Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors

BACKGROUND AND PURPOSE: Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. MATERIALS AND METHODS: This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. RESULTS: ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. CONCLUSIONS: Support vector machine–based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology

Molecular excitation in the Interstellar Medium: recent advances in collisional, radiative and chemical processes

We review the different excitation processes in the interstellar mediumComment: Accepted in Chem. Re

Global potential energy surface for the O2 + N2 interaction. Applications to the collisional, spectroscopic, and thermodynamic properties of the complex

A detailed characterization of the interaction between the most abundant molecules in air is important for the understanding of a variety of phenomena in atmospherical science. A completely {\em ab initio} global potential energy surface (PES) for the O$_2(^3\Sigma^-_g)$ + N$_2(^1\Sigma^+_g)$ interaction is reported for the first time. It has been obtained with the symmetry-adapted perturbation theory utilizing a density functional description of monomers [SAPT(DFT)] extended to treat the interaction involving high-spin open-shell complexes. The computed interaction energies of the complex are in a good agreement with those obtained by using the spin-restricted coupled cluster methodology with singles, doubles and noniterative triple excitations [RCCSD(T)]. A spherical harmonics expansion containing a large number of terms due to the anisotropy of the interaction has been built from the {\em ab initio} data. The radial coefficients of the expansion are matched in the long range with the analytical functions based on the recent {\em ab initio} calculations of the electric properties of the monomers [M. Bartolomei et al., J. Comp. Chem., {\bf 32}, 279 (2011)]. The PES is tested against the second virial coefficient $B(T)$ data and the integral cross sections measured with rotationally hot effusive beams, leading in both cases to a very good agreement. The first bound states of the complex have been computed and relevant spectroscopic features of the interacting complex are reported. A comparison with a previous experimentally derived PES is also provided

prohibited without the written consent of the copyright owner.

Wire sizing, repeater insertion and dominant time constant optimization for a bus lin

Augmented Lagrangian Algorithm for Optimizing Analog Circuit Design

Introduction The analog design assistance tool Adapt [5, 6] has been developed to help analog electronic circuit designers tuning design parameters, such that the functional design speci cations are met, given process technology constraints. Tuning is based on an optimization process, in which each iteration of the optimization loop implies the evaluation of the circuit by an analog circuit simulator. Considering the simulator as a black box tool, the choice of the optimization technique is restricted, because the simulator does not automatically supply derivatives of the design metrics and numerical noise is inherently present (for instance due to adaptive time stepping). This excludes optimization algorithms that adopt nite-dierence schemes to approximate derivatives. One of the two optimization algorithms available in Adapt is the Nelder{Mead (NM) method [7]. Adapt includes constraints by adding quadratic penalty terms to the cost function when using NM. The Nelder{Mead algori