the time-domain in vivo data The lack of subjective interaction should help the exchange and comparison of results More than 3000 human brain STEAM spectra from patients and healthy volunteers have been analyzed with LCModel N-acetylaspartate, cholines, creatines, myo-inositol, and glutamate can be reliably determined, and abnormal levels of these or elevated levels of lactate, alanine, scyllo-inositol, glutamine, or glucose clearly indicate numerous pathologies A computer program will be available

Automatic quantitation of localized in vivo 1H spectra with LCModel

Abstract: The LCModel method analyzes an in vivo spectrum as a Linear Combination of Model in vitro spectra from individual metabolite solutions. Complete model spectra, rather than individual resonances, are used in order to incorporate maximum prior information into the analysis. A nearly model-free constrained regularization method automatically accounts for the baseline and lineshape in vivo without imposing a restrictive parameterized form on them. LCModel is automatic (non-interactive) with no subjective input. Approximately maximum-likelihood estimates of the metabolite concentrations and their uncertainties (Cramer-Rao lower bounds) are obtained. LCModel analyses of spectra from users with fields from 1.5 to 9.4 T and a wide range of sequences, particularly with short TE, are used here to illustrate the capabilities and limitations of LCModel and proton MRS.

Inverse problems in polymer characterization: Direct analysis of polydispersity with photon correlation spectroscopy

Abstract: A method is presented for inverting the Fredholm integral equations of the first kind that arise in many experimental determinations of molecular weight distributions of high polymers. The well known problems of instability and nonuniqueness are minimized by constraining the distribution to be the smoothest nonnegative one that is consistent with the data. Analyses of simulated photon correlation spectroscopy data show that good accuracy can be obtained for unimodal distributions and fair accuracy for certain bimodal ones, provided that systematic errors are kept below the random noise level. The method is completely automatic in that no initial estimate or prior information about the distribution is needed. However, if there happens to be a priori knowledge that the distribution is unimodal or that it is bimodal, constraining the distribution accordingly can further improve the stability and accuracy.

Water diffusion in rat brain in vivo as detected at very large b values is multicompartmental.

Abstract: The diffusion-weighted signal attenuation of water in rat brain was measured with pulsed-field gradient nuclear magnetic resonance methods in a single voxel under in vivo and global ischemic conditions. The diffusion-attenuated water signal was observed in vivo atb values of 300 ms/μm2 (strength of diffusion weighting) and diffusion times up to 400 ms. A series of constant diffusion time (CT) experiments with varied gradient directions and diffusion times revealed a multiexponential decay with apparent diffusion coefficients (ADC) covering two orders of magnitude from 1 to 0.01 μm2/ms. In a four-exponential fit, the observed changes during global ischemia could be fully explained by changes in the relative volume fractions only with unchanged ADCs. An anisotropy of the ADC, detected at smallb values, was not observed for the ADC at largeb values, but for the concomitant volume fractions. An inverse Laplace Transform of the CT curves, performed with CONTIN, resulted in continuously distributed diffusion coefficients, for which the term ‘diffusogram’ is proposed. This approach was more appropriate than a discrete exponential model with four to six components, being related to the morphology of brain tissue and its cell size distribution. On the basis of an analytical, quantitative model, it is suggested that the measured ADC at smallb values reflects mainly properties of the restricting boundaries, i.e. the relative volume fractions and the extracellular tortuosity, while the intrinsic intracellular diffusion constant and the exchange time are predicted to have minor influence.

The basis of anisotropic water diffusion in the nervous system – a technical review

Abstract: Anisotropic water diffusion in neural fibres such as nerve, white matter in spinal cord, or white matter in brain forms the basis for the utilization of diffusion tensor imaging (DTI) to track fibre pathways. The fact that water diffusion is sensitive to the underlying tissue microstructure provides a unique method of assessing the orientation and integrity of these neural fibres, which may be useful in assessing a number of neurological disorders. The purpose of this review is to characterize the relationship of nuclear magnetic resonance measurements of water diffusion and its anisotropy (i.e. directional dependence) with the underlying microstructure of neural fibres. The emphasis of the review will be on model neurological systems both in vitro and in vivo. A systematic discussion of the possible sources of anisotropy and their evaluation will be presented followed by an overview of various studies of restricted diffusion and compartmentation as they relate to anisotropy. Pertinent pathological models, developmental studies and theoretical analyses provide further insight into the basis of anisotropic diffusion and its potential utility in the nervous system.

Estimation of globular protein secondary structure from circular dichroism.

Abstract: A new method is developed in which a circular dichroism (CD) spectrum is analyzed directly as a linear combination of the CD spectra (from 190 to 240 nm) of 16 proteins whose secondary structures are known from X-ray crystallography. This avoids the dilemma encountered in previous methods of trying to define single reference CD spectra that were supposed to characterize such broad and variable classes as helix, beta sheet, beta turn, and "remainder". It also permits a more accurate and flexible analysis. The usual instability in using so many parameters is automatically controlled by a simple constrained statistical regularization procedure (similar to ridge regression). Sixteen tests were made by removing 1 spectrum at a time from the set of 16 and analyzing it in terms of the other 15. The product moment correlation coefficients between the computed fractions of helix, beta sheet, beta turn, and remainder and the fractions from the X-ray data were 0.96, 0.94, 0.31,, and 0.49, respectively. Thus, the helix and beta-sheet accuracy is very good. (The corresponding values calculated by a previous method with four reference spectra were 0.85, 0.25, --0.31, and 0.46.).