A multidimensional segmentation evaluation for medical image data.

Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.

Neurochemical profile of the mouse hypothalamus using in vivo 1H MRS at 14.1T.

The hypothalamus plays an essential role in the central nervous system of mammals by among others regulating glucose homeostasis, food intake, temperature, and to some extent blood pressure. Assessments of hypothalamic metabolism using, e.g. (1)H MRS in mouse models can provide important insights into its function. To date, direct in vivo (1)H MRS measurements of hypothalamus have not been reported. Here, we report that in vivo single voxel measurements of mouse hypothalamus are feasible using (1)H MRS at 14.1T. Localized (1)H MR spectra from hypothalamus were obtained unilaterally (2-2.2 microL, VOI) and bilaterally (4-4.4 microL) with a quality comparable to that of hippocampus (3-3.5 microL). Using LCModel, a neurochemical profile consisting of 21 metabolites was quantified for both hypothalamus and hippocampus with most of the Cramér-Rao lower bounds within 20%. Relative to the hippocampus, the hypothalamus was characterized by high gamma-aminobutryric acid and myo-inositol, and low taurine concentrations. When studying transgenic mice with no glucose transporter isoform 8 expressed, small metabolic changes were observed, yet glucose homeostasis was well maintained. We conclude that a specific neurochemical profile of mouse hypothalamus can be measured by (1)H MRS which will allow identifying and following metabolic alterations longitudinally in the hypothalamus of genetic modified models.

Compositional Data in Biomedical Research

Modern methods of compositional data analysis are not well known in biomedical research.Moreover, there appear to be few mathematical and statistical researchersworking on compositional biomedical problems. Like the earth and environmental sciences,biomedicine has many problems in which the relevant scienti c information isencoded in the relative abundance of key species or categories. I introduce three problemsin cancer research in which analysis of compositions plays an important role. Theproblems involve 1) the classi cation of serum proteomic pro les for early detection oflung cancer, 2) inference of the relative amounts of di erent tissue types in a diagnostictumor biopsy, and 3) the subcellular localization of the BRCA1 protein, and it'srole in breast cancer patient prognosis. For each of these problems I outline a partialsolution. However, none of these problems is \solved". I attempt to identify areas inwhich additional statistical development is needed with the hope of encouraging morecompositional data analysts to become involved in biomedical research

An in vivo ultrahigh field 14.1 T (1) H-MRS study on 6-OHDA and α-synuclein-based rat models of Parkinson's disease: GABA as an early disease marker.

The detection of Parkinson's disease (PD) in its preclinical stages prior to outright neurodegeneration is essential to the development of neuroprotective therapies and could reduce the number of misdiagnosed patients. However, early diagnosis is currently hampered by lack of reliable biomarkers. (1) H magnetic resonance spectroscopy (MRS) offers a noninvasive measure of brain metabolite levels that allows the identification of such potential biomarkers. This study aimed at using MRS on an ultrahigh field 14.1 T magnet to explore the striatal metabolic changes occurring in two different rat models of the disease. Rats lesioned by the injection of 6-hydroxydopamine (6-OHDA) in the medial-forebrain bundle were used to model a complete nigrostriatal lesion while a genetic model based on the nigral injection of an adeno-associated viral (AAV) vector coding for the human α-synuclein was used to model a progressive neurodegeneration and dopaminergic neuron dysfunction, thereby replicating conditions closer to early pathological stages of PD. MRS measurements in the striatum of the 6-OHDA rats revealed significant decreases in glutamate and N-acetyl-aspartate levels and a significant increase in GABA level in the ipsilateral hemisphere compared with the contralateral one, while the αSyn overexpressing rats showed a significant increase in the GABA striatal level only. Therefore, we conclude that MRS measurements of striatal GABA levels could allow for the detection of early nigrostriatal defects prior to outright neurodegeneration and, as such, offers great potential as a sensitive biomarker of presymptomatic PD.

Identidade e Pertença: para além das Dimensões Materiais do Sofrimento Social

Um olhar antropológico sobre as relações sociais em dois microcosmos etnográficos – um bairro e um centro de saúde – revela as limitações de encarar a pobreza material como o único critério para compreender os processos de sofrimento social. De forma a explorar como o sofrimento social pode ser vivenciado através das identificações e das pertenças, a identidade étnica e a identidade profissional são examinadas como exemplos da identidade social em geral. A relação dialética entre a identidade social e a identidade pessoal demonstra como o poder não está depositado nas pessoas, mas depende das suas relações sociais. Dado que o exercício de poder não pode ser garantido pelo simples estatuto de uma determinada categoria social, urge procurar vivências e subjetividades nas fissuras das categorias, distinguindo entre uma categoria de prática e uma categoria de análise, de forma a alargar o horizonte sobre a natureza dos processos de sofrimento social.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Single-trial topographic analysis of human EEG: A new image of event-related potentials

We present a novel approach for analyzing single-trial electroencephalography (EEG) data, using topographic information. The method allows for visualizing event-related potentials using all the electrodes of recordings overcoming the problem of previous approaches that required electrode selection and waveforms filtering. We apply this method to EEG data from an auditory object recognition experiment that we have previously analyzed at an ERP level. Temporally structured periods were statistically identified wherein a given topography predominated without any prior information about the temporal behavior. In addition to providing novel methods for EEG analysis, the data indicate that ERPs are reliably observable at a single-trial level when examined topographically.

Quantification of brain glycogen concentration and turnover through localized 13C NMR of both the C1 and C6 resonances.

We have recently shown that at isotopic steady state (13)C NMR can provide a direct measurement of glycogen concentration changes, but that the turnover of glycogen was not accessible with this protocol. The aim of the present study was to design, implement and apply a novel dual-tracer infusion protocol to simultaneously measure glycogen concentration and turnover. After reaching isotopic steady state for glycogen C1 using [1-(13)C] glucose administration, [1,6-(13)C(2)] glucose was infused such that isotopic steady state was maintained at the C1 position, but the C6 position reflected (13)C label incorporation. To overcome the large chemical shift displacement error between the C1 and C6 resonances of glycogen, we implemented 2D gradient based localization using the Fourier series window approach, in conjunction with time-domain analysis of the resulting FIDs using jMRUI. The glycogen concentration of 5.1 +/- 1.6 mM measured from the C1 position was in excellent agreement with concomitant biochemical determinations. Glycogen turnover measured from the rate of label incorporation into the C6 position of glycogen in the alpha-chloralose anesthetized rat was 0.7 micromol/g/h.

A program for the computation of power and determination of sample size in hierarchical experimental designs.

We have devised a program that allows computation of the power of F-test, and hence determination of appropriate sample and subsample sizes, in the context of the one-way hierarchical analysis of variance with fixed effects. The power at a fixed alternative is an increasing function of the sample size and of the subsample size. The program makes it easy to obtain the power of F-test for a range of values of sample and subsample sizes, and therefore the appropriate sizes based on a desired power. The program can be used for the 'ordinary' case of the one-way analysis of variance, as well as for hierarchical analysis of variance with two stages of sampling. Examples are given of the practical use of the program.

Unedited in vivo detection and quantification of γ-aminobutyric acid in the occipital cortex using short-TE MRS at 3 T.

Short-TE MRS has been proposed recently as a method for the in vivo detection and quantification of γ-aminobutyric acid (GABA) in the human brain at 3 T. In this study, we investigated the accuracy and reproducibility of short-TE MRS measurements of GABA at 3 T using both simulations and experiments. LCModel analysis was performed on a large number of simulated spectra with known metabolite input concentrations. Simulated spectra were generated using a range of spectral linewidths and signal-to-noise ratios to investigate the effect of varying experimental conditions, and analyses were performed using two different baseline models to investigate the effect of an inaccurate baseline model on GABA quantification. The results of these analyses indicated that, under experimental conditions corresponding to those typically observed in the occipital cortex, GABA concentration estimates are reproducible (mean reproducibility error, <20%), even when an incorrect baseline model is used. However, simulations indicate that the accuracy of GABA concentration estimates depends strongly on the experimental conditions (linewidth and signal-to-noise ratio). In addition to simulations, in vivo GABA measurements were performed using both spectral editing and short-TE MRS in the occipital cortex of 14 healthy volunteers. Short-TE MRS measurements of GABA exhibited a significant positive correlation with edited GABA measurements (R = 0.58, p < 0.05), suggesting that short-TE measurements of GABA correspond well with measurements made using spectral editing techniques. Finally, within-session reproducibility was assessed in the same 14 subjects using four consecutive short-TE GABA measurements in the occipital cortex. Across all subjects, the average coefficient of variation of these four GABA measurements was 8.7 ± 4.9%. This study demonstrates that, under some experimental conditions, short-TE MRS can be employed for the reproducible detection of GABA at 3 T, but that the technique should be used with caution, as the results are dependent on the experimental conditions. Copyright © 2013 John Wiley & Sons, Ltd.

MRI monitoring of focal cerebral ischemia in peroxisome proliferator-activated receptor (PPAR)-deficient mice.

Peroxisome proliferator-activated receptors (PPARs) are a potential target for neuroprotection in focal ischemic stroke. These nuclear receptors have major effects in lipid metabolism, but they are also involved in inflammatory processes. Three PPAR isotypes have been identified: alpha, beta (or delta) and gamma. The development of PPAR transgenic mice offers a promising tool for prospective therapeutic studies. This study used MRI to assess the role of PPARalpha and PPARbeta in the development of stroke. Permanent middle cerebral artery occlusion induced focal ischemia in wild-type, PPARalpha-null mice and PPARbeta-null mice. T(2)-weighted MRI was performed with a 7 T MRI scan on day 0, 1, 3, 7 and 14 to monitor lesion growth in the various genotypes. General Linear Model statistical analysis found a significant difference in lesion volume between wild-type and PPAR-null mice for both alpha and beta isotypes. These data validate high-resolution MRI for monitoring cerebral ischemic lesions, and confirm the neuroprotective role of PPARalpha and PPARbeta in the brain.

Increased brain perfusion contrast with T2 -prepared intravoxel incoherent motion (T2prep IVIM) MRI.

The feasibility to measure brain perfusion using intravoxel incoherent motion (IVIM) MRI has been reported recently with currently clinically available technology. The method is intrinsically local and quantitative, but is contaminated by partial volume effects with cerebrospinal fluid (CSF). Signal from CSF can be suppressed by a 180° inversion recovery (180°-IR) magnetization preparation, but this also leads to strong suppression of blood and brain tissue signal. Here, we take advantage of the different T2 relaxations of blood and brain relative to CSF, and implement a T2 -prepared IVIM (T2prep IVIM) inversion recovery acquisition, which permits a recovery of between 43% and 57% of arterial and venous blood magnetization at excitation time compared with the theoretical recovery of between 27% and 30% with a standard 180°-IR. We acquired standard IVIM (IVIM), T2prep IVIM and dynamic susceptibility contrast (DSC) images at 3 T using a 32-multichannel receiver head coil in eight patients with known large high-grade brain tumors. We compared the contrast and contrast-to-noise ratio obtained in the corresponding cerebral blood volume images quantitatively, as well as subjectively by two neuroradiologists. Our findings suggest that quantitative cerebral blood volume contrast and contrast-to-noise ratio, as well as subjective lesion detection, contrast quality and diagnostic confidence, are increased with T2prep IVIM relative to IVIM and DSC.

MBIS: multivariate Bayesian image segmentation tool.

We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.

Optimized MEGA-SPECIAL for in vivo glutamine detection in the rat brain at 14.1 T.

Glutamine has multiple roles in brain metabolism and its concentration can be altered in various pathological conditions. An accurate knowledge of its concentration is therefore highly desirable to monitor and study several brain disorders in vivo. However, in recent years, several MRS studies have reported conflicting glutamine concentrations in the human brain. A recent hypothesis for explaining these discrepancies is that a short T2 component of the glutamine signal may impact on its quantification at long echo times. The present study therefore aimed to investigate the impact of acquisition parameters on the quantified glutamine concentration using two different acquisition techniques, SPECIAL at ultra-short echo time and MEGA-SPECIAL at moderate echo time. For this purpose, MEGA-SPECIAL was optimized for the first time for glutamine detection. Based on the very good agreement of the glutamine concentration obtained between the two measurements, it was concluded that no impact of a short T2 component of the glutamine signal was detected.

Advanced light microscopy techniques

This article summarizes the basic principles of light microscopy, with examples of applications in biomedicine that illustrate the capabilities of thetechnique.