Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>Steady state (SS) and transient temperature-rise in tissue from radiofrequency exposure forms the underlying basis for limits in international exposure guidelines. Periodically pulsed or intermittent exposures form a special case of having both peak and average levels, producing temperature-rise oscillations in the SS. Presented here is a method for determining tissue temperature-rise for periodic specific absorption rate (SAR) modulation having arbitrary waveform. It involves the finite difference solution of a form of the Pennes Bioheat Transfer equation (BHTE) and uses the concept of the transfer function and the Fast Fourier Transform (FFT). The time-dependent BHTE is converted to a SS harmonic version by assuming that the time-dependent SAR waveform and tissue temperature can both be represented by Fourier series. The transfer function is obtained from solutions of the harmonic BHTE for an assumed SAR waveform consisting of periodic impulses. The temperature versus time response for an arbitrary periodic SAR waveform is obtained from the inverse FFT of the product of the transfer function and the FFT of the actual SAR waveform. This method takes advantage of existing FFT algorithms on most computational platforms and the ability to store the transfer function for later re-use. The transfer function varies slowly with harmonic number, allowing interpolation and extrapolation to reduce the computational effort. The method is highly efficient for the case where repeated temperature-rise calculations for parameter variations in the SAR waveform are sought. Examples are given for a narrow, circularly symmetric beam incident on a planar skin/fat/muscle model with rectangular, triangular and cosine-pulsed SAR modulation waveforms. Calculations of temperature-rise crest factor as a function of rectangular pulse duty factor and pulse repetition frequency for the same exposure/tissue model are also presented as an example of the versatility of the method.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We evaluate a series of thin-sheet hydrogel molecularly imprinted polymers (MIPs), using a family of acrylamide-based monomers, selective for the target protein myoglobin (Mb). The simple production of the thin-sheet MIP offers an alternative biorecognition surface that is robust, stable and uniform, and has the potential to be adapted for biosensor applications. The MIP containing the functional monomer <jats:italic>N</jats:italic>-hydroxymethylacrylamide (NHMAm), produced optimal specific rebinding of the target protein (Mb) with 84.9% (± 0.7) rebinding and imprinting and selectivity factors of 1.41 and 1.55, respectively. The least optimal performing MIP contained the functional monomer <jats:italic>N,N</jats:italic>-dimethylacrylamide (DMAm) with 67.5% (± 0.7) rebinding and imprinting and selectivity factors of 1.11 and 1.32, respectively. Hydrogen bonding effects, within a protein-MIP complex, were investigated using computational methods and Fourier transform infrared (FTIR) spectroscopy. The quantum mechanical calculations predictions of a red shift of the monomer carbonyl peak is borne-out within FTIR spectra, with three of the MIPs, acrylamide, N-(hydroxymethyl) acrylamide, and <jats:italic>N</jats:italic>-(hydroxyethyl) acrylamide, showing peak downshifts of 4, 11, and 8 cm<jats:sup>−1</jats:sup>, respectively.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>One method for detecting radiotherapy treatment errors is to capture the exit dose using an electronic portal imaging device. In comparison with a baseline integrated image, subsequent fractions can be compared and differences in images suggest a difference in the radiation treatment delivered. The aim of this work was to assess the sensitivity of a commercial software PerFRACTION in detecting such differences, arising from three possible sources: (i) changes in the radiation beam or EPID position; (ii) changes in the patient position; and (iii) changes in the patient anatomy. By systematically introducing errors, PerFRACTION was shown to be very sensitive to changes in the radiation beam. Variation in the beam output could be detected within 0.3%, field size within 0.4 mm, collimator rotation within 0.3° and MLC positioning could be verified to within 0.1 mm. EPID misalignment could be detected within 0.3 mm. PerFRACTION was able to detect the mispositioning of an anthropomorphic phantom by 3 mm with static beams, however there was a relative dependency between the patient geometry and the direction of the shift. VMAT beams were less sensitive to patient misalignments, with a shift of 10 mm only detectable once a strict criterion of 1% dose difference was applied. In another simulated scenario PerFRACTION was also able to detect a weight loss equivalent to a 5 mm change in patient separation in VMAT plans and 10 mm in conformal plans. This work showed that the PerFRACTION software could be relied upon to detect potential radiotherapy treatment errors, arising from a variety of sources.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Tissue engineering is a branch of regenerative medicine that harnesses biomaterial and stem cell research to utilise the body’s natural healing responses to regenerate tissue and organs. There remain many unanswered questions in tissue engineering, with optimal biomaterial designs still to be developed and a lack of adequate stem cell knowledge limiting successful application. Advances in artificial intelligence (AI), and deep learning specifically, offer the potential to improve both scientific understanding and clinical outcomes in regenerative medicine. With enhanced perception of how to integrate artificial intelligence into current research and clinical practice, AI offers an invaluable tool to improve patient outcome.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Objective</jats:italic>. Software to visualize estimated volume of tissue activated (VTA) in deep brain stimulation assuming a homogeneous tissue surrounding such as SureTune3 has recently become available for clinical use. The objective of this study is to compare SureTune3 with homogeneous and heterogeneous patient-specific finite element method (FEM) simulations of the VTA to elucidate how well they coincide in their estimates. <jats:italic>Approach</jats:italic>. FEM simulations of the VTA were performed in COMSOL Multiphysics and compared with VTA from SureTune3 with variation of voltage and current amplitude, pulse width, axon diameter, number of active contacts, and surrounding homogeneous grey or white matter. Patient-specific simulations with heterogeneous tissue were also performed. <jats:italic>Main results</jats:italic>. The VTAs corresponded well for voltage control in homogeneous tissue, though with the smallest VTAs being slightly larger in SureTune3 and the largest VTAs being slightly larger in the FEM simulations. In current control, FEM estimated larger VTAs in white matter and smaller VTAs in grey matter compared to SureTune3 as grey matter has higher electric conductivity than white matter and requires less voltage to reach the same current. The VTAs also corresponded well in the patient-specific cases except for one case with a cyst of highly conductive cerebrospinal fluid (CSF) near the active contacts. <jats:italic>Significance</jats:italic>. The VTA estimates without taking the surrounding tissue into account in SureTune3 are in good agreement with patient-specific FEM simulations when using voltage control in the absence of CSF-filled cyst. In current control or when CSF is present near the active contacts, the tissue characteristics are important for the VTA and needs consideration. <jats:italic>Clinical</jats:italic>. trial ethical approval: Local ethics committee at Linköping University (2012/434-31).</jats:p>