Comparison of fractional and geodesic anisotropy in diffusion tensor images of 90 monozygotic and dizygotic twins

We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.

Probabilistic multi-tensor estimation using the tensor distribution function

Diffusion weighted magnetic resonance (MR) imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of 6 directions, second-order tensors can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve crossing fiber tracts. Recently, a number of high-angular resolution schemes with greater than 6 gradient directions have been employed to address this issue. In this paper, we introduce the Tensor Distribution Function (TDF), a probability function defined on the space of symmetric positive definite matrices. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the diffusion orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function.

Best individual template selection from deformation tensor minimization

We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. We also computed the intraclass correlation and associated permutation p-value at each voxel for the determinant of the Jacobian matrix of the transformation. The cumulative distribution function (cdf) of the p-values was found at each voxel for each of the templates and compared to the null distribution. Surprisingly, there was very little difference between CDFs of statistics computed from analyses using different templates. As the brain with least log-Euclidean deformation cost, the mean template defined here avoids the blurring caused by creating a synthetic image from a population, and when selected from a large population, avoids bias by being geometrically centered, in a metric that is sensitive enough to anatomical similarity that it can even detect genetic affinity among anatomies.

Investigating brain connectivity heritability in a twin study using diffusion imaging data

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.

How does angular resolution affect diffusion imaging measures?

A key question in diffusion imaging is how many diffusion-weighted images suffice to provide adequate signal-to-noise ratio (SNR) for studies of fiber integrity. Motion, physiological effects, and scan duration all affect the achievable SNR in real brain images, making theoretical studies and simulations only partially useful. We therefore scanned 50 healthy adults with 105-gradient high-angular resolution diffusion imaging (HARDI) at 4T. From gradient image subsets of varying size (6 ≤ N ≤ 94) that optimized a spherical angular distribution energy, we created SNR plots (versus gradient numbers) for seven common diffusion anisotropy indices: fractional and relative anisotropy (FA, RA), mean diffusivity (MD), volume ratio (VR), geodesic anisotropy (GA), its hyperbolic tangent (tGA), and generalized fractional anisotropy (GFA). SNR, defined in a region of interest in the corpus callosum, was near-maximal with 58, 66, and 62 gradients for MD, FA, and RA, respectively, and with about 55 gradients for GA and tGA. For VR and GFA, SNR increased rapidly with more gradients. SNR was optimized when the ratio of diffusion-sensitized to non-sensitized images was 9.13 for GA and tGA, 10.57 for FA, 9.17 for RA, and 26 for MD and VR. In orientation density functions modeling the HARDI signal as a continuous mixture of tensors, the diffusion profile reconstruction accuracy rose rapidly with additional gradients. These plots may help in making trade-off decisions when designing diffusion imaging protocols.

A Probe for the Selective and Parts-per-Billion-Level Detection of Copper(II) and Mercury(II) using a Micellar Medium and Its Utility in Cell Imaging

A novel colorimetric probe 1 based on the picolyl moiety has been designed and synthesized. Probe 1 is composed of a pyrene and a bispicolyl amine (BPA) unit, in which the BPA moiety acts as a binding unit and the binding phenomenon is sensed from the changes in the signaling subunit. The probe detects Cu2+ specifically in water and both Cu2+ and Hg2+ efficiently in neutral Brij-58 micellar media. The probe shows a color change visible to the naked eye upon addition of metal ions. Notably, in a micellar medium, probe 1 can detect both the Cu2+ and Hg2+ ions even at parts-per-billion levels. Furthermore, the probe shows ratiometric detection of both the metal ions making the sensing quantitative. The two metal ions could be discriminated both visibly under a UV lamp and with the use of fluorescence spectroscopy. The probe could be also used in biological cell lines for the detection of both Hg2+ and Cu2+ ions.

EVALUATION OF HARMONIC MOTION ELASTOGRAPHY AND ACOUSTO-­OPTIC IMAGING FOR MONITORING LESION FORMATION BY HIGH INTENSITY FOCUSED ULTRASOUND

Malignant or benign tumors may be ablated with high‐intensity focused ultrasound (HIFU). This technique, known as focused ultrasound surgery (FUS), has been actively investigated for decades, but slow to be implemented and difficult to control due to lack of real‐time feedback during ablation. Two methods of imaging and monitoring HIFU lesions during formation were implemented simultaneously, in order to investigate the efficacy of each and to increase confidence in the detection of the lesion. The first, Acousto‐Optic Imaging (AOI) detects the increasing optical absorption and scattering in the lesion. The intensity of a diffuse optical field in illuminated tissue is mapped at the spatial resolution of an ultrasound focal spot, using the acousto‐optic effect. The second, Harmonic Motion Imaging (HMI), detects the changing stiffness in the lesion. The HIFU beam is modulated to force oscillatory motion in the tissue, and the amplitude of this motion, measured by ultrasound pulse‐echo techniques, is influenced by the stiffness. Experiments were performed on store‐bought chicken breast and freshly slaughtered bovine liver. The AOI results correlated with the onset and relative size of forming lesions much better than prior knowledge of the HIFU power and duration. For HMI, a significant artifact was discovered due to acoustic nonlinearity. The artifact was mitigated by adjusting the phase of the HIFU and imaging pulses. A more detailed model of the HMI process than previously published was made using finite element analysis. The model showed that the amplitude of harmonic motion was primarily affected by increases in acoustic attenuation and stiffness as the lesion formed and the interaction of these effects was complex and often counteracted each other. Further biological variability in tissue properties meant that changes in motion were masked by sample‐to‐sample variation. The HMI experiments predicted lesion formation in only about a quarter of the lesions made. In simultaneous AOI/HMI experiments it appeared that AOI was a more robust method for lesion detection.

Autocrine loop in the purinergic control of airway surface liquid volume : monitoring with a novel side-view imaging technique

La Fibrose Kystique (FK) est une maladie dégénérative qui entraine une dégénération des poumons dû au problème de clairance mucociliaire (CMC). Le volume de surface liquide (SL) couvrant les cellules pulmonaires est essentiel à la clairance de mucus et au combat contre les infections. Les nucléotides extracellulaires jouent un rôle important dans la CMC des voies aériennes, en modifiant le volume de la SL pulmonaire. Cependant, les mécanismes du relâchement de l’ATP et de leurs déplacements à travers la SL, restent inconnus. Des études ultérieures démontrent que l’exocytose d’ATP mécano-sensible et Ca2+-dépendant, dans les cellules A549, est amplifié par les actions synergétiques autocrine/paracrine des cellules avoisinantes. Nous avions comme but de confirmer la présence de la boucle purinergique dans plusieurs modèles de cellules épithéliales et de développer un système nous permettant d’observer directement la SL. Nous avons démontrés que la boucle purinergique est fonctionnelle dans les modèles de cellules épithéliales examinés, mis appart les cellules Calu-3. L’utilisation de modulateur de la signalisation purinergique nous a permis d’observer que le relâchement d’ATP ainsi que l’augmentation du [Ca2+]i suivant un stress hypotonique, sont modulés par le biais de cette boucle purinergique et des récepteurs P2Y. De plus, nous avons développé un système de microscopie qui permet d’observer les changements de volume de SL en temps réel. Notre système permet de contrôler la température et l’humidité de l’environnement où se trouvent les cellules, reproduisant l’environnement pulmonaire humain. Nous avons démontré que notre système peut identifier même les petits changements de volume de SL.

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Analyzing diffusion tensor images with ghosting artifacts: the effects of direct and indirect normalization

The current study aims to assess the applicability of direct or indirect normalization for the analysis of fractional anisotropy (FA) maps in the context of diffusion-weighted images (DWIs) contaminated by ghosting artifacts. We found that FA maps acquired by direct normalization showed generally higher anisotropy than indirect normalization, and the disparities were aggravated by the presence of ghosting artifacts in DWIs. The voxel-wise statistical comparisons demonstrated that indirect normalization reduced the influence of artifacts and enhanced the sensitivity of detecting anisotropy differences between groups. This suggested that images contaminated with ghosting artifacts can be sensibly analyzed using indirect normalization.

CHANDRA AND SPITZER IMAGING OF THE INFRARED CLUSTER IN NGC 2071

We present results of a sensitive Chandra X-ray observation and Spitzer mid-infrared (mid-IR) observations of the IR cluster lying north of the NGC 2071 reflection nebula in the Orion B molecular cloud. We focus on the dense cluster core known as NGC 2071-IR, which contains at least nine IR sources within a 40 `` x 40 `` region. This region shows clear signs of active star formation including powerful molecular outflows, Herbig-Haro objects, and both OH and H(2)O masers. We use Spitzer Infrared Array Camera (IRAC) images to aid in X-ray source identification and to determine young stellar object (YSO) classes using mid-IR colors. Spitzer IRAC colors show that the luminous source IRS 1 is a class I protostar. IRS 1 is believed to be driving a powerful bipolar molecular outflow and may be an embedded B-type star or its progenitor. Its X-ray spectrum reveals a fluorescent Fe emission line at 6.4 keV, arising in cold material near the protostar. The line is present even in the absence of large flares, raising questions about the nature of the ionizing mechanism responsible for producing the 6.4 keV fluorescent line. Chandra also detects X-ray sources at or near the positions of IRS 2, IRS 3, IRS 4, and IRS 6 and a variable X-ray source coincident with the radio source VLA 1, located just 2 `` north of IRS 1. No IR data are yet available to determine a YSO classification for VLA 1, but its high X-ray absorption shows that it is even more deeply embedded than IRS 1, suggesting that it could be an even younger, less-evolved protostar.

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.