Imagem de tensor de difusão na epilesia de lobo temporal mesial

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Performance analysis of reconstruction algorithms for breast microwave imaging

The problem of localizing a scatterer, which represents a tumor, in a homogeneous circular domain, which represents a breast, is addressed. A breast imaging method based on microwaves is considered. The microwave imaging involves to several techniques for detecting, localizing and characterizing tumors in breast tissues. In all such methods an electromagnetic inverse scattering problem exists. For the scattering detection method, an algorithm based on a linear procedure solution, inspired by MUltiple SIgnal Classification algorithm (MUSIC) and Time Reversal method (TR), is implemented. The algorithm returns a reconstructed image of the investigation domain in which it is detected the scatterer position. This image is called pseudospectrum. A preliminary performance analysis of the algorithm vying the working frequency is performed: the resolution and the signal-to-noise ratio of the pseudospectra are improved if a multi-frequency approach is considered. The Geometrical Mean-MUSIC algorithm (GM- MUSIC) is proposed as multi-frequency method. The performance of the GMMUSIC is tested in different real life computer simulations. The performed analysis shows that the algorithm detects the scatterer until the electrical parameters of the breast are known. This is an evident limit, since, in a real life situation, the anatomy of the breast is unknown. An improvement in GM-MUSIC is proposed: the Eye-GMMUSIC algorithm. Eye-GMMUSIC algorithm needs no a priori information on the electrical parameters of the breast. It is an optimizing algorithm based on the pattern search algorithm: it searches the breast parameters which minimize the Signal-to-Clutter Mean Ratio (SCMR) in the signal. Finally, the GM-MUSIC and the Eye-GMMUSIC algorithms are tested on a microwave breast cancer detection system consisting of an dipole antenna, a Vector Network Analyzer and a novel breast phantom built at University of Bologna. The reconstruction of the experimental data confirm the GM-MUSIC ability to localize a scatterer in a homogeneous medium.

MRI detects hemorrhages in the muscles of the back in hypothermia

Morphological findings in death due to hypothermia are variable and predominantly unspecific. Goal of this study was to check the usefulness of post-mortem cross-sectional imaging methods in the diagnosis of externally invisible findings in death due to hypothermia. Three consecutive forensic cases that died due to hypothermia were examined using post-mortem multi-slice computed tomography (MSCT) and magnetic resonance imaging (MRI) prior to autopsy. MSCT excluded traumatic skeletal and fatty tissue injury. Using MRI, it was possible to detect hemorrhages within the muscles of the back in all three cases, a so far unknown finding in death due to hypothermia. MRI also allowed the detection of hemorrhages in the iliopsoas muscles. Wishnewsky spots remained radiologically undetected using the present examination techniques. In conclusion, hemorrhages of the muscles of the back might serve as a new sign of death due to hypothermia; however, additional studies on their specificity are necessary. Post-mortem MRI is considered as a good diagnosing tool for muscular hemorrhages, with a great potential for examination and documentation.

Deep gray matter atrophy in multiple sclerosis: a tensor based morphometry.

Tensor based morphometry (TBM) was applied to determine the atrophy of deep gray matter (DGM) structures in 88 relapsing multiple sclerosis (MS) patients. For group analysis of atrophy, an unbiased atlas was constructed from 20 normal brains. The MS brain images were co-registered with the unbiased atlas using a symmetric inverse consistent nonlinear registration. These studies demonstrate significant atrophy of thalamus, caudate nucleus, and putamen even at a modest clinical disability, as assessed by the expanded disability status score (EDSS). A significant correlation between atrophy and EDSS was observed for different DGM structures: (thalamus: r=-0.51, p=3.85 x 10(-7); caudate nucleus: r=-0.43, p=2.35 x 10(-5); putamen: r=-0.36, p=6.12 x 10(-6)). Atrophy of these structures also correlated with 1) T2 hyperintense lesion volumes (thalamus: r=-0.56, p=9.96 x 10(-9); caudate nucleus: r=-0.31, p=3.10 x 10(-3); putamen: r=-0.50, p=6.06 x 10(-7)), 2) T1 hypointense lesion volumes (thalamus: r=-0.61, p=2.29 x 10(-10); caudate nucleus: r=-0.35, p=9.51 x 10(-4); putamen: r=-0.43, p=3.51 x 10(-5)), and 3) normalized CSF volume (thalamus: r=-0.66, p=3.55 x 10(-12); caudate nucleus: r=-0.52, p=2.31 x 10(-7), and putamen: r=-0.66, r=2.13 x 10(-12)). More severe atrophy was observed mainly in thalamus at higher EDSS. These studies appear to suggest a link between the white matter damage and DGM atrophy in MS.

Quantification of the spatiotemporal microstructural organization of the human brain association, projection and commissural pathways across the lifespan using diffusion tensor tractography.

Using diffusion tensor tractography, we quantified the microstructural changes in the association, projection, and commissural compact white matter pathways of the human brain over the lifespan in a cohort of healthy right-handed children and adults aged 6-68 years. In both males and females, the diffusion tensor radial diffusivity of the bilateral arcuate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, corticospinal, somatosensory tracts, and the corpus callosum followed a U-curve with advancing age; fractional anisotropy in the same pathways followed an inverted U-curve. Our study provides useful baseline data for the interpretation of data collected from patients.

Leptomeningeal collateralization in acute ischemic stroke: Impact on prominent cortical veins in susceptibility-weighted imaging.

BACKGROUND The extent of hypoperfusion is an important prognostic factor in acute ischemic stroke. Previous studies have postulated that the extent of prominent cortical veins (PCV) on susceptibility-weighted imaging (SWI) reflects the extent of hypoperfusion. Our aim was to investigate, whether there is an association between PCV and the grade of leptomeningeal arterial collateralization in acute ischemic stroke. In addition, we analyzed the correlation between SWI and perfusion-MRI findings. METHODS 33 patients with acute ischemic stroke due to a thromboembolic M1-segment occlusion underwent MRI followed by digital subtraction angiography (DSA) and were subdivided into two groups with very good to good and moderate to no leptomeningeal collaterals according to the DSA. The extent of PCV on SWI, diffusion restriction (DR) on diffusion-weighted imaging (DWI) and prolonged mean transit time (MTT) on perfusion-imaging were graded according to the Alberta Stroke Program Early CT Score (ASPECTS). The National Institutes of Health Stroke Scale (NIHSS) scores at admission and the time between symptom onset and MRI were documented. RESULTS 20 patients showed very good to good and 13 patients poor to no collateralization. PCV-ASPECTS was significantly higher for cases with good leptomeningeal collaterals versus those with poor leptomeningeal collaterals (mean 4.1 versus 2.69; p=0.039). MTT-ASPECTS was significantly lower than PCV-ASPECTS in all 33 patients (mean 1.0 versus 3.5; p<0.00). CONCLUSIONS In our small study the grade of leptomeningeal collateralization correlates with the extent of PCV in SWI in acute ischemic stroke, due to the deoxyhemoglobin to oxyhemoglobin ratio. Consequently, extensive PCV correlate with poor leptomeningeal collateralization while less pronounced PCV correlate with good leptomeningeal collateralization. Further SWI is a very helpful tool in detecting tissue at risk but cannot replace PWI since MTT detects significantly more ill-perfused areas than SWI, especially in good collateralized subjects.

Imaging, anatomical, and molecular analysis of callosal formation in the developing human fetal brain

A complex set of axonal guidance mechanisms are utilized by axons to locate and innervate their targets. In the developing mouse forebrain, we previously described several midline glial populations as well as various guidance molecules that regulate the formation of the corpus callosum. Since agenesis of the corpus callosum is associated with over 50 different human congenital syndromes, we wanted to investigate whether these same mechanisms also operate during human callosal development. Here we analyze midline glial and commissural development in human fetal brains ranging from 13 to 20 weeks of gestation using both diffusion tensor magnetic resonance imaging and immunohistochemistry. Through our combined radiological and histological studies, we demonstrate the morphological development of multiple forebrain commissures/decussations, including the corpus callosum, anterior commissure, hippocampal commissure, and the optic chiasm. Histological analyses demonstrated that all the midline glial populations previously described in mouse, as well as structures analogous to the subcallosal sling and cingulate pioneering axons, that mediate callosal axon guidance in mouse, are also present during human brain development. Finally, by Northern blot analysis, we have identified that molecules involved in mouse callosal development, including Slit, Robo, Netrin1, DCC, Nfia, Emx1, and GAP-43, are all expressed in human fetal brain. These data suggest that similar mechanisms and molecules required for midline commissure formation operate during both mouse and human brain development. Thus, the mouse is an excellent model system for studying normal and pathological commissural formation in human brain development. (c) 2006 Wiley-Liss, Inc.

Tensor Completion for Multidimensional Inverse Problems with Applications to Magnetic Resonance Relaxometry

This thesis deals with tensor completion for the solution of multidimensional inverse problems. We study the problem of reconstructing an approximately low rank tensor from a small number of noisy linear measurements. New recovery guarantees, numerical algorithms, non-uniform sampling strategies, and parameter selection algorithms are developed. We derive a fixed point continuation algorithm for tensor completion and prove its convergence. A restricted isometry property (RIP) based tensor recovery guarantee is proved. Probabilistic recovery guarantees are obtained for sub-Gaussian measurement operators and for measurements obtained by non-uniform sampling from a Parseval tight frame. We show how tensor completion can be used to solve multidimensional inverse problems arising in NMR relaxometry. Algorithms are developed for regularization parameter selection, including accelerated k-fold cross-validation and generalized cross-validation. These methods are validated on experimental and simulated data. We also derive condition number estimates for nonnegative least squares problems. Tensor recovery promises to significantly accelerate N-dimensional NMR relaxometry and related experiments, enabling previously impractical experiments. Our methods could also be applied to other inverse problems arising in machine learning, image processing, signal processing, computer vision, and other fields.

Characterizing neural tissues with mass spectrometry imaging via enhanced computational approaches

Neuropeptides affect the activity of the myriad of neuronal circuits in the brain. They are under tight spatial and chemical control and the dynamics of their release and catabolism directly modify neuronal network activity. Understanding neuropeptide functioning requires approaches to determine their chemical and spatial heterogeneity within neural tissue, but most imaging techniques do not provide the complete information desired. To provide chemical information, most imaging techniques used to study the nervous system require preselection and labeling of the peptides of interest; however, mass spectrometry imaging (MSI) detects analytes across a broad mass range without the need to target a specific analyte. When used with matrix-assisted laser desorption/ionization (MALDI), MSI detects analytes in the mass range of neuropeptides. MALDI MSI simultaneously provides spatial and chemical information resulting in images that plot the spatial distributions of neuropeptides over the surface of a thin slice of neural tissue. Here a variety of approaches for neuropeptide characterization are developed. Specifically, several computational approaches are combined with MALDI MSI to create improved approaches that provide spatial distributions and neuropeptide characterizations. After successfully validating these MALDI MSI protocols, the methods are applied to characterize both known and unidentified neuropeptides from neural tissues. The methods are further adapted from tissue analysis to be able to perform tandem MS (MS/MS) imaging on neuronal cultures to enable the study of network formation. In addition, MALDI MSI has been carried out over the timecourse of nervous system regeneration in planarian flatworms resulting in the discovery of two novel neuropeptides that may be involved in planarian regeneration. In addition, several bioinformatic tools are developed to predict final neuropeptide structures and associated masses that can be compared to experimental MSI data in order to make assignments of neuropeptide identities. The integration of computational approaches into the experimental design of MALDI MSI has allowed improved instrument automation and enhanced data acquisition and analysis. These tools also make the methods versatile and adaptable to new sample types.

Tensor-Train decomposition for image classification problems

In these last years a great effort has been put in the development of new techniques for automatic object classification, also due to the consequences in many applications such as medical imaging or driverless cars. To this end, several mathematical models have been developed from logistic regression to neural networks. A crucial aspect of these so called classification algorithms is the use of algebraic tools to represent and approximate the input data. In this thesis, we examine two different models for image classification based on a particular tensor decomposition named Tensor-Train (TT) decomposition. The use of tensor approaches preserves the multidimensional structure of the data and the neighboring relations among pixels. Furthermore the Tensor-Train, differently from other tensor decompositions, does not suffer from the curse of dimensionality making it an extremely powerful strategy when dealing with high-dimensional data. It also allows data compression when combined with truncation strategies that reduce memory requirements without spoiling classification performance. The first model we propose is based on a direct decomposition of the database by means of the TT decomposition to find basis vectors used to classify a new object. The second model is a tensor dictionary learning model, based on the TT decomposition where the terms of the decomposition are estimated using a proximal alternating linearized minimization algorithm with a spectral stepsize.

Study Of The Homogeneity Of Drug Loaded In Polymeric Films Using Near-infrared Chemical Imaging And Split-plot Design.

Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.

Feasibility And Reproducibility Of Diffusion-weighted Magnetic Resonance Imaging Of The Fetal Brain In Twin-twin Transfusion Syndrome.

The aim of this study is to test the feasibility and reproducibility of diffusion-weighted magnetic resonance imaging (DW-MRI) evaluations of the fetal brains in cases of twin-twin transfusion syndrome (TTTS). From May 2011 to June 2012, 24 patients with severe TTTS underwent MRI scans for evaluation of the fetal brains. Datasets were analyzed offline on axial DW images and apparent diffusion coefficient (ADC) maps by two radiologists. The subjective evaluation was described as the absence or presence of water diffusion restriction. The objective evaluation was performed by the placement of 20-mm(2) circular regions of interest on the DW image and ADC maps. Subjective interobserver agreement was assessed by the kappa correlation coefficient. Objective intraobserver and interobserver agreements were assessed by proportionate Bland-Altman tests. Seventy-four DW-MRI scans were performed. Sixty of them (81.1%) were considered to be of good quality. Agreement between the radiologists was 100% for the absence or presence of diffusion restriction of water. For both intraobserver and interobserver agreement of ADC measurements, proportionate Bland-Altman tests showed average percentage differences of less than 1.5% and 95% CI of less than 18% for all sites evaluated. Our data demonstrate that DW-MRI evaluation of the fetal brain in TTTS is feasible and reproducible.

Intraventricular Mass Lesions At Magnetic Resonance Imaging: Iconographic Essay - Part 1.

The present essay is illustrated with magnetic resonance images obtained at the authors' institution over the past 15 years and discusses the main imaging findings of intraventricular tumor-like lesions (ependymoma, pilocytic astrocytoma, central neurocytoma, ganglioglioma, choroid plexus papilloma, primitive neuroectodermal tumors, meningioma, epidermoid tumor). Such lesions represent a subgroup of intracranial lesions with unique characteristics and some image patterns that may facilitate the differential diagnosis.

Intraventricular Mass Lesions At Magnetic Resonance Imaging: Iconographic Essay - Part 2.

The present essay is illustrated with magnetic resonance images obtained at the authors' institution over the past 15 years and discusses the main imaging findings of intraventricular tumor-like lesions (colloid cyst, oligodendroglioma, astroblastoma, lipoma, cavernoma) and of inflammatory/infectious lesions (neurocysticercosis and an atypical presentation of neurohistoplasmosis). Such lesions represent a subgroup of intracranial lesions with unique characteristics and some imaging patterns that may facilitate the differential diagnosis.

Two-dimensional Ultrasound And Ultrasound Elastography Imaging Of Trigger Points In Women With Myofascial Pain Syndrome Treated By Acupuncture And Electroacupuncture: A Double-blinded Randomized Controlled Pilot Study.

Chronic pain has been often associated with myofascial pain syndrome (MPS), which is determined by myofascial trigger points (MTrP). New features have been tested for MTrP diagnosis. The aim of this study was to evaluate two-dimensional ultrasonography (2D US) and ultrasound elastography (UE) images and elastograms of upper trapezius MTrP during electroacupuncture (EA) and acupuncture (AC) treatment. 24 women participated, aged between 20 and 40 years (M ± SD = 27.33 ± 5.05) with a body mass index ranging from 18.03 to 27.59 kg/m2 (22.59 ± 3.11), a regular menstrual cycle, at least one active MTrP at both right (RTPz) and left trapezius (LTPz) and local or referred pain for up to six months. Subjects were randomized into EA and AC treatment groups and the control sham AC (SHAM) group. Intensity of pain was assessed by visual analogue scale; MTrP mean area and strain ratio (SR) by 2D US and UE. A significant decrease of intensity in general, RTPz, and LTPz pain was observed in the EA group (p = 0.027; p < 0.001; p = 0.005, respectively) and in general pain in the AC group (p < 0.001). Decreased MTrP area in RTPz and LTPz were observed in AC (p < 0.001) and EA groups (RTPz, p = 0.003; LTPz, p = 0.005). Post-treatment SR in RTPz and LTPz was lower than pre-treatment in both treatment groups. 2D US and UE effectively characterized MTrP and surrounding tissue, pointing to the possibility of objective confirmation of subjective EA and AC treatment effects.