4 resultados para Optical dispersion

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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A main field in biomedical optics research is diffuse optical tomography, where intensity variations of the transmitted light traversing through tissue are detected. Mathematical models and reconstruction algorithms based on finite element methods and Monte Carlo simulations describe the light transport inside the tissue and determine differences in absorption and scattering coefficients. Precise knowledge of the sample's surface shape and orientation is required to provide boundary conditions for these techniques. We propose an integrated method based on structured light three-dimensional (3-D) scanning that provides detailed surface information of the object, which is usable for volume mesh creation and allows the normalization of the intensity dispersion between surface and camera. The experimental setup is complemented by polarization difference imaging to avoid overlaying byproducts caused by inter-reflections and multiple scattering in semitransparent tissue.

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We have recently developed a method to obtain distributed atomic polarizabilities adopting a partitioning of the molecular electron density (for example, the Quantum Theory of Atoms in Molecules, [1]), calculated with or without an applied electric field. The procedure [2] allows to obtained atomic polarizability tensors, which are perfectly exportable, because quite representative of an atom in a given functional group. Among the many applications of this idea, the calculation of crystal susceptibility is easily available, either from a rough estimation (the polarizability of the isolated molecule is used) or from a more precise estimation (the polarizability of a molecule embedded in a cluster representing the first coordination sphere is used). Lorentz factor is applied to include the long range effect of packing, which is enhancing the molecular polarizability. Simple properties like linear refractive index or the gyration tensor can be calculated at relatively low costs and with good precision. This approach is particularly useful within the field of crystal engineering of organic/organometallic materials, because it would allow a relatively easy prediction of a property as a function of the packing, thus allowing "reverse crystal engineering". Examples of some amino acid crystals and salts of amino acids [3] will be illustrated, together with other crystallographic or non-crystallographic applications. For example, the induction and dispersion energies of intermolecular interactions could be calculated with superior precision (allowing anisotropic van der Waals interactions). This could allow revision of some commonly misunderstood intermolecular interactions, like the halogen bonding (see for example the recent remarks by Stone or Gilli [4]). Moreover, the chemical reactivity of coordination complexes could be reinvestigated, by coupling the conventional analysis of the electrostatic potential (useful only in the circumstances of hard nucleophilic/electrophilic interaction) with the distributed atomic polarizability. The enhanced reactivity of coordinated organic ligands would be better appreciated. [1] R. F. W. Bader, Atoms in Molecules: A Quantum Theory. Oxford Univ. Press, 1990. [2] A. Krawczuk-Pantula, D. Pérez, K. Stadnicka, P. Macchi, Trans. Amer. Cryst. Ass. 2011, 1-25 [3] A. S. Chimpri1, M. Gryl, L. H.R. Dos Santos1, A. Krawczuk, P. Macchi Crystal Growth & Design, in the press. [4] a) A. J. Stone, J. Am. Chem. Soc. 2013, 135, 7005−7009; b) V. Bertolasi, P. Gilli, G. Gilli Crystal Growth & Design, 2013, 12, 4758-4770.

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OBJECTIVE This study presents the first in vivo real-time optical tissue characterization during image-guided percutaneous intervention using near-infrared diffuse optical spectroscopy sensing at the tip of a needle. The goal of this study was to indicate transition boundaries from healthy tissue to tumors, namely, hepatic carcinoma, based on the real-time feedback derived from the optical measurements. MATERIALS AND METHODS Five woodchucks with hepatic carcinoma were used for this study. The woodchucks were imaged with contrast-enhanced cone beam computed tomography with a flat panel detector C-arm system to visualize the carcinoma in the liver. In each animal, 3 insertions were performed, starting from the skin surface toward the hepatic carcinoma under image guidance. In 2 woodchucks, each end point of the insertion was confirmed with pathologic examination of a biopsy sample. While advancing the needle in the animals under image guidance such as fluoroscopy overlaid with cone beam computed tomography slice and ultrasound, optical spectra were acquired at the distal end of the needles. Optical tissue characterization was determined by translating the acquired optical spectra into clinical parameters such as blood, water, lipid, and bile fractions; tissue oxygenation levels; and scattering amplitude related to tissue density. The Kruskal-Wallis test was used to study the difference in the derived clinical parameters from the measurements performed within the healthy tissue and the hepatic carcinoma. Kurtoses were calculated to assess the dispersion of these parameters within the healthy and carcinoma tissues. RESULTS Blood and lipid volume fractions as well as tissue oxygenation and reduced scattering amplitude showed to be significantly different between the healthy part of the liver and the hepatic carcinoma (P < 0.05) being higher in normal liver tissue. A decrease in blood and lipid volume fractions and tissue oxygenation as well as an increase in scattering amplitude were observed when the tip of the needle crossed the margin from the healthy liver tissue to the carcinoma. The kurtosis for each derived clinical parameter was high in the hepatic tumor as compared with that in the healthy liver indicating intracarcinoma variability. CONCLUSIONS Tissue blood content, oxygenation level, lipid content, and tissue density all showed significant differences when the needle tip was guided from the healthy tissue to the carcinoma and can therefore be used to identify tissue boundaries during percutaneous image-guided interventions.