Monte Carlo Dose Calculation on Deforming Anatomy

This article presents the implementation and validation of a dose calculation approach for deforming anatomical objects. Deformation is represented by deformation vector fields leading to deformed voxel grids representing the different deformation scenarios. Particle transport in the resulting deformed voxels is handled through the approximation of voxel surfaces by triangles in the geometry implementation of the Swiss Monte Carlo Plan framework. The focus lies on the validation methodology which uses computational phantoms representing the same physical object through regular and irregular voxel grids. These phantoms are chosen such that the new implementation for a deformed voxel grid can be compared directly with an established dose calculation algorithm for regular grids. Furthermore, separate validation of the aspects voxel geometry and the density changes resulting from deformation is achieved through suitable design of the validation phantom. We show that equivalent results are obtained with the proposed method and that no statistically significant errors are introduced through the implementation for irregular voxel geometries. This enables the use of the presented and validated implementation for further investigations of dose calculation on deforming anatomy.

3D-based reconstruction using growing neural gas landmark: application to rapid prototyping in shoe last manufacturing

Customizing shoe manufacturing is one of the great challenges in the footwear industry. It is a production model change where design adopts not only the main role, but also the main bottleneck. It is therefore necessary to accelerate this process by improving the accuracy of current methods. Rapid prototyping techniques are based on the reuse of manufactured footwear lasts so that they can be modified with CAD systems leading rapidly to new shoe models. In this work, we present a shoe last fast reconstruction method that fits current design and manufacturing processes. The method is based on the scanning of shoe last obtaining sections and establishing a fixed number of landmarks onto those sections to reconstruct the shoe last 3D surface. Automated landmark extraction is accomplished through the use of the self-organizing network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates up to 12 times the surface reconstruction and filtering processes used by the current shoe last design software. The proposed method offers higher accuracy compared with methods with similar efficiency as voxel grid.

3D reconstruction of medical images from slices automatically landmarked with growing neural models

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid.

3D model reconstruction using neural gas accelerated on GPU

In this work, we propose the use of the neural gas (NG), a neural network that uses an unsupervised Competitive Hebbian Learning (CHL) rule, to develop a reverse engineering process. This is a simple and accurate method to reconstruct objects from point clouds obtained from multiple overlapping views using low-cost sensors. In contrast to other methods that may need several stages that include downsampling, noise filtering and many other tasks, the NG automatically obtains the 3D model of the scanned objects. To demonstrate the validity of our proposal we tested our method with several models and performed a study of the neural network parameterization computing the quality of representation and also comparing results with other neural methods like growing neural gas and Kohonen maps or classical methods like Voxel Grid. We also reconstructed models acquired by low cost sensors that can be used in virtual and augmented reality environments for redesign or manipulation purposes. Since the NG algorithm has a strong computational cost we propose its acceleration. We have redesigned and implemented the NG learning algorithm to fit it onto Graphics Processing Units using CUDA. A speed-up of 180× faster is obtained compared to the sequential CPU version.

Acoustic multi-frequency indicator of four major groups on a spatial grid in the Bay of Biscay

The first data set contains the mean and cofficient of variation (standard deviation divided by mean) of a multi-frequency indicator I derived from ER60 acoustic information collected at five frequencies (18, 38, 70, 120, and 200 kHz) in the Bay of Biscay in May of the years 2006, 2008, 2009 and 2010 (Pelgas surveys). The multi-frequency indicator was first calculated per voxel (20 m long × 5 m deep sampling unit) and then averaged on a spatial grid (approx. 20 nm × 20 nm) for five 5-m depth layers in the surface waters (10-15m, 15-20m, 20-25m, 25-30m below sea surface); there are missing values in particular in the shallowest layer. The second data set provides for each grid cell and depth layer the proportion of voxels for which the multi-frequency indicator I was indicative of a certain group of organisms. For this the following interpretation was used: I < 0.39 swim bladder fish or large gas bubbles, I = 0.39-0.58 small resonant bubbles present in gas bearing organisms such as larval fish and phytoplankton, I = 0.7-0.8 fluidlike zooplankton such as copepods and euphausiids, and I > 0.8 mackerel. These proportions can be interpreted as a relative abundance index for each of the four organism groups.

A Study on the Relationship of Embedded Sensitivity With Measuring Grid and Mode Shapes

Embedded sensitivity analysis has proven to be a useful tool in finding optimum positions of structure reinforcements. However, it was not clear how sensitivities obtained from the embedded sensitivity method were related to the normal mode, or operational mode, associated to the frequency of interest. In this work, this relationship is studied based on a finite element of a slender sheet metal piece, with preponderant bending modes. It is shown that higher sensitivities always occur at nodes or antinodes of the vibrating system. [DOI: 10.1115/1.4002127]

Applying semantics to grid middleware

Scheduling parallel and distributed applications efficiently onto grid environments is a difficult task and a great variety of scheduling heuristics has been developed aiming to address this issue. A successful grid resource allocation depends, among other things, on the quality of the available information about software artifacts and grid resources. In this article, we propose a semantic approach to integrate selection of equivalent resources and selection of equivalent software artifacts to improve the scheduling of resources suitable for a given set of application execution requirements. We also describe a prototype implementation of our approach based on the Integrade grid middleware and experimental results that illustrate its benefits. Copyright (C) 2009 John Wiley & Sons, Ltd.

Coarse-grid higher order finite-difference time-domain algorithm with low dispersion errors

Higher order (2,4) FDTD schemes used for numerical solutions of Maxwell`s equations are focused on diminishing the truncation errors caused by the Taylor series expansion of the spatial derivatives. These schemes use a larger computational stencil, which generally makes use of the two constant coefficients, C-1 and C-2, for the four-point central-difference operators. In this paper we propose a novel way to diminish these truncation errors, in order to obtain more accurate numerical solutions of Maxwell`s equations. For such purpose, we present a method to individually optimize the pair of coefficients, C-1 and C-2, based on any desired grid size resolution and size of time step. Particularly, we are interested in using coarser grid discretizations to be able to simulate electrically large domains. The results of our optimization algorithm show a significant reduction in dispersion error and numerical anisotropy for all modeled grid size resolutions. Numerical simulations of free-space propagation verifies the very promising theoretical results. The model is also shown to perform well in more complex, realistic scenarios.

Embedded Voxel Colouring

The reconstruction of a complex scene from multiple images is a fundamental problem in the field of computer vision. Volumetric methods have proven to be a strong alternative to traditional correspondence-based methods due to their flexible visibility models. In this paper we analyse existing methods for volumetric reconstruction and identify three key properties of voxel colouring algorithms: a water-tight surface model, a monotonic carving order, and causality. We present a new Voxel Colouring algorithm which embeds all reconstructions of a scene into a single output. While modelling exact visibility for arbitrary camera locations, Embedded Voxel Colouring removes the need for a priori threshold selection present in previous work. An efficient implementation is given along with results demonstrating the advantages of posteriori threshold selection.

Depression in Parkinson`s disease: Convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus

Depression is the most frequent psychiatric disorder in Parkinson`s disease (PD). Although evidence Suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontall cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation. (C) 2009 Elsevier Inc. All rights reserved.

Regional gray matter abnormalities in panic disorder: A voxel-based morphometry study

Although abnonnalities in brain structures involved in the neurobiology of fear and anxiety have been implicated in the pathophysiology of panic disorder (PD), relatively few studies have made use of voxel-based morphometry (VBM) magnetic resonance imaging (MRI) to determine structural brain abnormalities in PD. We have assessed gray matter volume in 19 PD patients and 20 healthy volunteers using VBM. Images were acquired using a 1.5 T MRI scanner, and were spatially normalized and segmented using optimized VBM. Statistical comparisons were performed using the general linear model. A relative increase in gay matter volume was found in the left insula of PD patients compared with controls. Additional structures showing differential increases were the left superior temporal gyrus, the midbrain, and the pons. A relative gray matter deficit was found in the right anterior cingulate cortex. The insula and anterior cingulate abnormalities may be relevant to the pathophysiology of PD, since these structures participate in the evaluation process that ascribes negative emotional meaning to potentially distressing cognitive and interoceptive sensory information. The abnormal brain stem structures may be involved in the generation of panic attacks. (C) 2007 Elsevier Ireland Ltd. All rights reserved.

Age-Related Metabolic Profiles in Cognitively Healthy Elders: Results from a Voxel-Based [(18)F]Fluorodeoxyglucose-Positron-Emission Tomography Study with Partial Volume Effects Correction

BACKGROUND AND PURPOSE: Functional brain variability has been scarcely investigated in cognitively healthy elderly subjects, and it is currently debated whether previous findings of regional metabolic variability are artifacts associated with brain atrophy. The primary purpose of this study was to test whether there is regional cerebral age-related hypometabolism specifically in later stages of life. MATERIALS AND METHODS: MR imaging and FDG-PET data were acquired from 55 cognitively healthy elderly subjects, and voxel-based linear correlations between age and GM volume or regional cerebral metabolism were conducted by using SPM5 in images with and without correction for PVE. To investigate sex-specific differences in the pattern of brain aging, we repeated the above voxelwise calculations after dividing our sample by sex. RESULTS: Our analysis revealed 2 large clusters of age-related metabolic decrease in the overall sample, 1 in the left orbitofrontal cortex and the other in the right temporolimbic region, encompassing the hippocampus, the parahippocampal gyrus, and the amygdala. The division of our sample by sex revealed significant sex-specific age-related metabolic decrease in the left temporolimbic region of men and in the left dorsolateral frontal cortex of women. When we applied atrophy correction to our PET data, none of the above-mentioned correlations remained significant. CONCLUSIONS: Our findings suggest that age-related functional brain variability in cognitively healthy elderly individuals is largely secondary to the degree of regional brain atrophy, and the findings provide support to the notion that appropriate PVE correction is a key tool in neuroimaging investigations.

Reduced medial prefrontal N-Acetyl-Aspartate levels in pediatric major depressive disorder: A multi-voxel in vivo (1)H spectroscopy study

There is increasing evidence of a reciprocal fronto-limbic network in the pathogenesis of mood disorders. Prior in vivo proton ((1)H) spectroscopy studies provide evidence of abnormal neurochemical levels in the cingulate and dorsolateral prefrontal cortex (DLPFC) of adult subjects with major depressive disorder (MOD). We examined whether similar abnormalities occur in children and adolescents with MDD. We collected two-dimensional multi-voxel in vivo 1H spectroscopy data at 1.5 Tesla to quantify levels of N-acetyl-aspartate (NAA), glycerolphosphocholine plus phosphocholine (GPC + PC), and phosphocreatine plus creatine (PCr + Cr) in the DLPFC, medial prefrontal cortex (MPFC), and anterior cingulate (AC) of children and adolescents aged 8-17 years with MDD (n = 16) compared with healthy control subjects (n = 38). Analysis of covariance with age and gender as covariates was performed. MDD subjects showed significantly lower levels of NAA in the right MPFC and right AC than controls. MDD subjects also had significantly lower levels of GPC + PC in the right AC than control subjects. There were no significant differences in other metabolites in the studied regions. Pediatric patients with MDD exhibit neurochemical alterations in prefrontal cortex regions that are important in the monitoring and regulation of emotional states. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Normal metabolite levels in the left dorsolateral prefrontal cortex of unmedicated major depressive disorder patients: A single voxel (1)H spectroscopy study

Few proton magnetic resonance spectroscopy ((1)H spectroscopy) studies have investigated the dorsolateral prefrontal cortex (DLPFC), a key region in the pathophysiology of major depressive disorder (MDD). We used (1)H spectroscopy to verify whether MDD patients differ from healthy controls (HQ in metabolite levels in this brain area. Thirty-seven unmedicated DSM-IV MDD patients were compared with 40 HC. Subjects underwent a short echo-time (1)H spectroscopy examination at 1.5 T, with an 8-cm(3) single voxel placed in the left DLPFC. Reliable absolute metabolite levels of N-acetyl aspartate (NAA), phosphocreatine plus creatine (PCr+Cr), choline-containing compounds (GPC+PC), myo-inositol, glutamate plus glutamine (Glu+Gln), and glutamate were obtained using the unsuppressed water signal as an internal reference. Metabolite levels in the left DLPFC did not statistically differ between MDD patients and HC. We found an interaction between gender and diagnosis on PCr+Cr levels. Male MDD patients presented lower levels of PCr+Cr than male HC, and female MDD patients presented higher levels of PCr+Cr than female HC. Moreover, length of illness was inversely correlated with NAA levels. These findings suggest that there is not an effect of diagnosis on the left DLPFC neurochemistry. Possible effects of gender on PCr+Cr levels of MDD patients need to be further investigated. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

A Voxel-Based Morphometry Study of Frontal Gray Matter Correlates of Impulsivity

Impulsivity is a personality trait exhibited by healthy individuals, but excessive impulsivity is associated with some mental disorders. Lesion and functional, neuroimaging Studies indicate that the ventromedial prefrontal region (VMPFC), including the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC) and medial prefrontal cortex, and the amygdala may modulate impulsivity and aggression. However, no morphometric study has examined the association between VMPFC and impulsivity. We hypothesized that healthy subjects with high impulsivity would have smaller volumes in these brain regions compared with those with low impulsivity. Sixty-two healthy Subjects were Studied (age 35.4 +/- 12.1 years) using a 1.5-T MRI system. The Barratt impulsiveness scale (BIS) was used to assess impulsivity. Images were processed using an optimized voxel-based morphometry (VBM) protocol. We calculated the correlations between BIS scale scores and the gray matter (GM) and white matter (WM) volumes of VMPFC and amygdala. GM volumes of the left and right OFC were inversely correlated with the BIS total score (P = 0.04 and 0.02, respectively). Left ACC GM Volumes had a tendency to be inversely correlated with the BIS total score (P = 0.05. Right OFC GM Volumes were inversely correlated with BIS nonplanning impulsivity, and left OFC GM volumes were inversely correlated with motor impulsivity. There were no significant WM volume correlations with impulsivity. The results Of this morphometry Study indicate that small OFC volume relate to high impulsivity and extend the prior finding that the VMPFC is involved in the circuit modulating impulsivity. HUM Brain Mapp 30:1188-1195, 2009. (C) 2008 Wiley-Liss, Inc.