Separation of small metabolites and lipids in spectra from biopsies by diffusion-weighted HR-MAS NMR: a feasibility study.

High Resolution Magic Angle Spinning (HR-MAS) NMR allows metabolic characterization of biopsies. HR-MAS spectra from tissues of most organs show strong lipid contributions that are overlapping metabolite regions, which hamper metabolite estimation. Metabolite quantification and analysis would benefit from a separation of lipids and small metabolites. Generally, a relaxation filter is used to reduce lipid contributions. However, the strong relaxation filter required to eliminate most of the lipids also reduces the signals for small metabolites. The aim of our study was therefore to investigate different diffusion editing techniques in order to employ diffusion differences for separating lipid and small metabolite contributions in the spectra from different organs for unbiased metabonomic analysis. Thus, 1D and 2D diffusion measurements were performed, and pure lipid spectra that were obtained at strong diffusion weighting (DW) were subtracted from those obtained at low DW, which include both small metabolites and lipids. This subtraction yielded almost lipid free small metabolite spectra from muscle tissue. Further improved separation was obtained by combining a 1D diffusion sequence with a T2-filter, with the subtraction method eliminating residual lipids from the spectra. Similar results obtained for biopsies of different organs suggest that this method is applicable in various tissue types. The elimination of lipids from HR-MAS spectra and the resulting less biased assessment of small metabolites have potential to remove ambiguities in the interpretation of metabonomic results. This is demonstrated in a reproducibility study on biopsies from human muscle.

Profile order and time-dependent artifacts in contrast-enhanced coronary MR angiography at 3T: origin and prevention.

To enhance the clinical value of coronary magnetic resonance angiography (MRA), high-relaxivity contrast agents have recently been used at 3T. Here we examine a uniform bilateral shadowing artifact observed along the coronary arteries in MRA images collected using such a contrast agent. Simulations were performed to characterize this artifact, including its origin, to determine how best to mitigate this effect, and to optimize a data acquisition/injection scheme. An intraluminal contrast agent concentration model was used to simulate various acquisition strategies with two profile orders for a slow-infusion of a high-relaxivity contrast agent. Filtering effects from temporally variable weighting in k-space are prominent when a centric, radial (CR) profile order is applied during contrast infusion, resulting in decreased signal enhancement and underestimation of vessel width, while both pre- and postinfusion steady-state acquisitions result in overestimation of the vessel width. Acquisition during the brief postinfusion steady-state produces the greatest signal enhancement and minimizes k-space filtering artifacts.

Spatially selective implementation of the adiabatic T2 prep sequence for magnetic resonance angiography of the coronary arteries.

In coronary magnetic resonance angiography, a magnetization-preparation scheme for T2 -weighting (T2 Prep) is widely used to enhance contrast between the coronary blood-pool and the myocardium. This prepulse is commonly applied without spatial selection to minimize flow sensitivity, but the nonselective implementation results in a reduced magnetization of the in-flowing blood and a related penalty in signal-to-noise ratio. It is hypothesized that a spatially selective T2 Prep would leave the magnetization of blood outside the T2 Prep volume unaffected and thereby lower the signal-to-noise ratio penalty. To test this hypothesis, a spatially selective T2 Prep was implemented where the user could freely adjust angulation and position of the T2 Prep slab to avoid covering the ventricular blood-pool and saturating the in-flowing spins. A time gap of 150 ms was further added between the T2 Prep and other prepulses to allow for in-flow of a larger volume of unsaturated spins. Consistent with numerical simulation, the spatially selective T2 Prep increased in vivo human coronary artery signal-to-noise ratio (42.3 ± 2.9 vs. 31.4 ± 2.2, n = 22, P < 0.0001) and contrast-to-noise-ratio (18.6 ± 1.5 vs. 13.9 ± 1.2, P = 0.009) as compared to those of the nonselective T2 Prep. Additionally, a segmental analysis demonstrated that the spatially selective T2 Prep was most beneficial in proximal and mid segments where the in-flowing blood volume was largest compared to the distal segments. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.

Imaging of tophaceous gout: computed tomography provides specific images compared with magnetic resonance imaging and ultrasonography.

OBJECTIVE: To determine the usefulness of computed tomography (CT), magnetic resonance imaging (MRI), and Doppler ultrasonography (US) in providing specific images of gouty tophi. METHODS: Four male patients with chronic gout with tophi affecting the knee joints (three cases) or the olecranon processes of the elbows (one case) were assessed. Crystallographic analyses of the synovial fluid or tissue aspirates of the areas of interest were made with polarising light microscopy, alizarin red staining, and x ray diffraction. CT was performed with a GE scanner, MR imaging was obtained with a 1.5 T Magneton (Siemens), and ultrasonography with colour Doppler was carried out by standard technique. RESULTS: Crystallographic analyses showed monosodium urate (MSU) crystals in the specimens of the four patients; hydroxyapatite and calcium pyrophosphate dihydrate (CPPD) crystals were not found. A diffuse soft tissue thickening was seen on plain radiographs but no calcifications or ossifications of the tophi. CT disclosed lesions containing round and oval opacities, with a mean density of about 160 Hounsfield units (HU). With MRI, lesions were of low to intermediate signal intensity on T(1) and T(2) weighting. After contrast injection in two cases, enhancement of the tophus was seen in one. Colour Doppler US showed the tophi to be hypoechogenic with peripheral increase of the blood flow in three cases. CONCLUSION: The MR and colour Doppler US images showed the tophi as masses surrounded by a hypervascular area, which cannot be considered as specific for gout. But on CT images, masses of about 160 HU density were clearly seen, which correspond to MSU crystal deposits.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Measuring ecological niche overlap from occurrence and spatial environmental data

1. Aim - Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.¦2. Location - Europe, North America, South America¦3. Methods - The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with predefined distributions and amounts of niche overlap to evaluate several ordination and species distribution modeling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.¦4. Results - We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographic space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.¦5. Main conclusions - The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate to study niche differences between species, subspecies or intraspecific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intraspecific lineage has changed over time.

Comparison of the polynomial model against explicit measurements of noise components for different mammography systems.

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.

Integrating detection probabilities in species distribution models of amphibians breeding in Mediterranean temporary ponds

Aim  The imperfect detection of species may lead to erroneous conclusions about species-environment relationships. Accuracy in species detection usually requires temporal replication at sampling sites, a time-consuming and costly monitoring scheme. Here, we applied a lower-cost alternative based on a double-sampling approach to incorporate the reliability of species detection into regression-based species distribution modelling.Location  Doñana National Park (south-western Spain).Methods  Using species-specific monthly detection probabilities, we estimated the detection reliability as the probability of having detected the species given the species-specific survey time. Such reliability estimates were used to account explicitly for data uncertainty by weighting each absence. We illustrated how this novel framework can be used to evaluate four competing hypotheses as to what constitutes primary environmental control of amphibian distribution: breeding habitat, aestivating habitat, spatial distribution of surrounding habitats and/or major ecosystems zonation. The study was conducted on six pond-breeding amphibian species during a 4-year period.Results  Non-detections should not be considered equivalent to real absences, as their reliability varied considerably. The occurrence of Hyla meridionalis and Triturus pygmaeus was related to a particular major ecosystem of the study area, where suitable habitat for these species seemed to be widely available. Characteristics of the breeding habitat (area and hydroperiod) were of high importance for the occurrence of Pelobates cultripes and Pleurodeles waltl. Terrestrial characteristics were the most important predictors of the occurrence of Discoglossus galganoi and Lissotriton boscai, along with spatial distribution of breeding habitats for the last species.Main conclusions  We did not find a single best supported hypothesis valid for all species, which stresses the importance of multiscale and multifactor approaches. More importantly, this study shows that estimating the reliability of non-detection records, an exercise that had been previously seen as a naïve goal in species distribution modelling, is feasible and could be promoted in future studies, at least in comparable systems.

Diffusion-weighted spectroscopy: a novel approach to determine macromolecule resonances in short-echo time 1H-MRS.

Quantification of short-echo time proton magnetic resonance spectroscopy results in >18 metabolite concentrations (neurochemical profile). Their quantification accuracy depends on the assessment of the contribution of macromolecule (MM) resonances, previously experimentally achieved by exploiting the several fold difference in T(1). To minimize effects of heterogeneities in metabolites T(1), the aim of the study was to assess MM signal contributions by combining inversion recovery (IR) and diffusion-weighted proton spectroscopy at high-magnetic field (14.1 T) and short echo time (= 8 msec) in the rat brain. IR combined with diffusion weighting experiments (with δ/Δ = 1.5/200 msec and b-value = 11.8 msec/μm(2)) showed that the metabolite nulled spectrum (inversion time = 740 msec) was affected by residuals attributed to creatine, inositol, taurine, choline, N-acetylaspartate as well as glutamine and glutamate. While the metabolite residuals were significantly attenuated by 50%, the MM signals were almost not affected (< 8%). The combination of metabolite-nulled IR spectra with diffusion weighting allows a specific characterization of MM resonances with minimal metabolite signal contributions and is expected to lead to a more precise quantification of the neurochemical profile.

Infrequent transmission of HIV-1 drug-resistant variants.

Transmission of drug-resistant variants is influenced by several factors, including the prevalence of drug resistance in the population of HIV-1-infected patients, HIV-1 RNA levels and transmission by recently infected patients. In order to evaluate the impact of these factors on the transmission of drug-resistant variants, we have defined the population of potential transmitters and compared their resistance profiles to those of newly infected patients. Sequencing of pol gene was performed in 220 recently infected patients and in 373 chronically infected patients with HIV-1 RNA >1000 copies/ml. Minimal and maximal drug-resistance profiles of potential transmitters were estimated by weighting resistance profiles of chronically infected patients with estimates of the Swiss HIV-1-infected population, the prevalence of exposure to antiviral drugs and the proportion of infections attributed to primary HIV infections. The drug-resistance prevalence in recently infected patients was 10.5% (one class drug resistance: 9.1%; two classes: 1.4%; three classes: 0%). Phylogenetic analysis revealed significant clustering for 30% of recent infections. The drug-resistance prevalence in chronically infected patients was 72.4% (one class: 29%; two classes: 27.6%; three classes: 15.8%). After adjustment, the risk of transmission relative to wild-type was reduced both for one class drug resistance (minimal and maximal estimates: odds ratio: 0.39, P<0.001; and odds ratio: 0.55, P=0.011, respectively), and for two to three class drug resistance (odds ratios: 0.05 and 0.07, respectively, P<0.001). Neither sexual behaviour nor HIV-1 RNA levels explained the low transmission of drug-resistant variants. These data suggest that drug-resistant variants and in particular multidrug-resistant variants have a substantially reduced transmission capacity.

Transfer insensitive labeling technique (TILT): application to multislice functional perfusion imaging.

Cerebral blood flow can be studied in a multislice mode with a recently proposed perfusion sequence using inversion of water spins as an endogenous tracer without magnetization transfer artifacts. The magnetization transfer insensitive labeling technique (TILT) has been used for mapping blood flow changes at a microvascular level under motor activation in a multislice mode. In TILT, perfusion mapping is achieved by subtraction of a perfusion-sensitized image from a control image. Perfusion weighting is accomplished by proximal blood labeling using two 90 degrees radiofrequency excitation pulses. For control preparation the labeling pulses are modified such that they have no net effect on blood water magnetization. The percentage of blood flow change, as well as its spatial extent, has been studied in single and multislice modes with varying delays between labeling and imaging. The average perfusion signal change due to activation was 36.9 +/- 9.1% in the single-slice experiments and 38.1 +/- 7.9% in the multislice experiments. The volume of activated brain areas amounted to 1.51 +/- 0.95 cm3 in the contralateral primary motor (M1) area, 0.90 +/- 0.72 cc in the ipsilateral M1 area, 1.27 +/- 0.39 cm3 in the contralateral and 1.42 +/- 0.75 cm3 in the ipsilateral premotor areas, and 0.71 +/- 0.19 cm3 in the supplementary motor area.

High b-value diffusion-weighted imaging: A sensitive method to reveal white matter differences in schizophrenia.

Over the last 10 years, diffusion-weighted imaging (DWI) has become an important tool to investigate white matter (WM) anomalies in schizophrenia. Despite technological improvement and the exponential use of this technique, discrepancies remain and little is known about optimal parameters to apply for diffusion weighting during image acquisition. Specifically, high b-value diffusion-weighted imaging known to be more sensitive to slow diffusion is not widely used, even though subtle myelin alterations as thought to happen in schizophrenia are likely to affect slow-diffusing protons. Schizophrenia patients and healthy controls were scanned with a high b-value (4000s/mm(2)) protocol. Apparent diffusion coefficient (ADC) measures turned out to be very sensitive in detecting differences between schizophrenia patients and healthy volunteers even in a relatively small sample. We speculate that this is related to the sensitivity of high b-value imaging to the slow-diffusing compartment believed to reflect mainly the intra-axonal and myelin bound water pool. We also compared these results to a low b-value imaging experiment performed on the same population in the same scanning session. Even though the acquisition protocols are not strictly comparable, we noticed important differences in sensitivities in the favor of high b-value imaging, warranting further exploration.

Pattern recognition ecological niche models fit to presence-only and presence-absence data

1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable. 2. We studied nine methods for one-class classification and seven methods for two-class classification (five common to both), all primarily used in pattern recognition and therefore not common in species distribution and ecological niche modelling, across a set of 106 mountain plant species for which presence-absence data was available. We assessed accuracy using standard metrics and compared trade-offs in omission and commission errors between classification groups as well as effects of prevalence and spatial autocorrelation on accuracy. 3. One-class models fit to presence-only data were comparable to two-class models fit to presence-absence data when performance was evaluated with a measure weighting omission and commission errors equally. One-class models were superior for reducing omission errors (i.e. yielding higher sensitivity), and two-classes models were superior for reducing commission errors (i.e. yielding higher specificity). For these methods, spatial autocorrelation was only influential when prevalence was low. 4. These results differ from previous efforts to evaluate alternative modelling approaches to build ENM and are particularly noteworthy because data are from exhaustively sampled populations minimizing false absence records. Accurate, transferable models of species' ecological niches and distributions are needed to advance ecological research and are crucial for effective environmental planning and conservation; the pattern-recognition approaches studied here show good potential for future modelling studies. This study also provides an introduction to promising methods for ecological modelling inherited from the pattern-recognition discipline.

Assessment of letrozole and tamoxifen alone and in sequence for postmenopausal women with steroid hormone receptor-positive breast cancer: the BIG 1-98 randomised clinical trial at 8·1 years median follow-up.

BACKGROUND: Postmenopausal women with hormone receptor-positive early breast cancer have persistent, long-term risk of breast-cancer recurrence and death. Therefore, trials assessing endocrine therapies for this patient population need extended follow-up. We present an update of efficacy outcomes in the Breast International Group (BIG) 1-98 study at 8·1 years median follow-up. METHODS: BIG 1-98 is a randomised, phase 3, double-blind trial of postmenopausal women with hormone receptor-positive early breast cancer that compares 5 years of tamoxifen or letrozole monotherapy, or sequential treatment with 2 years of one of these drugs followed by 3 years of the other. Randomisation was done with permuted blocks, and stratified according to the two-arm or four-arm randomisation option, participating institution, and chemotherapy use. Patients, investigators, data managers, and medical reviewers were masked. The primary efficacy endpoint was disease-free survival (events were invasive breast cancer relapse, second primaries [contralateral breast and non-breast], or death without previous cancer event). Secondary endpoints were overall survival, distant recurrence-free interval (DRFI), and breast cancer-free interval (BCFI). The monotherapy comparison included patients randomly assigned to tamoxifen or letrozole for 5 years. In 2005, after a significant disease-free survival benefit was reported for letrozole as compared with tamoxifen, a protocol amendment facilitated the crossover to letrozole of patients who were still receiving tamoxifen alone; Cox models and Kaplan-Meier estimates with inverse probability of censoring weighting (IPCW) are used to account for selective crossover to letrozole of patients (n=619) in the tamoxifen arm. Comparison of sequential treatments to letrozole monotherapy included patients enrolled and randomly assigned to letrozole for 5 years, letrozole for 2 years followed by tamoxifen for 3 years, or tamoxifen for 2 years followed by letrozole for 3 years. Treatment has ended for all patients and detailed safety results for adverse events that occurred during the 5 years of treatment have been reported elsewhere. Follow-up is continuing for those enrolled in the four-arm option. BIG 1-98 is registered at clinicaltrials.govNCT00004205. FINDINGS: 8010 patients were included in the trial, with a median follow-up of 8·1 years (range 0-12·4). 2459 were randomly assigned to monotherapy with tamoxifen for 5 years and 2463 to monotherapy with letrozole for 5 years. In the four-arm option of the trial, 1546 were randomly assigned to letrozole for 5 years, 1548 to tamoxifen for 5 years, 1540 to letrozole for 2 years followed by tamoxifen for 3 years, and 1548 to tamoxifen for 2 years followed by letrozole for 3 years. At a median follow-up of 8·7 years from randomisation (range 0-12·4), letrozole monotherapy was significantly better than tamoxifen, whether by IPCW or intention-to-treat analysis (IPCW disease-free survival HR 0·82 [95% CI 0·74-0·92], overall survival HR 0·79 [0·69-0·90], DRFI HR 0·79 [0·68-0·92], BCFI HR 0·80 [0·70-0·92]; intention-to-treat disease-free survival HR 0·86 [0·78-0·96], overall survival HR 0·87 [0·77-0·999], DRFI HR 0·86 [0·74-0·998], BCFI HR 0·86 [0·76-0·98]). At a median follow-up of 8·0 years from randomisation (range 0-11·2) for the comparison of the sequential groups with letrozole monotherapy, there were no statistically significant differences in any of the four endpoints for either sequence. 8-year intention-to-treat estimates (each with SE ≤1·1%) for letrozole monotherapy, letrozole followed by tamoxifen, and tamoxifen followed by letrozole were 78·6%, 77·8%, 77·3% for disease-free survival; 87·5%, 87·7%, 85·9% for overall survival; 89·9%, 88·7%, 88·1% for DRFI; and 86·1%, 85·3%, 84·3% for BCFI. INTERPRETATION: For postmenopausal women with endocrine-responsive early breast cancer, a reduction in breast cancer recurrence and mortality is obtained by letrozole monotherapy when compared with tamoxifen montherapy. Sequential treatments involving tamoxifen and letrozole do not improve outcome compared with letrozole monotherapy, but might be useful strategies when considering an individual patient's risk of recurrence and treatment tolerability. FUNDING: Novartis, United States National Cancer Institute, International Breast Cancer Study Group.

MP2RAGE Multiple Sclerosis Magnetic Resonance Imaging at 3 T.

OBJECTIVES: Lesion detection and characterization in multiple sclerosis (MS) are an essential part of its clinical diagnosis and an important research field. In this pilot study, we applied the recently introduced two inversion-contrast magnetization-prepared rapid gradient echo sequence (MP2RAGE) to patients with early-stage MS.¦MATERIALS AND METHODS: The MP2RAGE is a 3-dimensional (3D) magnetization-prepared rapid gradient echo derivative providing homogeneous T1 weighting and simultaneous T1 mapping. The MP2RAGE performance was compared with that of 2 clinical routine sequences (2D fluid-attenuated inversion recovery [FLAIR] and 3D magnetization-prepared rapid gradient echo [MP-RAGE]) and 2 state-of-the art clinical research sequences (the 3D FLAIR-SPACE [sampling perfection with application-optimized contrasts by using different flip-angle evolutions], a fluid-attenuated variable flip-angle fast spin echo technique, and the 3D double-inversion recovery SPACE). A cohort of 10 early-stage female MS patients (age, 31.6 ± 4.7 years; disease duration, 3.8 ± 1.9 years; median expanded disability status scale score, 1.75) and 10 age- and gender-matched controls were enrolled after approval of the local institutional review board was obtained. Multiple sclerosis lesions were identified and assigned to brain locations and tissue types by two experienced physicians in all 5 contrasts. Subsequently, lesions were manually delineated for comparison and statistical analysis of lesion count, volume and quantitative measures.¦RESULTS AND CONCLUSIONS: The results show that the 3D T1-weighted high-resolution MP2RAGE contrast provides a sensitive means for MS lesion assessment. The additional quantitative T1 relaxation time maps obtained with the MP2RAGE provide further potential diagnostic and prognostic information that could help (a) to better discriminate lesion subtypes and (b) to stage and predict the activity and the evolution of MS. Results also indicate that the T2-weighted double-inversion recovery and FLAIR-SPACE contrasts are attractive complements to the MP2RAGE for lesion detection.