Correlation of O6-methylguanine methyltransferase (MGMT) promoter methylation with clinical outcomes in glioblastoma and clinical strategies to modulate MGMT activity.

Resistance to alkylating agents via direct DNA repair by O(6)-methylguanine methyltransferase (MGMT) remains a significant barrier to the successful treatment of patients with malignant glioma. The relative expression of MGMT in the tumor may determine response to alkylating agents, and epigenetic silencing of the MGMT gene by promoter methylation plays an important role in regulating MGMT expression in gliomas. MGMT promoter methylation is correlated with improved progression-free and overall survival in patients treated with alkylating agents. Strategies to overcome MGMT-mediated chemoresistance are being actively investigated. These include treatment with nontoxic pseudosubstrate inhibitors of MGMT, such as O(6)-benzylguanine, or RNA interference-mediated gene silencing of MGMT. However, systemic application of MGMT inhibitors is limited by an increase in hematologic toxicity. Another strategy is to deplete MGMT activity in tumor tissue using a dose-dense temozolomide schedule. These alternative schedules are well tolerated; however, it remains unclear whether they are more effective than the standard dosing regimen or whether they effectively deplete MGMT activity in tumor tissue. Of note, not all patients with glioblastoma having MGMT promoter methylation respond to alkylating agents, and even those who respond will inevitably experience relapse. Herein we review the data supporting MGMT as a major mechanism of chemotherapy resistance in malignant gliomas and describe ongoing studies that are testing resistance-modulating strategies.

Comparison of organ doses and image quality between CT and flat panel XperCT scans in wrist and inner ear examinations.

The aim of this study was to evaluate and compare organ doses delivered to patients in wrist and petrous bone examinations using a multislice spiral computed tomography (CT) and a C-arm cone-beam CT equipped with a flat-panel detector (XperCT). For this purpose, doses to the target organ, i.e. wrist or petrous bone, together with those to the most radiosensitive nearby organs, i.e. thyroid and eye lens, were measured and compared. Furthermore, image quality was compared for both imaging systems and different acquisition modes using a Catphan phantom. Results show that both systems guarantee adequate accuracy for diagnostic purposes for wrist and petrous bone examinations. Compared with the CT scanner, the XperCT system slightly reduces the dose to target organs and shortens the overall duration of the wrist examination. In addition, using the XperCT enables a reduction of the dose to the eye lens during head scans (skull base and ear examinations).

Habitudes alimentaires et image corporelle chez des étudiants de deuxième année de gymnase à Lausanne [Food habits and body image of students in Lausanne]

During adolescence, nutrition needs are high; however the literature shows that few adolescents are following standardized nutritional requirements. A few weeks before an intervention about nutrition to high school adolescents in Lausanne, they were invited to fill in a self-reported questionnaire about their nutrition modes and habits, and their self-image satisfaction (N = 198). Results show that only 5% of youth are eating 5 fruits and vegetables per day and only 29% 3 to 5 dairy products. 21% of female and 6% of boys are not satisfied about their self-image, and those exhibiting a poor self-image tend to adopt health compromising eating patterns in a higher proportion. During adolescence it is important not only to investigate the nutritional habits but also one's self image.

Estimation of surface roughness in a semiarid region from C-band ERS-1 synthetic aperture radar data

In this study, we investigated the feasibility of using the C-band European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data to estimate surface soil roughness in a semiarid rangeland. Radar backscattering coefficients were extracted from a dry and a wet season SAR image and were compared with 47 in situ soil roughness measurements obtained in the rocky soils of the Walnut Gulch Experimental Watershed, southeastern Arizona, USA. Both the dry and the wet season SAR data showed exponential relationships with root mean square (RMS) height measurements. The dry C-band ERS-1 SAR data were strongly correlated (R² = 0.80), while the wet season SAR data have somewhat higher secondary variation (R² = 0.59). This lower correlation was probably provoked by the stronger influence of soil moisture, which may not be negligible in the wet season SAR data. We concluded that the single configuration C-band SAR data is useful to estimate surface roughness of rocky soils in a semiarid rangeland.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Schizophrenia connectivity: correlation between cognitive deficits and reduced thalamo-cortical fibers

Introduction: Schizophrenia is associated with multiple neuropsychological dysfunctions, such as disturbances of attention, memory, perceptual functioning, concept formation and executive processes. These cognitive functions are reported to depend on the integrity of the prefrontal and thalamo-prefrontal circuits. Multiple lines of evidence suggest that schizophrenia is related to abnormalities in neural circuitry and impaired structural connectivity. Here, we report a preliminary case-control study that showed a correlation between thalamo-frontal connections and several cognitive functions known to be impaired in schizophrenia. Materials and Methods: We investigated 9 schizophrenic patients (DSM IV criteria, Diagnostic Interview for Genetic Studies) and 9 age and sex matched control subjects. We obtained from each volunteer a DT-MRI dataset (3 T, _ _ 1,000 s/mm2), and a high resolution anatomic T1. The thalamo- frontal tracts are simulated with DTI tractography on these dataset, a method allowing inference of the main neural fiber tracks from Diffusion MRI data. In order to see an eventual correlation with the thalamo-frontal connections, every subject performs a battery of neuropsychological tests including computerized tests of attention (sustained attention, selective attention and reaction time), working memory tests (Plane test and the working memory sub-tests of the Wechsler Adult Intelligence Scale), a executive functioning task (Tower of Hanoï) and a test of visual binding abilities. Results: In a pilot case-control study (patients: n _ 9; controls: n _ 9), we showed that this methodology is appropriate and giving results in the excepted range. Considering the relation of the connectivity density and the neuropsychological data, a correlation between the number of thalamo- frontal fibers and the performance in the Tower of Hanoï was observed in the patients (Pearson correlation, r _ 0.76, p _ 0.05) but not in control subjects. In the most difficult item of the test, the least number of fibers corresponds to the worst performance of the test (fig. 2, number of supplementary movements of the elements necessary to realize the right configuration). It's interesting to note here that in an independent study, we showed that schizophrenia patients (n _ 32) perform in the most difficult item of the Tower of Hanoï (Mann-Whitney, p _ 0.005) significantly worse than control subjects (n _ 29). This has been observed in several others neuropsychological studies. Discussion: This pilot study of schizophrenia patients shows a correlation between the number of thalam-frontal fibers and the performance in the Tower of Hanoï, which is a planning and goal oriented actions task known to be associated with frontal dysfonction. This observation is consistent with the proposed impaired connectivity in schizophrenia. We aim to pursue the study with a larger sample in order to determine if other neuropsychological tests may be associated with the connectivity density.

Direct Fourier Tomographic Reconstruction Image-To-Image Filter

We present an open-source ITK implementation of a directFourier method for tomographic reconstruction, applicableto parallel-beam x-ray images. Direct Fourierreconstruction makes use of the central-slice theorem tobuild a polar 2D Fourier space from the 1D transformedprojections of the scanned object, that is resampled intoa Cartesian grid. Inverse 2D Fourier transform eventuallyyields the reconstructed image. Additionally, we providea complex wrapper to the BSplineInterpolateImageFunctionto overcome ITKâeuro?s current lack for image interpolatorsdealing with complex data types. A sample application ispresented and extensively illustrated on the Shepp-Loganhead phantom. We show that appropriate input zeropaddingand 2D-DFT oversampling rates together with radial cubicb-spline interpolation improve 2D-DFT interpolationquality and are efficient remedies to reducereconstruction artifacts.

A noninvasive method for measuring the velocity of diffuse hydrothermal flow by tracking moving refractive index anomalies

Diffuse flow velocimetry (DFV) is introduced as a new, noninvasive, optical technique for measuring the velocity of diffuse hydrothermal flow. The technique uses images of a motionless, random medium (e.g.,rocks) obtained through the lens of a moving refraction index anomaly (e.g., a hot upwelling). The method works in two stages. First, the changes in apparent background deformation are calculated using particle image velocimetry (PIV). The deformation vectors are determined by a cross correlation of pixel intensities across consecutive images. Second, the 2-D velocity field is calculated by cross correlating the deformation vectors between consecutive PIV calculations. The accuracy of the method is tested with laboratory and numerical experiments of a laminar, axisymmetric plume in fluids with both constant and temperaturedependent viscosity. Results show that average RMS errors are ∼5%–7% and are most accurate in regions of pervasive apparent background deformation which is commonly encountered in regions of diffuse hydrothermal flow. The method is applied to a 25 s video sequence of diffuse flow from a small fracture captured during the Bathyluck’09 cruise to the Lucky Strike hydrothermal field (September 2009). The velocities of the ∼10°C–15°C effluent reach ∼5.5 cm/s, in strong agreement with previous measurements of diffuse flow. DFV is found to be most accurate for approximately 2‐D flows where background objects have a small spatial scale, such as sand or gravel

Three-dimensional magnetic resonance myocardial motion tracking from a single image plane.

Three-dimensional imaging for the quantification of myocardial motion is a key step in the evaluation of cardiac disease. A tagged magnetic resonance imaging method that automatically tracks myocardial displacement in three dimensions is presented. Unlike other techniques, this method tracks both in-plane and through-plane motion from a single image plane without affecting the duration of image acquisition. A small z-encoding gradient is subsequently added to the refocusing lobe of the slice-selection gradient pulse in a slice following CSPAMM acquisition. An opposite polarity z-encoding gradient is added to the orthogonal tag direction. The additional z-gradients encode the instantaneous through plane position of the slice. The vertical and horizontal tags are used to resolve in-plane motion, while the added z-gradients is used to resolve through-plane motion. Postprocessing automatically decodes the acquired data and tracks the three-dimensional displacement of every material point within the image plane for each cine frame. Experiments include both a phantom and in vivo human validation. These studies demonstrate that the simultaneous extraction of both in-plane and through-plane displacements and pathlines from tagged images is achievable. This capability should open up new avenues for the automatic quantification of cardiac motion and strain for scientific and clinical purposes.

Bayesian image reconstruction with space-variant noise suppression

In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.