Effects of carrier frequency mismatch on frequency-selective spectral editing.

OBJECTIVES: This study sought to investigate the effects of carrier frequency mismatch on spectral editing and its correction by frequency matching of basis functions. MATERIALS AND METHODS: Full density matrix computations and Monte-Carlo simulations based on magnetic resonance spectroscopy (MRS) data collected from five healthy volunteers at 7 T were used to analyze the effects of carrier frequency mismatch on spectral editing. Relative errors in metabolite quantification were calculated with and without frequency matching of basis functions. The algorithm for numerical computation of basis functions was also improved for higher computational efficiency. RESULTS: We found significant errors without frequency matching of basis functions when carrier frequency mismatch was generally considered negligible. By matching basis functions with the history of frequency deviation, the mean errors in glutamate, glutamine, γ-aminobutyric acid, and glutathione concentrations were reduced from 3.90%, 1.85%, 11.53%, and 3.43% to 0.18%, 0.34%, 0.40%, and 0.51%, respectively. CONCLUSION: Matching basis functions to frequency deviation history was necessary even when frequency deviations during frequency-selective spectral editing were fairly small. Basis set frequency matching significantly improved accuracy in the quantification of glutamate, glutamine, γ-aminobutyric acid, and glutathione concentrations.

Bayesian change-point modeling with segmented ARMA model.

Time series segmentation aims to identify segment boundary points in a time series, and to determine the dynamical properties corresponding to each segment. To segment time series data, this article presents a Bayesian change-point model in which the data within segments follows an autoregressive moving average (ARMA) model. A prior distribution is defined for the number of change-points, their positions, segment means and error terms. To quantify uncertainty about the location of change-points, the resulting posterior probability distributions are sampled using the Generalized Gibbs sampler Markov chain Monte Carlo technique. This methodology is illustrated by applying it to simulated data and to real data known as the well-log time series data. This well-log data records the measurements of nuclear magnetic response of underground rocks during the drilling of a well. Our approach has high sensitivity, and detects a larger number of change-points than have been identified by comparable methods in the existing literature.

Fitting interrelated datasets: metabolite diffusion and general lineshapes.

OBJECTIVE: Simultaneous modeling of true 2-D spectroscopy data, or more generally, interrelated spectral datasets has been described previously and is useful for quantitative magnetic resonance spectroscopy applications. In this study, a combined method of reference-lineshape enhanced model fitting and two-dimensional prior-knowledge fitting for the case of diffusion weighted MR spectroscopy is presented. MATERIALS AND METHODS: Time-dependent field distortions determined from a water reference are applied to the spectral bases used in linear-combination modeling of interrelated spectra. This was implemented together with a simultaneous spectral and diffusion model fitting in the previously described Fitting Tool for Arrays of Interrelated Datasets (FiTAID), where prior knowledge conditions and restraints can be enforced in two dimensions. RESULTS: The benefit in terms of increased accuracy and precision of parameters is illustrated with examples from Monte Carlo simulations, in vitro and in vivo human brain scans for one- and two-dimensional datasets from 2-D separation, inversion recovery and diffusion-weighted spectroscopy (DWS). For DWS, it was found that acquisitions could be substantially shortened. CONCLUSION: It is shown that inclusion of a measured lineshape into modeling of interrelated MR spectra is beneficial and can be combined also with simultaneous spectral and diffusion modeling.

Magnetic resonance-derived circumferential strain provides a superior and incremental assessment of improvement in contractile function in patients early after ST-segment elevation myocardial infarction.

BACKGROUND: We evaluate whether circumferential strain derived from grid-tagged CMR is a better method for assessing improvement in segmental contractile function after STEMI compared to late gadolinium enhancement (LGE). METHODS: STEMI patients post primary PCI underwent baseline CMR (day 3) and follow-up (day 90). Cine, grid-tagged and LGE images were acquired. Baseline LGE infarct hyperenhancement was categorised as ≤25 %, 26-50 %, 51-75 % and >75 % hyperenhancement. The segmental baseline circumferential strain (CS) and circumferential strain rate (CSR) were calculated from grid-tagged images. Segments demonstrating an improvement in wall motion of ≥1 grade compared to baseline were regarded as having improved segmental contractile-function. RESULTS: Forty-five patients (aged 58 ± 12 years) and 179 infarct segments were analysed. A baseline CS cutoff of -5 % had sensitivity of 89 % and specificity of 70 % for detection of improvement in segmental-contractile-function. On receiver-operating characteristic analysis for predicting improvement in contractile function, AUC for baseline CS (0.82) compared favourably to LGE hyperenhancement (0.68), MVO (0.67) and baseline-CSR (0.74). On comparison of AUCs, baseline CS was superior to LGE hyperenhancement and MVO in predicting improvement in contractile function (P < 0.001). On multivariate-analysis, baseline CS was the independent predictor of improvement in segmental contractile function (P < 0.001). CONCLUSION: Grid-tagged CMR-derived baseline CS is a superior predictor of improvement in segmental contractile function, providing incremental value when added to LGE hyperenhancement and MVO following STEMI. KEY POINTS: Baseline CS predicts contractile function recovery better than LGE and MVO following STEMI. Baseline CS predicts contractile function recovery better than baseline CSR following STEMI. Baseline CS provides incremental value to LGE and MVO following STEMI.

Magnetic resonance Spectroscopy with Linear Algebraic Modeling (SLAM) for higher speed and sensitivity.

Speed and signal-to-noise ratio (SNR) are critical for localized magnetic resonance spectroscopy (MRS) of low-concentration metabolites. Matching voxels to anatomical compartments a priori yields better SNR than the spectra created by summing signals from constituent chemical-shift-imaging (CSI) voxels post-acquisition. Here, a new method of localized Spectroscopy using Linear Algebraic Modeling (SLAM) is presented, that can realize this additional SNR gain. Unlike prior methods, SLAM generates spectra from C signal-generating anatomic compartments utilizing a CSI sequence wherein essentially only the C central k-space phase-encoding gradient steps with highest SNR are retained. After MRI-based compartment segmentation, the spectra are reconstructed by solving a sub-set of linear simultaneous equations from the standard CSI algorithm. SLAM is demonstrated with one-dimensional CSI surface coil phosphorus MRS in phantoms, the human leg and the heart on a 3T clinical scanner. Its SNR performance, accuracy, sensitivity to registration errors and inhomogeneity, are evaluated. Compared to one-dimensional CSI, SLAM yielded quantitatively the same results 4-times faster in 24 cardiac patients and healthy subjects. SLAM is further extended with fractional phase-encoding gradients that optimize SNR and/or minimize both inter- and intra-compartmental contamination. In proactive cardiac phosphorus MRS of six healthy subjects, both SLAM and fractional-SLAM (fSLAM) produced results indistinguishable from CSI while preserving SNR gains of 36-45% in the same scan-time. Both SLAM and fSLAM are simple to implement and reduce the minimum scan-time for CSI, which otherwise limits the translation of higher SNR achievable at higher field strengths to faster scanning.

Metabolomic approach by 1H NMR spectroscopy of serum for the assessment of chronic liver failure in patients with cirrhosis.

Assessment of chronic liver failure (CLF) in cirrhotic patients is needed to make therapeutic decisions. A biological score is usually performed, using the Model for End-Stage Liver Disease (MELD), to evaluate CLF. Nevertheless, MELD does not take into account metabolic perturbations produced by liver-function impairment. In contrast, metabolomics can investigate many metabolic perturbations within biological systems. The purpose of this study was to assess whether metabolomic profiles of serum, obtained by proton NMR spectroscopy from cirrhotic patients, are affected by the severity of CLF. An orthogonal projection to latent-structure analysis was performed to compare MELD scores and NMR spectra of 124 patients with cirrhosis. The statistical model obtained showed a good explained variance (R(2)X = 0.87 and R(2)Y = 0.86) and a good predictability (Q(2)Y = 0.64). Metabolomic profiles showed significant differences regarding various metabolites depending of severity of CLF: levels of high-density lipoprotein and phosphocholine resonances were significantly higher in patients with mild CLF compared to severe CLF. Other metabolites such as lactate, pyruvate, glucose, amino acids, and creatinine were significantly higher in patients with severe CLF than mild CLF. Our conclusion is that metabolomic NMR analysis provides new insights into metabolic processes related to the severity of hepatic function impairment in cirrhosis.

GPU accelerated Monte Carlo simulation of pulsed-field gradient NMR experiments.

The simulation of diffusion by Monte Carlo methods is often essential to describing NMR measurements of diffusion in porous media. However, simulation timescales must often span hundreds of milliseconds, with large numbers of trajectories required to ensure statistical convergence. Here we demonstrate that by parallelising code to run on graphics processing units (GPUs), these calculations may be accelerated by over three orders of magnitude, opening new frontiers in experimental design and analysis. As such cards are commonly installed on most desktop computers, we expect that this will prove useful in many cases where simple analytical descriptions are not available or appropriate, e.g. in complex geometries or where short gradient pulse approximations do not hold, or for the analysis of diffusion-weighted MRI in complex tissues such as the lungs and brain.

Combined magnetic resonance imaging and spectroscopy in the assessment of high grade prostate carcinoma in patients with elevated PSA: a single-institution experience of 356 patients.

PURPOSE: To assess the ability of combined whole-prostate magnetic resonance imaging and magnetic resonance spectroscopy imaging (MRI+MRSI) to predict the presence or absence of high grade (Gleason 4+3 or higher) prostate carcinoma in men with elevated PSA. MATERIALS AND METHODS: Between March 2002 and September 2007, 356 subjects (mean serum PSA 11.5 ng/ml, range 0.4-133.0 ng/ml) were examined with fast-T2-weighted magnetic resonance imaging (MRI) and 3D-magnetic resonance spectroscopy imaging (MRSI) on a 1.5T scanner. Prostate cancer was histopathologically proven in 220 patients (41 with high grade and 179 with lower grade cancer) and non-evidence of cancer was determined after at least 12 months (mean 21 months) clinical follow-up in 136 subjects. The sensitivity, false positive rate, and negative predictive value of MRI+MRSI were calculated using histopathology and follow-up results as reference standard. RESULTS: MRI+MRSI had a significantly higher sensitivity for high grade tumors (92.7%) than for lower grade tumors (67.6%), and was false positive in only 7.4% of patients with non-evidence of prostate cancer. For exclusion of a high grade tumor, MRI+MRSI had a negative predictive value of 98.4%. CONCLUSIONS: MRI+MRSI holds great potential for predicting presence or absence of high grade tumors in men with elevated PSA. This can be important in the selection of patients for active surveillance, or in the decision to rebiopsy patients with prior negative biopsies.

A Monte Carlo/simulated annealing algorithm for sequential resonance assignment in solid state NMR of uniformly labeled proteins with magic-angle spinning.

We describe a computational approach to sequential resonance assignment in solid state NMR studies of uniformly (15)N,(13)C-labeled proteins with magic-angle spinning. As input, the algorithm uses only the protein sequence and lists of (15)N/(13)C(alpha) crosspeaks from 2D NCACX and NCOCX spectra that include possible residue-type assignments of each crosspeak. Assignment of crosspeaks to specific residues is carried out by a Monte Carlo/simulated annealing algorithm, implemented in the program MC_ASSIGN1. The algorithm tolerates substantial ambiguity in residue-type assignments and coexistence of visible and invisible segments in the protein sequence. We use MC_ASSIGN1 and our own 2D spectra to replicate and extend the sequential assignments for uniformly-labeled HET-s(218-289) fibrils previously determined manually by Siemer et al. (J. Biomol. NMR, 34 (2006) 75-87) from a more extensive set of 2D and 3D spectra. Accurate assignments by MC_ASSIGN1 do not require data that are of exceptionally high quality. Use of MC_ASSIGN1 (and its extensions to other types of 2D and 3D data) is likely to alleviate many of the difficulties and uncertainties associated with manual resonance assignments in solid state NMR studies of uniformly labeled proteins, where spectral resolution and signal-to-noise are often sub-optimal.

Spectral estimation of irregularly sampled exponentially decaying signals with applications to RF spectroscopy.

The problem of estimating the spectral content of exponentially decaying signals from a set of irregularly sampled data is of considerable interest in several applications, for example in various forms of radio frequency spectroscopy. In this paper, we propose a new nonparametric iterative adaptive approach that provides a solution to this estimation problem. As opposed to commonly used methods in the field, the damping coefficient, or linewidth, is explicitly modeled, which allows for an improved estimation performance. Numerical examples using both simulated data and data from NQR experiments illustrate the benefits of the proposed estimator as compared to currently available nonparametric methods.

Effects of jump dynamics on solid state nuclear magnetic resonance line shapes and spin relaxation times.

This paper describes EXPRESS (EXchange Program for RElaxing Spin Systems), a computer program that simulates the effects of Markovian jump dynamics for a wide variety of solid state nuclear magnetic resonance experiments. A graphical interface is described that facilitates the definition of rotational jumps around non-commuting axes that may occur at arbitrary, different rates. Solid state deuteron NMR is widely used to investigate such processes, and EXPRESS allows simulations of deuteron quadrupole echo and magic angle spinning line (MAS) shapes, as well as partially relaxed line shapes for measurements of anisotropic relaxation of Zeeman and quadrupolar order. Facilities are included for chemical shift tensors (at user-defined orientations relative to the quadrupole coupling tensors), so that EXPRESS is potentially useful for studies of paramagnetic systems where these interactions are of comparable magnitude. Many of the same techniques used for deuterons can be extended to half-integer quadrupolar nuclei. The same interface that specifies rotational "sites" for deuteron NMR studies is usable in EXPRESS to simulate static line shapes, MAS line shapes, and multiple pulse Carr-Purcell-Meiboom-Gill (CPMG) line shapes for the central transition of high spin quadrupoles with second order quadrupole coupling and chemical shift anisotropy. Representative simulations are displayed that show effects of slow libration on deuteron quadrupole echo line shapes and relaxation time anisotropies. EXPRESS is also used to investigate fundamental differences in the mechanism of echo formation in deuteron MAS and quadrupole CPMG experiments, and to illustrate significant differences between these techniques in the context of high spin quadrupolar nuclei. The program is modular and platform-independent, with facilities for users to add routines for experiments not yet envisioned.

Assessment of metabolite quantitation reproducibility in serial 3D-(1)H-MR spectroscopic imaging of human brain using stereotactic repositioning.

Intrasubject reproducibility of metabolite quantitation in three-dimensional proton magnetic resonance spectroscopic imaging (3D-MRSI) was investigated in 10 healthy volunteers over five separate sessions using two echo times (TEs): 144 and 30 ms. The use of a Gill-Thomas-Cosman (GTC) stereotactic head frame enabled precise subject repositioning and immobilization. Metabolite levels from each voxel in the volume of interest (VOI) were quantified using the Linear Combination of Model spectra (LCModel) analysis algorithm, and coefficients of variation (CVs) were calculated. Standard error estimates (%SD or Cramer-Rao lower bounds) generated by LCModel were used as a confidence filter. The 95% confidence interval (CI) was found for each metabolite, providing an indication of the normal fluctuation expected for 3D-MRSI. In vivo, median CVs at the %SD < or = 20 level were found to be (%CV for TE = 144 and 30 ms, respectively): N-acetyl-aspartate plus N-acetyl-aspartyl-glutamate (NAA): 10.2% and 13.5%; creatine plus phosphocreatine (Cr), 14.4% and 21.7%; and choline-containing compounds (Cho), 15.2% and 18.4%. Relaxing the statistical filtering criteria to %SD < or = 30 increased median CVs by less than 5% and permitted in vivo quantitation reproducibility to be evaluated for glutamine plus glutamate (Glx) and myoinositol (Ins) for TE = 30 ms, yielding CVs of 24.0% and 21.0%, respectively.

Handling outliers in brain tumour MRS data analysis through robust topographic mapping.

Uncertainty is inherent in medical decision making and poses a challenge for intelligent technologies. This paper focuses on magnetic resonance spectra (MRS) for discrimination of brain tumour types and grades. Modelling of this type of high-dimensional data is commonly affected by uncertainty caused by the presence of outliers. Multivariate data clustering and visualization of MRS data is proposed using the GTM framework with basis functions comprising Student t-distributions in order to minimize the negative impact on the model from outliers. The effectiveness of this model on the MRS data is demonstrated empirically.

Noninvasive assessment of cardiac ischemic injury using (87)Rb and (23)Na MR imaging, (31)P MR, and optical spectroscopy.

The aim of the study was to compare and analyze different noninvasive indices of cell damage in the isolated pig heart model of regional ischemia. We used (23)Na and (87)Rb MR imaging to evaluate Na(+)/K(+) balance, (31)P MR spectroscopy to measure energetics, and optical spectroscopy to assess oxymyoglobin (MbO(2)). Hearts were subjected to 120-min occlusion of the left anterior descending artery and were then reperfused for 120 min. Reperfusion resulted in an increase in (23)Na (37 +/- 18% of the posterior wall) and decrease in (87)Rb (55 +/- 15%) image intensities, partial recovery of PCr, ATP, the total phosphates, and MbO(2) in the anterior wall. The above changes are consistent with the irreversible cell damage in the anterior wall, confirmed by lack of staining with triphenyltetrazolium chloride. Changes in Na(+) and Rb(+) in the infarct area inversely correlated and their ratio is a more sensitive index of cell injury than either of them alone.

Strong field behavior of the NMR signal from magnetically heterogeneous tissues.

A theory for the behavior of the nuclear magnetic resonance (NMR) signal obtained from magnetically heterogeneous tissues is developed for the limit of a strong external magnetic field. If BO is the magnitude of the external magnetic field, it is found that a free-induction signal decays in a time scaling as 1/Bo, a single-spin echo signal decays in a time scaling as 1/Bo(2/3), and a multiple-spin echo signal decays in a time scaling as 1/Bo(2). Moreover, it is shown that the form of the signal decay for a multiple-spin echo sequence may deviate significantly from an exponential. Numerical results for a model consisting of randomly distributed magnetic spheres are used to confirm the theory. In addition, good agreement is demonstrated between the theory and experimental measurements obtained with particle suspensions. The validity and application of the theory to biological tissues are discussed.

Changes in CT utilization between 1981 and 1984: implications for Medicare payment for MR imaging under the prospective payment system.

In the absence of data on current or likely patterns of use of magnetic resonance (MR) imaging, use of computed tomography (CT) at one institution in 1981 and 1984 was analyzed to provide data relevant to current federal deliberations regarding Medicare payment for inpatient MR imaging. Between 1981 and 1984 inpatient CT utilization increased 59%, primarily due to a 265% increase in body CT. In 1984 inpatients who underwent at least one CT procedure were as likely to undergo more than one procedure as to undergo only one. CT procedures were performed in a high proportion of diagnosis-related groups (DRGs), with more than one-half of head CT procedures performed in non-neurologic DRGs. Given the similarities between clinical applications of CT and MR imaging, these findings regarding CT utilization have the following implications: (a) a delay in recalibration of DRG payment rates may not take account of expected growth in utilization of MR imaging, (b) a DRG "add-on" for MR imaging should reflect the likelihood that more than one MR imaging procedure will be performed in many hospitalizations, and (c) adjustments in DRG payments for MR imaging should not be limited to the 35 neurologic DRGs.

Use of MR imaging in an outpatient MR center.

Indications for MR examinations and patient characteristics are evaluated for 4561 MR examinations performed at a freestanding outpatient MR imaging center between May 1984 and June 1986. Hospitalized patients accounted for less than 3% of the case load. Examinations of the head and spine accounted for 60% and 31% of the work load, respectively. Patients 65 years or older made up 15% of the case load during 1984 and 1985 and 21% in 1986. Referrals from neurologists, internists, and neurosurgeons accounted for 56%, 11% and 9% of patients, respectively. The percentage of patients who had CT, myelography, and other imaging procedures performed before referral for MR imaging declined significantly between 1984 and 1986. Indications for examination were mostly neoplastic diseases; degenerative diseases of the CNS, including multiple sclerosis; other disorders of the CNS; and disk diseases. Approximately 40% of all examinations were interpreted as normal. The number of patients referred for degenerative intervertebral disk disorders increased substantially between 1984 and 1985. This study documents the increasing acceptance of MR imaging as an important primary imaging technique for a variety of conditions, particularly those of the brain and spine.

Swiss Hospital Institute's approach to the problems of magnetic resonance imaging.

The Swiss Hospital Institute, a nonprofit institution that provides guidance on hospital planning and operation to Switzerland's health care community, conducted in 1984 a comprehensive study of magnetic resonance imaging (MRI) and magnetic resonance spectroscopy via a 17-member commission that examined all aspects of these emerging technologies. Future MRI utilization was estimated by developing five clinical categories of possible MRI use, based on ICD codes, and a probability of MRI utilization was developed for each category. By applying these probabilities to the number of inpatient admissions in each category, an annual nationwide volume of 20,000 scans was estimated. Ten MRI systems were considered adequate for a period of up to five years after the report's promulgation, based on a per-system annual throughput of 1,900-2,000 patients. A superconducting-magnet system with an 0.5-T field strength was deemed the most suitable, with units to be located in university hospitals. [Spectroscopy was considered best left to separate research installations.] The cost of equipment and construction for the 0.5-T superconducting magnet system were calculated as high as 3.6 million Swiss francs (Sfr) (approximately $1.65 million at fall 1985 exchange rates). the annual operating cost was estimated as Sfr 1.3 million ($600,000). On this basis a per-study fee of Sfr 690 ($315) was projected. The study recommended health insurance coverage of MRi use, only in patients with well-proven clinical indications for an MRI scan. The report is expected to aid in the orderly introduction of MRI into Switzerland's health care system.

The introduction of clinical magnetic resonance imaging in Australia.

Magnetic resonance imaging is a new, but expensive, modality that is being introduced into clinical use in Australia. While it promises increased safety and accuracy in many situations, its precise role when compared with computed tomography and other modalities is not fully established. Therefore, a Government financed evaluation of costs and efficacy of magnetic resonance imaging units in five teaching hospitals is to be conducted over two years (1986-1988). Experience with the introduction of computed tomography to Australia and other nations has revealed difficulties in the evaluation by conventional methods of a diagnostic technology that is improving rapidly; it is to be hoped that a systematic evaluation of the clinical applications of magnetic resonance imaging will be more achievable and useful. Open cooperation between the Commonwealth and State Governments and the medical profession in this evaluation should lead to a rational policy for the clinical availability of magnetic resonance imaging within Australia in the future.