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1

Identification of brains tissue hyperelastic parameters

Kuś W., Poręba-Sebastjan M.

Journal of Applied Mathematics and Computational Mechanics

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2018

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Vol. 17, nr 3

53--60

EN

The goal of the paper is to correlate real brain deflection with its numerical model as the 3D model of a fragment of the brain and suction pipe. The model is analyzed with the Finite Element Method with use of Ansys software. The brain tissue can undergo large strains, which is why it is described by a hyperelastic material. The Mooney-Rivlin material model is used for numerical analyzes. The inverse problem is solved with use of optimization Non-Linear Programming by Quadratic Lagrangian (NLPQL).

2

An example of the application of Mössbauer spectroscopy for determination of concentration of iron in lyophilized brain tissue

Rzepecka P., Duda P., Giebułtowicz J., Sochacka M., Friedman A., Gałązka-Friedman J.

Nukleonika

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2017

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Vol. 62, No. 2

159--163

EN

Mössbauer spectroscopy is not routinely used for the determination of the concentration of iron. However, as this method does not need any pre-treatment of samples before measurements, it may be of extreme importance for the assessment of iron in samples, which can then be used for further investigations. Biological samples are a good example, however, as the concentrations of iron are very low in these, it is important to exclude possible artefacts from the background spectrum related to iron present in the counter and cryostat windows. The aim of this study was to compare two methods of determination of the amounts of iron in investigated sample: one, in which the background spectrum was subtracted from the sample spectrum measured, and the other, in which the obtained non-elaborated spectrum was fitted with two doublets – a doublet for the measured sample and a doublet for the background spectrum. Three samples containing known amounts of natural iron (400, 800 and 1600 µg) and a sample of lyophilized human brain tissue obtained from globus pallidus were assessed. Both methods led to the creation of a very good calibration curve with a correlation coefficient of 0.99. Although both methods gave similar results for the concentration of iron in the sample, the subtraction of the background spectrum had a significantly lower error of the final result.

3

Aminobutyric Acid in Rat Brain Tissue Samples Using Benzoyl Chloride Derivatization and PDA Detection

Akula K. K., Chandrasekaran B., Kaur M., Kulkarni S. K.

Acta Chromatographica

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2015

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Vol. 27, no. 3

413--433

EN

A new, rapid, and specific reversed phase high-performance liquid chromatographic (RP-HPLC) method involving precolumn derivatization with benzoyl chloride was developed and validated for the estimation of γ-aminobutyric acid (GABA) in rat brain tissue preparations. The derivatization product of GABA was identified by melting point, infrared, and proton nuclear magnetic resonance (1H NMR) spectroscopy to be n-benzoyl GABA. Various parameters which influenced derivatization and elusion were optimized. The chromatographic system consisted of C-18 column with ultraviolet (UV)—photodiode array detection ranging from 210 to 400 nm. Elution with an isocratic mobile phase consisting of 0.025 M disodium hydrogen phosphate buffer—methanol (65:35, v/v; pH 6) at a flow rate of 1 mL min-1 yielded sharp and specific peak of n-benzoyl GABA within 7 min. The method was validated with respect to the linearity, accuracy, precision, sensitivity, selectivity, and stability, wherein the benzoyl derivative of GABA showed stability for 2 months. The lower limit of detection was 0.5 nmol L-1. This novel derivatization procedure for the estimation of GABA with benzoyl chloride was also applied for rat brain tissue preparations that gave highly specific peak and good component recovery. The results show that the method for the determination of GABA by benzoylation using RP-HPLC has good linearity, accuracy, precision, sensitivity, and specificity and is simple and economical to perform.

4

Zastosowanie syntezy i analizy obwodów elektrycznych do wyznaczania oporów naczyniowych tkanki mózgowej

Muc A., Szarmach A., Szurowska E., Dzierżanowski J.

Pomiary Automatyka Robotyka

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2014

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R. 18, nr 3

107--111

PL

W pracy przedstawiono schemat obwodowy odwzorowujący przepływ krwi przez tkankę mózgową oraz metodę identyfikacji jego parametrów elektrycznych na podstawie rzeczywistych danych medycznych otrzymanych w wyniku zastosowania nieinwazyjnych procedur zabiegowych. Celem modelowania i identyfikacji jest usprawnienie diagnostyki patologii mózgowych o podłożu naczyniowym. Podczas identyfikacji uwzględniono średnie wartości regionalnego przeływu krwi (rCBF) i ciśnienia tętniczego (MAP), którym w schemacie obwodowym odpowiada stały prąd i napięcie. Dysponując jedynie stałym napięciem i prądem syntezowano obwód prądu stałego, w którym rezystancjom odpowiadają wypadkowe opory naczyniowe warstw skanowanej tkanki mózgowej. Praca została wykonana w ramach projektu „Interdyscyplinarna kadra akademicka na rzecz rozwoju gospodarki opartej na wiedzy” współfinansowanego ze środków Unii Europejskiej w ramach Europejskiego Funduszu Społecznego.

EN

In this study, the results of computed tomography perfusion (p-CT) was used to create a model of blood flow through the brain tissue as a constant current circuit. The equivalent electric circuit of the blood flow has been developed on the basis of similarities between electrical engineering and haemodynamics. Created model allows us to determine the additional hemodynamic brain blood flow in the form of resistance. The resistances in circuit are corresponding to vascular resistance for the individual layers and the entire scanned area of the brain. The mathematical model that results from the electric circuit, allows the analysis of the relationship between the layers of p-CT. The purpose of the modeling of brain tissue using an electrical circuit and then the identification of his parameters is a need to improve the diagnosis of cerebral vascular pathology. This work was financially supported by the European Community from the European Social Fund within the INTERKADRA project.

5

Zastosowanie technik XRF i PIXE w analizie składu pierwiastkowego tkanki mózgu

Szczerbkowska-Boruchowska M., Ostachowicz J.

LAB Laboratoria, Aparatura, Badania

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2004

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R. 9, nr 3

22-27

6

Biomechanics of brain for computer assisted surgery

Miller K.

Zeszyty Naukowe Katedry Mechaniki Stosowanej / Politechnika Śląska

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2003

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z. 20

309-314

EN

Many modern applications of technology to medicine require knowledge of mechanical properties of very soft tissues. In this paper a model of mechanical properties of brain tissue is described and identified. A non-linear, viscoelastic model based on the generalization of the Ogden strain energy hyperelastic constitutive equation is proposed. The material parameters are identified using in-vitro experimental results. The model accounts well for brain tissue deformation behaviour in both tension and compression for strain rates typical for surgical procedures and natural strain between -0.3 and 0.2.

PL

Wiele nowoczesnych zastosowań technologii w medycynie wymaga znajomość, własności mechanicznych tkanek "bardzo" miękkich. W pracy opisano i zidentyfikowano model własności mechanicznych tkanki mózgowej. Zaproponowano nieliniowy model konstytutywny oparty na uogólnieniu funkcji energii Ogdena. Stałe materiałowe zidentyfikowana na podstawę pomiarów in-vitro. Model dobrze opisuje własności tkanki zarówno przy ściskaniu jak i rozciąganiu dla prędkości odkształcenia typowych dla procedur chirurgicznych w zakresie naturalnych odkształceń pomiędzy -0.3 a 0.2.