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.

Diagnostic value of MRI for the detection of suspected placental invasion: Does it depend on observers' experience?

Purpose: To evaluate the diagnostic value of specific MR features for detection of suspected placental invasion according to observers' experience.Methods and Materials: Our study population included 25 pregnant women (mean age 35.16) investigated by prenatal MRI. In twelve out of them placental invasion was histopathologically proven, the 13 other women (52%) without placental invasion served as control group. Multiplanar T1- and T2-weighted sequences had been performed mostly without IV contrast injection (1.5 T). MR examinations of the two groups were rendered anonymous, mixed, then independently and retrospectively reviewed by two senior and two junior radiologists in view of 8 MR features indicating placentar invasion including the degree. Results were compared with surgical diagnosis (placenta normal/increta/accreta/percreta). Interobserver agrement between senior and junior readers were calculated. Stepwise logistic regression and receiver operating (ROC) curvers were performed.Results: Demographics between the two groups were not statistically different. Overall sensitivity and specificity for detecting placentar invasion was 90.9% and 75.0% for senior readers, and 81.8% and 61.8% for junior readers respectively. The most significant MR features indicating placentar invasion were T2 hypointense placental bands, followed by placenta praevia, focally interrupted myometrial border, posterior placental insertion, and heterogeneous placental signal. For each of the evaluated MR features the interobserver agreement kappa between the two senior readers was superior than that between the junior readers, ranging from bad (<0.4) to good (0.4-0.75).Conclusions: MRI can be a reliable and reproducible tool for detection of suspected placentar invasion, however very variable according to the observers' experience.

Whole-body 3D T1-weighted MR imaging in patients with prostate cancer: feasibility and evaluation in screening for metastatic disease.

PURPOSE: To develop and assess the diagnostic performance of a three-dimensional (3D) whole-body T1-weighted magnetic resonance (MR) imaging pulse sequence at 3.0 T for bone and node staging in patients with prostate cancer. MATERIALS AND METHODS This prospective study was approved by the institutional ethics committee; informed consent was obtained from all patients. Thirty patients with prostate cancer at high risk for metastases underwent whole-body 3D T1-weighted imaging in addition to the routine MR imaging protocol for node and/or bone metastasis screening, which included coronal two-dimensional (2D) whole-body T1-weighted MR imaging, sagittal proton-density fat-saturated (PDFS) imaging of the spine, and whole-body diffusion-weighted MR imaging. Two observers read the 2D and 3D images separately in a blinded manner for bone and node screening. Images were read in random order. The consensus review of MR images and the findings at prospective clinical and MR imaging follow-up at 6 months were used as the standard of reference. The interobserver agreement and diagnostic performance of each sequence were assessed on per-patient and per-lesion bases. RESULTS: The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were significantly higher with whole-body 3D T1-weighted imaging than with whole-body 2D T1-weighted imaging regardless of the reference region (bone or fat) and lesion location (bone or node) (P < .003 for all). For node metastasis, diagnostic performance (area under the receiver operating characteristic curve) was higher for whole-body 3D T1-weighted imaging (per-patient analysis; observer 1: P < .001 for 2D T1-weighted imaging vs 3D T1-weighted imaging, P = .006 for 2D T1-weighted imaging + PDFS imaging vs 3D T1-weighted imaging; observer 2: P = .006 for 2D T1-weighted imaging vs 3D T1-weighted imaging, P = .006 for 2D T1-weighted imaging + PDFS imaging vs 3D T1-weighted imaging), as was sensitivity (per-lesion analysis; observer 1: P < .001 for 2D T1-weighted imaging vs 3D T1-weighted imaging, P < .001 for 2D T1-weighted imaging + PDFS imaging vs 3D T1-weighted imaging; observer 2: P < .001 for 2D T1-weighted imaging vs 3D T1-weighted imaging, P < .001 for 2D T1-weighted imaging + PDFS imaging vs 3D T1-weighted imaging). CONCLUSION: Whole-body MR imaging is feasible with a 3D T1-weighted sequence and provides better SNR and CNR compared with 2D sequences, with a diagnostic performance that is as good or better for the detection of bone metastases and better for the detection of lymph node metastases.

Complete and long-lasting regression of disseminated multiple skin melanoma metastases under treatment with cyclooxygenase-2 inhibitor.

Experimental and clinical evidence indicates that non-steroidal anti-inflammatory drugs and cyclooxygenase-2 inhibitors may have anti-cancer activities. Here we report on a patient with a metastatic melanoma of the leg who experienced a complete and sustained regression of skin metastases upon continuous single treatment with the cyclooxygenase-2 inhibitor rofecoxib. Our observations indicate that the inhibition of cyclooxygenase-2 can lead to the regression of disseminated skin melanoma metastases, even after failure of chemotherapy.

Accurate calculations of intermolecular interaction energies using explicitly correlated coupled cluster wave functions and a dispersion-weighted MP2 method.

Explicitly correlated coupled-cluster calculations of intermolecular interaction energies for the S22 benchmark set of Jurecka, Sponer, Cerny, and Hobza (Chem. Phys. Phys. Chem. 2006, 8, 1985) are presented. Results obtained with the recently proposed CCSD(T)-F12a method and augmented double-zeta basis sets are found to be in very close agreement with basis set extrapolated conventional CCSD(T) results. Furthermore, we propose a dispersion-weighted MP2 (DW-MP2) approximation that combines the good accuracy of MP2 for complexes with predominately electrostatic bonding and SCS-MP2 for dispersion-dominated ones. The MP2-F12 and SCS-MP2-F12 correlation energies are weighted by a switching function that depends on the relative HF and correlation contributions to the interaction energy. For the S22 set, this yields a mean absolute deviation of 0.2 kcal/mol from the CCSD(T)-F12a results. The method, which allows obtaining accurate results at low cost, is also tested for a number of dimers that are not in the training set.

Molecular Proxies for Climate Maladaptation in a Long-Lived Tree (Pinus pinaster Aiton, Pinaceae).

Understanding adaptive genetic responses to climate change is a main challenge for preserving biological diversity. Successful predictive models for climate-driven range shifts of species depend on the integration of information on adaptation, including that derived from genomic studies. Long-lived forest trees can experience substantial environmental change across generations, which results in a much more prominent adaptation lag than in annual species. Here, we show that candidate-gene SNPs (single nucleotide polymorphisms) can be used as predictors of maladaptation to climate in maritime pine (Pinus pinaster Aiton), an outcrossing long-lived keystone tree. A set of 18 SNPs potentially associated with climate, 5 of them involving amino acid-changing variants, were retained after performing logistic regression, latent factor mixed models, and Bayesian analyses of SNP-climate correlations. These relationships identified temperature as an important adaptive driver in maritime pine and highlighted that selective forces are operating differentially in geographically discrete gene pools. The frequency of the locally advantageous alleles at these selected loci was strongly correlated with survival in a common garden under extreme (hot and dry) climate conditions, which suggests that candidate-gene SNPs can be used to forecast the likely destiny of natural forest ecosystems under climate change scenarios. Differential levels of forest decline are anticipated for distinct maritime pine gene pools. Geographically defined molecular proxies for climate adaptation will thus critically enhance the predictive power of range-shift models and help establish mitigation measures for long-lived keystone forest trees in the face of impending climate change.

What is the influence of vaccination's routes on the regression of tumors located at mucosal sites?

Tumor-regressions following tumor-associated-antigen vaccination in animal models contrast with the limited clinical outcomes in cancer patients. Most animal studies however used subcutaneous-tumor-models and questions arise as whether these are relevant for tumors growing in mucosae; whether specific mucosal-homing instructions are required; and how this may be influenced by the tumor.

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.

Geomodelling of a fluvial system with semi-supervised support vector regression

Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance

Testing Spatial Autocorrelation in Weighted Networks : the Modes Permutation Test

In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

Method for performing cerebral perfusion-weighted MRI in neonates

Cerebral perfusion-weighted imaging (PWI) in neonates is known to be technically difficult and there are very few published studies on its use in preterm infants. In this paper, we describe one convenient method to perform PWI in neonates, a method only recently used in newborns. A device was used to manually inject gadolinium contrast material intravenously in an easy, quick and reproducible way. We studied 28 newborn infants, with various gestational ages and weights, including both normal infants and those suffering from different brain pathologies. A signal intensity-time curve was obtained for each infant, allowing us to build perfusion maps. This technique offered a fast and easy method to manually inject a bolus gadolinium contrast material, which is essential in performing PWI in neonates. Cerebral PWI is technically feasible and reproducible in neonates of various gestational age and with various pathologies.

Retrospective feasibility study of simultaneous integrated boost in cervical cancer using Tomotherapy: the impact of organ motion and tumor regression.

BACKGROUND: Whole pelvis intensity modulated radiotherapy (IMRT) is increasingly being used to treat cervical cancer aiming to reduce side effects. Encouraged by this, some groups have proposed the use of simultaneous integrated boost (SIB) to target the tumor, either to get a higher tumoricidal effect or to replace brachytherapy. Nevertheless, physiological organ movement and rapid tumor regression throughout treatment might substantially reduce any benefit of this approach. PURPOSE: To evaluate the clinical target volume - simultaneous integrated boost (CTV-SIB) regression and motion during chemo-radiotherapy (CRT) for cervical cancer, and to monitor treatment progress dosimetrically and volumetrically to ensure treatment goals are met. METHODS AND MATERIALS: Ten patients treated with standard doses of CRT and brachytherapy were retrospectively re-planned using a helical Tomotherapy - SIB technique for the hypothetical scenario of this feasibility study. Target and organs at risk (OAR) were contoured on deformable fused planning-computed tomography and megavoltage computed tomography images. The CTV-SIB volume regression was determined. The center of mass (CM) was used to evaluate the degree of motion. The Dice's similarity coefficient (DSC) was used to assess the spatial overlap of CTV-SIBs between scans. A cumulative dose-volume histogram modeled estimated delivered doses. RESULTS: The CTV-SIB relative reduction was between 31 and 70%. The mean maximum CM change was 12.5, 9, and 3 mm in the superior-inferior, antero-posterior, and right-left dimensions, respectively. The CTV-SIB-DSC approached 1 in the first week of treatment, indicating almost perfect overlap. CTV-SIB-DSC regressed linearly during therapy, and by the end of treatment was 0.5, indicating 50% discordance. Two patients received less than 95% of the prescribed dose. Much higher doses to the OAR were observed. A multiple regression analysis showed a significant interaction between CTV-SIB reduction and OAR dose increase. CONCLUSIONS: The CTV-SIB had important regression and motion during CRT, receiving lower therapeutic doses than expected. The OAR had unpredictable shifts and received higher doses. The use of SIB without frequent adaptation of the treatment plan exposes cervical cancer patients to an unpredictable risk of under-dosing the target and/or overdosing adjacent critical structures. In that scenario, brachytherapy continues to be the gold standard approach.

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

Hepatic hemangiomas: Factors associated with T2 shine-through effect on diffusion-weighted MR sequences.

PURPOSE: To determine the frequency and factors associated with the presence of T2 shine-through effect in hepatic hemangiomas on diffusion-weighted (DW) magnetic resonance (MR) sequences. MATERIALS AND METHODS: This retrospective study was approved by institutional review board with waiver of informed consent. One hundred forty-nine consecutive patients with 388 hepatic hemangiomas who underwent a liver MR between January 2010 and November 2011 were included. MR analysis evaluated the lesion characteristics (signal intensities and enhancement patterns (classical, rapidly filling, delayed filling)), the presence of T2 shine-through effect on DW sequences (b values of 0, 150, and 600s/mm(2)), and apparent diffusion coefficient (ADC) values. Multivariate analysis was performed to study the factors associated with the T2 shine-through effect. RESULTS: T2 shine-through effect was observed in 204/388 (52.6%) of hepatic hemangiomas and in 100 (67.1%) patients. Mean ADC value of hemangiomas with T2 shine-through effect was significantly lower than hemangiomas without (2.0±0.48 vs 2.38±0.45, P<.0001). On multivariate analysis, high signal intensity on fat-suppressed T2-weighted fast spin-echo images, hemangiomas with classical or delayed enhancement, and the ADC of the liver were the only significant factors associated with T2 shine-through effect. CONCLUSION: T2 shine-through effect is commonly observed in hepatic hemangiomas and is related to hemangiomas characteristics. Radiologists should be aware of this phenomenon which could lead to misdiagnosis. Its presence should not question the diagnosis of hemangiomas when typical MR findings are found.