Quantitative combination of volumetric MR imaging and MR spectroscopy data for the discrimination of meningiomas from metastatic brain tumors by means of pattern recognition

The analysis of information derived from magnetic resonance imaging (MRI) and spectroscopy (MRS) has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to investigate the efficiency of the combination of textural MRI features and MRS metabolite ratios by means of a pattern recognition system in the task of discriminating between meningiomas and metastatic brain tumors. The data set consisted of 40 brain MR image series and their corresponding spectral data obtained from patients with verified tumors. The pattern recognition system was designed employing the support vector machines classifier with radial basis function kernel; the system was evaluated using an external cross validation process to render results indicative of the generalization performance to “unknown” cases. The combination of MR textural and spectroscopic features resulted in 92.15% overall accuracy in discriminating meningiomas from metastatic brain tumors. The fusion of the information derived from MRI and MRS data might be helpful in providing clinicians a useful second opinion tool for accurate characterization of brain tumors.     

Doping dependence of the pressure response of Tc in the SmO(1-x)F(x)FeAs superconductors

The superconducting transition temperature of the high-Tc SmO1-xFxFeAs superconductors increases monotonically as the F-doping level x increases to 0.20. High-pressure magnetization experiments reveal a strong sensitivity of Tc to interatomic distances in the underdoped regime (x 相似文献   

Pattern recognition system for the discrimination of multiple sclerosis from cerebral microangiopathy lesions based on texture analysis of magnetic resonance images

In this study, a pattern recognition system has been developed for the discrimination of multiple sclerosis (MS) from cerebral microangiopathy (CM) lesions based on computer-assisted texture analysis of magnetic resonance images. Twenty-three textural features were calculated from MS and CM regions of interest, delineated by experienced radiologists on fluid attenuated inversion recovery images and obtained from 11 patients diagnosed with clinically definite MS and from 18 patients diagnosed with clinically definite CM. The probabilistic neural network classifier was used to construct the proposed pattern recognition system and the generalization of the system to unseen data was evaluated using an external cross validation process. According to the findings of the present study, statistically significant differences exist in the values of the textural features between CM and MS: MS regions were darker, of higher contrast, less homogeneous and rougher as compared to CM.     

Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods

Three-dimensional (3D) texture analysis of volumetric brain magnetic resonance (MR) images has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to evaluate the efficiency of 3D textural features using a pattern recognition system in the task of discriminating benign, malignant and metastatic brain tissues on T1 postcontrast MR imaging (MRI) series. The dataset consisted of 67 brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed as an ensemble classification scheme employing a support vector machine classifier, specially modified in order to integrate the least squares features transformation logic in its kernel function. The latter, in conjunction with using 3D textural features, enabled boosting up the performance of the system in discriminating metastatic, malignant and benign brain tumors with 77.14%, 89.19% and 93.33% accuracy, respectively. The method was evaluated using an external cross-validation process; thus, results might be considered indicative of the generalization performance of the system to "unseen" cases. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.     

Pressure-induced sequential magnetic pole inversion and antiferromagnetic-ferromagnetic crossover in a trimetallic prussian blue analogue

The flexibility of the structure of Prussian blue analogues and its ability to incorporate a variety of competing magnetic interactions have allowed the design of mixed ferro-ferrimagnets, which span the whole spectrum of magnetic behavior, including the rare phenomenon of magnetization reversal in response to a change in temperature. Hydrostatic pressure is used here to induce multiple reversals of the direction of the spontaneous magnetization in the trimetallic Prussian blue analogue, Rb0.64Ni0.31Mn0.87[Fe(CN)6].2.8H2O. Remarkably, the magnetic response is extremely sensitive to pressure, and the magnetization flips from positive to negative and back to positive in a very narrow pressure range (0 < P < 0.6 kbar). A further increase in pressure to 4.0 kbar induces an internal redox reaction, and the magnetic order switches from ferrimagnetic to bulk ferromagnetism.     

X-ray illumination induced Fe(II) spin crossover in the Prussian blue analogue cesium iron hexacyanochromate

The effect of X-ray illumination on the structural properties of the mixed valence Prussian blue analogue CsFe(II)[Cr(III)(CN)6] has been studied by time-dependent high-resolution synchrotron X-ray diffraction. Abrupt isosymmetric phase transitions, accompanied by dramatic volume collapse, were found in the temperature range 245-265 K, induced by sudden Fe(II) spin transitions from the high spin (HS) (4t(2g)2e(g), S = 2) to the low spin (LS) (6t(2g)0e(g), S = 0) configuration. Absorption of X-ray photons generates photoexcited Fe(II)(LS) domains whose size rapidly grows with time until the percolation threshold is reached and the structure collapse is triggered. The persistent character of the optically excited spin crossover states derives from the strong electron-phonon coupling, associated with the large lattice relaxations, which accompany the internal spin rearrangements. It is thus possible to use X-ray light in a controllable and efficient way to induce photoswitching between the ground and hidden or inaccessible excited states in suitably selected multistable materials in the bulk.     

Influence of the organic compounds on the ecotoxicity in the treatment of foundry sludge and olive mill waste

The study of the ecotoxicity in two industrial waste materials and the relationships with the organic parameters has been conducted. Foundry sludge and olive mill waste have been used as industrial waste materials with organic or mixed character. Stabilisation/solidification (S/S) and advanced oxidation (AOP) processes have been carried out in order to treat both foundry sludge and olive mill waste. Analysis of ecotoxicity, total organic carbon, COD and phenol index have been evaluated in the untreated waste and end-products. The results of the treated samples allow obtaining the best formulations in both processes. The best formulations in the immobilisation process have been obtained with Portland cement and black carbon, activated carbon or foundry sand ashes. In the AOP process, ozone concentrations above 35 mg/l and reaction times equal to 120 minutes have been the optimal variables. The relationships between the organic parameters and the ecotoxicity of the samples have been studied in this paper. Furthermore, the global organic parameters have been studied in relation to the phenolic compounds. Lineal and logarithmic expressions have been obtained between the total organic carbon and phenol index and the ecotoxicity of the samples related to the organic parameters, respectively. Ecotoxicity of the samples with Vibrio fischeri is recommended as a very promising biotest for the study of the characterisation and the evaluation of the treatment of organic and mixed character waste and total organic carbon is recommended as global organic parameter in the treatment of foundry sludge.     

Pattern-recognition system,designed on GPU,for discriminating between injured normal and pathological knee cartilage

The aim was to design a pattern-recognition (PR) system for discriminating between normal and pathological knee articular cartilage of the medial femoral (MFC) and tibial condyles (MTC). The data set comprised segmented regions of interest (ROIs) from coronal and sagittal 3-T magnetic resonance images of the MFC and MTC cartilage of young patients, 28 with abnormality-free knee and 16 with pathological findings. The PR system was designed employing the probabilistic neural network classifier, textural features from the segmented ROIs and the leave-one-out evaluation method, while the PR system's precision to “unseen” data was assessed by employing the external cross-validation method. Optimal system design was accomplished on a consumer graphics processing unit (GPU) using Compute Unified Device Architecture parallel programming. PR system design on the GPU required about 3.5 min against 15 h on a CPU-based system. Highest classification accuracies for the MFC and MTC cartilages were 93.2% and 95.5%, and accuracies to “unseen” data were 89% and 86%, respectively. The proposed PR system is housed in a PC, equipped with a consumer GPU, and it may be easily retrained when new verified data are incorporated in its repository and may be of value as a second-opinion tool in a clinical environment.     

Efficient Population Transfer in a Λ-Type Quantum System Coupled to a Gold Nanoparticle Using STIRAP Shortcuts

A theoretical investigation on the population transfer in a Λ-type quantum system near a spherical gold nanoparticle under application of two stimulated Raman adiabatic passage (STIRAP) shortcuts and efficiency comparison with conventional STIRAP. It combines the density matrix approach for system dynamics, with classical electromagnetic calculations used to obtain the modified electric field amplitudes of the applied pulses and the Purcell factor of the quantum system due to the presence of the nanoparticle. The efficiency of population transfer is investigated by varying the distance between the quantum system and the nanoparticle, the free-space decay rate of quantum states, the mutual polarization, and the Rabi frequencies of each STIRAP shortcut pulses. In all cases, at least one of the applied shortcuts is more efficient than conventional STIRAP, while in most cases both perform better. When the pump and Stokes fields of the shortcuts have radial and tangential polarizations with respect to the nanoparticle surface, respectively, high transfer efficiency is obtained for small distances of the quantum system to the nanoparticle, moderate free space decay rates and large Rabi frequencies of the fields, while when the pulse polarizations are interchanged, the transfer becomes highly efficient only at large distances.     

Radiometric dating of sediment cores from aquatic environments of north-east Mediterranean

Journal of Radioanalytical and Nuclear Chemistry - Chronological records and sedimentation rates of coastal sediment cores from different aquatic environments of NE Mediterranean are reported....