Advanced MRI unravels the nature of tissue alterations in early multiple sclerosis.

INTRODUCTION: In patients with multiple sclerosis (MS), conventional magnetic resonance imaging (MRI) provides only limited insights into the nature of brain damage with modest clinic-radiological correlation. In this study, we applied recent advances in MRI techniques to study brain microstructural alterations in early relapsing-remitting MS (RRMS) patients with minor deficits. Further, we investigated the potential use of advanced MRI to predict functional performances in these patients. METHODS: Brain relaxometry (T1, T2, T2*) and magnetization transfer MRI were performed at 3T in 36 RRMS patients and 18 healthy controls (HC). Multicontrast analysis was used to assess for microstructural alterations in normal-appearing (NA) tissue and lesions. A generalized linear model was computed to predict clinical performance in patients using multicontrast MRI data, conventional MRI measures as well as demographic and behavioral data as covariates. RESULTS: Quantitative T2 and T2* relaxometry were significantly increased in temporal normal-appearing white matter (NAWM) of patients compared to HC, indicating subtle microedema (P = 0.03 and 0.004). Furthermore, significant T1 and magnetization transfer ratio (MTR) variations in lesions (mean T1 z-score: 4.42 and mean MTR z-score: -4.09) suggested substantial tissue loss. Combinations of multicontrast and conventional MRI data significantly predicted cognitive fatigue (P = 0.01, Adj-R (2) = 0.4), attention (P = 0.0005, Adj-R (2) = 0.6), and disability (P = 0.03, Adj-R (2) = 0.4). CONCLUSION: Advanced MRI techniques at 3T, unraveled the nature of brain tissue damage in early MS and substantially improved clinical-radiological correlations in patients with minor deficits, as compared to conventional measures of disease.

Diagnostic contribution of cardiac magnetic resonance in patients with acute coronary syndrome and culprit-free angiograms.

BACKGROUND: In spite of robust knowledge about underlying ischemic myocardial damage, acute coronary syndromes (ACS) with culprit-free angiograms raise diagnostic concerns. The present study aimed to evaluate the additional value of cardiac magnetic resonance (CMR) over commonly available non-CMR standard tests, for the differentiation of myocardial injury in patients with ACS and non-obstructed coronary arteries. MATERIAL/METHODS: Patients with ACS, elevated hs-TnT, and a culprit-free angiogram were prospectively enrolled into the study between January 2009 and July 2013. After initial evaluation with standard tests (ECG, echocardiography, hs-TnT) and provisional exclusion of acute myocardial infarction (AMI) in coronary angiogram, patients were referred for CMR with the suspicion of myocarditis or Takotsubo cardiomyopathy (TTC). According to the result of CMR, patients were reclassified as having myocarditis, AMI, TTC, or non-injured myocardium as assessed by late gadolinium enhancement. RESULTS: Out of 5110 patients admitted with ACS, 75 had normal coronary angiograms and entered the study; 69 of them (92%) were suspected for myocarditis and 6 (8%) for TTC. After CMR, 49 patients were finally diagnosed with myocarditis (65%), 3 with TTC (4%), 7 with AMI (9%), and 16 (21%) with non-injured myocardium. The provisional diagnosis was changed or excluded in 23 patients (31%), with a 9% rate of unrecognized AMI. CONCLUSIONS: The study results suggest that the evaluation of patients with ACS and culprit-free angiogram should be complemented by a CMR examination, if available, because the initial work-up with non-CMR tests leads to a significant proportion of misdiagnosed AMI.

Nuclear magnetic resonance

This article reviews the principles and methods of nuclear magnetic resonance spectroscopy, and gives examples of applications carried out at ourFacility, which illustrate the capabilities of the technique.

Helical tomotherapy in the treatment of anal canal cancer: 3-year clinical experience

Objective: To report a single-center experience treating patients with squamous- cell carcinoma of the anal canal using helical Tomotherapy (HT) and concurrent chemotherapy (CT).Materials/Methods: From October 2007 to February 2011, 55 patients were treated with HT and concurrent CT (5-fluorouracil/capecitabin and mitomycin) for anal squamous-cell carcinoma. All patients underwent computed- tomography-based treatment planning, with pelvic and inguinal nodes receiving 36 Gy in 1.8 Gy/fraction. Following a planned 1-week break, primary tumor site and involved nodes were boosted to a total dose 59.4 Gy in 1.8 Gy/fraction. Dose-volume histograms of several organs at risk (OAR; bladder, small intestine, rectum, femoral heads, penile bulb, external genitalia) were assessed in terms of conformal avoidance. All toxicity was scored according to the CTCAE, v.3.0. HT plans and treatment were implemented using the Tomotherapy, Inc. software and hardware. For dosimetric comparisons, 3D RT and/or IMRT plans were also computed for some of the patients using the CMS planning system, for treatment with 6-18 MV photons and/or electrons with suitable energies from a Siemens Primus linear accelerator equipped with a multileaf collimator.Locoregional control and survival curves were compared with the log-rank test, and multivariate analysis by the Cox model.Results: With 360-degree-of-freedom beam projection, HT has an advantage over other RT techniques (3D or 5-field step-and-shot IMRT). There is significant improvement over 3D or 5-field IMRT plans in terms of dose conformity around the PTV, and dose gradients are steeper outside the target volume, resulting in reduced doses to OARs. Using HT, acute toxicity was acceptable, and seemed to be better than historical standards.Conclusions: Our results suggest that HT combined with concurrent CT for anal cancer is effective and tolerable. Compared to 3D RT or 5-field step-andshot IMRT, there is better conformity around the PTV, and better OAR sparing.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Investigation of high-resolution functional magnetic resonance imaging by means of surface and array radiofrequency coils at 7 T.

In this investigation, high-resolution, 1x1x1-mm(3) functional magnetic resonance imaging (fMRI) at 7 T is performed using a multichannel array head coil and a surface coil approach. Scan geometry was optimized for each coil separately to exploit the strengths of both coils. Acquisitions with the surface coil focused on partial brain coverage, while whole-brain coverage fMRI experiments were performed with the array head coil. BOLD sensitivity in the occipital lobe was found to be higher with the surface coil than with the head array, suggesting that restriction of signal detection to the area of interest may be beneficial for localized activation studies. Performing independent component analysis (ICA) decomposition of the fMRI data, we consistently detected BOLD signal changes and resting state networks. In the surface coil data, a small negative BOLD response could be detected in these resting state network areas. Also in the data acquired with the surface coil, two distinct components of the positive BOLD signal were consistently observed. These two components were tentatively assigned to tissue and venous signal changes.

Shielding requirements in helical tomotherapy.

Helical tomotherapy is a relatively new intensity-modulated radiation therapy (IMRT) treatment for which room shielding has to be reassessed for the following reasons. The beam-on-time needed to deliver a given target dose is increased and leads to a weekly workload of typically one order of magnitude higher than that for conventional radiation therapy. The special configuration of tomotherapy units does not allow the use of standard shielding calculation methods. A conventional linear accelerator must be shielded for primary, leakage and scatter photon radiations. For tomotherapy, primary radiation is no longer the main shielding issue since a beam stop is mounted on the gantry directly opposite the source. On the other hand, due to the longer irradiation time, the accelerator head leakage becomes a major concern. An analytical model based on geometric considerations has been developed to determine leakage radiation levels throughout the room for continuous gantry rotation. Compared to leakage radiation, scatter radiation is a minor contribution. Since tomotherapy units operate at a nominal energy of 6 MV, neutron production is negligible. This work proposes a synthetic and conservative model for calculating shielding requirements for the Hi-Art II TomoTherapy unit. Finally, the required concrete shielding thickness is given for different positions of interest.

Détection des lésions focales hépatiques malignes. Comparaison de l'échographie, de la porto-tomodensitométrie, de la tomodensitométrie tardive et de l'imagerie par résonance magnétique [Detection of malignant focal hepatic lesions. Comparison of ultrasonography, computerized tomography during arterial portography, delayed computerized tomography and magnetic resonance imaging]

AIMS: This study was performed to compare the sensitivity of ultrasonography, computerized tomography during arterial portography, delayed computerized tomography, and magnetic resonance imaging to detect focal liver lesions. Forty three patients with primary or secondary malignant liver lesions were studied prior to surgical intervention. METHODS: The results of the imaging studies were compared with intraoperative examination of the liver, intraoperative ultrasonography and pathology results (29 patients). In the non-operated (14 patients) group, we compared the number of lesions detected by each technique. RESULTS: One hundred and forty six lesions were detected. There was 84% sensitivity with computerized tomography during arterial portography, 61.3% with delayed scan, 63.3% with magnetic resonance imaging and 51% with ultrasonography in operated patients. In patients who did not undergo surgery, magnetic resonance imaging was more sensitive in detecting lesions. CONCLUSIONS: In operated and non-operated patients series, CT during arterial portography had the highest sensitivity, but magnetic resonance imaging had the most consistent overall results.

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

Selective resonance suppression 1H-[13C] NMR spectroscopy with asymmetric adiabatic RF pulses.

Despite obvious improvements in spectral resolution at high magnetic field, the detection of 13C labeling by 1H-[13C] NMR spectroscopy remains hampered by spectral overlap, such as in the spectral region of 1H resonances bound to C3 of glutamate (Glu) and glutamine (Gln), and C6 of N-acetylaspartate (NAA). The aim of this study was to develop, implement, and apply a novel 1H-[13C] NMR spectroscopic editing scheme, dubbed "selective Resonance suppression by Adiabatic Carbon Editing and Decoupling single-voxel STimulated Echo Acquisition Mode" (RACED-STEAM). The sequence is based on the application of two asymmetric narrow-transition-band adiabatic RF inversion pulses at the resonance frequency of the 13C coupled to the protons that need to be suppressed during the mixing time (TM) period, alternating the inversion band downfield and upfield from the 13C resonance on odd and even scans, respectively, thus suppressing the detection of 1H resonances bound to 13C within the transition band of the inversion pulse. The results demonstrate the efficient suppression of 1H resonances bound to C3 of Glu and Gln, and C4 of Glu, which allows the 1H resonances bound to C6 of NAA and C4 of Gln to be revealed. The measured time course of the resolved labeling into NAA C6 with the new scheme was consistent with the slow turnover of NAA.

A review of atlas-based segmentation for magnetic resonance brain images.

Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.

SAT Modulo Linear Arithmetic for Solving Polynomial

Polynomial constraint solving plays a prominent role in several areas of hardware and software analysis and verification, e.g., termination proving, program invariant generation and hybrid system verification, to name a few. In this paper we propose a new method for solving non-linear constraints based on encoding the problem into an SMT problem considering only linear arithmetic. Unlike other existing methods, our method focuses on proving satisfiability of the constraints rather than on proving unsatisfiability, which is more relevant in several applications as we illustrate with several examples. Nevertheless, we also present new techniques based on the analysis of unsatisfiable cores that allow one to efficiently prove unsatisfiability too for a broad class of problems. The power of our approach is demonstrated by means of extensive experiments comparing our prototype with state-of-the-art tools on benchmarks taken both from the academic and the industrial world.

Can 3T multiparametric magnetic resonance imaging accurately detect prostate cancer extracapsular extension?

BACKGROUND: Accurate staging is essential to determine the correct management of patients diagnosed with prostate cancer. We assess the accuracy of 3T multiparametric magnetic resonance imaging (MRI) with endorectal coil (3TemMRI) in detecting prostate cancer local extension. METHODS: We retrospectively reviewed charts from January 2008 to July 2012 from all patients undergoing radical prostatectomy. Patients were only included if 3TemMRI and radical prostatectomy were performed at our institution. Based on the presence of extracapsular extension (ECE) at 3TemMRI, prostate cancer was dichotomized into locally advanced or organ-confined disease. The accuracy of 3TemMRI local staging was then evaluated using definitive pathology as a reference. RESULTS: Overall, 177 radical prostatectomies were performed within the timeframe. After applying exclusion criteria, 60 patients were included in the final analysis. The mean patient age was 67 ± 7 (standard deviation) years. Mean prostate-specific antigen value was 12.7 ± 12.7 ng/L. Based on preoperative characteristics, we considered 38 of the 60 patients (63%) patients high risk. 3TemMRI identified an organ-confined tumour in 46 patients and locally advanced disease in 14 patients. When correlated to final pathology, 3TemMRI specificity, sensitivity, negative and positive predictive values, and accuracy in detecting locally advanced prostate cancer were 90%, 35%, 57%, 79% and 62%, respectively. INTERPRETATION: This study shows that the use of preoperative 3TemMRI can be used to identify organ-confined prostate cancer when locally advanced disease is suspected.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.