956 resultados para Medical Physics, Hyperpolarization, Metabolic Imaging


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A major challenge in imaging is the detection of small amounts of molecules of interest. In the case of magnetic resonance imaging (MRI) their signals are typically concealed by the large background signal of e.g. the tissue of the body. This problem can be tackled by hyperpolarization which increases the NMR signals up to several orders of magnitude. However, this strategy is limited for 1H, the most widely used nucleus in NMR andrnMRI, because the enormous number of protons in the body screen the small amount of hyperpolarized ones.Here, I describe a method giving rise to high 1H MRI contrast for hyperpolarized molecules against a large background signal. The contrast is based on the J-coupling induced rephasing of the NMR signal of molecules hyperpolarized via parahydrogen induce polarization (PHIP) and it can easily be implemented in common pulse sequences.rnrnHyperpolarization methods typically require expensive technical equipment (e.g. lasers or microwaves) and most techniques work only in batch mode, thus the limited lifetime of the hyperpolarization is limiting its applications. Therefore, the second part of my thesis deals with the simple and efficient generation of an hyperpolarization.These two achievements open up alternative opportunities to use the standard MRI nucleus 1H for e.g. metabolic imaging in the future.

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The focus of this Editorial is recent developments in magnetic resonance imaging (MRI) modalities for evaluation of the microstructure and macromolecular organisation of articular cartilage. We place a specific emphasis on three types of measurements: (1) MRI transverse spin-relaxation mapping (T2 mapping); (2) diffusion-tensor imaging; and (3) compression micro-MRI (uMRI) measurements of articular cartilage in vitro. Such studies have a significant role to play in improving the understanding of the fundamental biomechanics of articular cartilage and in the development of in vitro models of early osteoarthritis. We discuss how the supramolecular organisation of the cartilage extracellular matrix and its behaviour under mechanical compression can be inferred from diffusion-tensor and T2 maps with in-plane resolution ~100 um. The emphasis is on in vitro studies performed under controlled physiological conditions but in vivo applications of T2 mapping and DTI are also briefly discussed.

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We present a mini-review of the development and contemporary applications of diffusion-sensitive nuclear magnetic resonance (NMR) techniques in biomedical sciences. Molecular diffusion is a fundamental physical phenomenon present in all biological systems. Due to the connection between experimentally measured diffusion metrics and the microscopic environment sensed by the diffusing molecules, diffusion measurements can be used for characterisation of molecular size, molecular binding and association, and the morphology of biological tissues. The emergence of magnetic resonance was instrumental to the development of biomedical applications of diffusion. We discuss the fundamental physical principles of diffusion NMR spectroscopy and diffusion MR imaging. The emphasis is placed on conceptual understanding, historical evolution and practical applications rather than complex technical details. Mathematical description of diffusion is presented to the extent that it is required for the basic understanding of the concepts. We present a wide range of spectroscopic and imaging applications of diffusion magnetic resonance, including colloidal drug delivery vehicles; protein association; characterisation of cell morphology; neural fibre tractography; cardiac imaging; and the imaging of load-bearing connective tissues. This paper is intended as an accessible introduction into the exciting and growing field of diffusion magnetic resonance.

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This study aims to help broaden the use of electronic portal imaging devices (EPIDs) for pre-treatment patient positioning verification, from photon-beam radiotherapy to photon- and electron-beam radiotherapy, by proposing and testing a method for acquiring clinicallyuseful EPID images of patient anatomy using electron beams, with a view to enabling and encouraging further research in this area. EPID images used in this study were acquired using all available beams from a linac configured to deliver electron beams with nominal energies of 6, 9, 12, 16 and 20 MeV, as well as photon beams with nominal energies of 6 and 10 MV. A widely-available heterogeneous, approximately-humanoid, thorax phantom was used, to provide an indication of the contrast and noise produced when imaging different types of tissue with comparatively realistic thicknesses. The acquired images were automatically calibrated, corrected for the effects of variations in the sensitivity of individual photodiodes, using a flood field image. For electron beam imaging, flood field EPID calibration images were acquired with and without the placement of blocks of water-equivalent plastic (with thicknesses approximately equal to the practical range of electrons in the plastic) placed upstream of the EPID, to filter out the primary electron beam, leaving only the bremsstrahlung photon signal. While the electron beam images acquired using a standard (unfiltered) flood field calibration were observed to be noisy and difficult to interpret, the electron beam images acquired using the filtered flood field calibration showed tissues and bony anatomy with levels of contrast and noise that were similar to the contrast and noise levels seen in the clinically acceptable photon beam EPID images. The best electron beam imaging results (highest contrast, signal-to-noise and contrast-to-noise ratios) were achieved when the images were acquired using the higher energy electron beams (16 and 20 MeV) when the EPID was calibrated using an intermediate (12 MeV) electron beam energy. These results demonstrate the feasibility of acquiring clinically-useful EPID images of patient anatomy using electron beams and suggest important avenues for future investigation, thus enabling and encouraging further research in this area. There is manifest potential for the EPID imaging method proposed in this work to lead to the clinical use of electron beam imaging for geometric verification of electron treatments in the future.

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The RET (rearranged-during-transfection protein) protooncogene triggers multiple intracellular signaling cascades regulating cell cycle progression and cellular metabolism. We therefore hypothesized that metabolic imaging could allow noninvasive detection of response to the RET inhibitor vandetanib in vivo.

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Positron emission tomography (PET)-computed tomography (CT) using [18F]-fluorodeoxyglucose (FDG) (FDG-PET/CT) is a valuable method for initial staging and follow up of patients with alveolar echinococcosis (AE). However, the cells responsible for FDG uptake have not been clearly identified. The main goal of our study was to evaluate the uptake of PET tracers by the cells involved in the host-parasite reaction around AE lesions as the first step to develop a specific PET tracer that would allow direct assessment of parasite viability in AE. Candidate molecules ([18F]-fluorotyrosine (FET), [18F]-fluorothymidine (FLT), and [18F]-fluorometylcholine (FMC), were compared to FDG by in vitro studies on human leukocytes and parasite vesicles. Our results confirmed that FDG was mainly consumed by immune cells and showed that FLT was the best candidate tracer for parasite metabolism. Indeed, parasite cells exhibited high uptake of FLT. We also performed PET/CT scans in mice infected intraperitoneally with E. multilocularis metacestodes. PET images showed no FDG or FLT uptake in parasitic lesions. This preliminary study assessed the metabolic activity of human leukocytes and AE cells using radiolabeling. Future studies could develop a specific PET tracer for AE lesions to improve lesion detection and echinococcosis treatment in patients. Our results demonstrated that a new animal model is needed for preclinical PET imaging to better mimic human hepatic and/or periparasitic metabolism.

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Mode of access: Internet.

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In this work, a Langevin dynamics model of the diffusion of water in articular cartilage was developed. Numerical simulations of the translational dynamics of water molecules and their interaction with collagen fibers were used to study the quantitative relationship between the organization of the collagen fiber network and the diffusion tensor of water in model cartilage. Langevin dynamics was used to simulate water diffusion in both ordered and partially disordered cartilage models. In addition, an analytical approach was developed to estimate the diffusion tensor for a network comprising a given distribution of fiber orientations. The key findings are that (1) an approximately linear relationship was observed between collagen volume fraction and the fractional anisotropy of the diffusion tensor in fiber networks of a given degree of alignment, (2) for any given fiber volume fraction, fractional anisotropy follows a fiber alignment dependency similar to the square of the second Legendre polynomial of cos(θ), with the minimum anisotropy occurring at approximately the magic angle (θMA), and (3) a decrease in the principal eigenvalue and an increase in the transverse eigenvalues is observed as the fiber orientation angle θ progresses from 0◦ to 90◦. The corresponding diffusion ellipsoids are prolate for θ < θMA, spherical for θ ≈ θMA, and oblate for θ > θMA. Expansion of the model to include discrimination between the combined effects of alignment disorder and collagen fiber volume fraction on the diffusion tensor is discussed.

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Monte Carlo simulations were used to investigate the relationship between the morphological characteristics and the diffusion tensor (DT) of partially aligned networks of cylindrical fibres. The orientation distributions of the fibres in each network were approximately uniform within a cone of a given semi-angle (θ0). This semi-angle was used to control the degree of alignment of the fibres. The networks studied ranged from perfectly aligned (θ0 = 0) to completely disordered (θ0 = 90°). Our results are qualitatively consistent with previous numerical models in the overall behaviour of the DT. However, we report a non-linear relationship between the fractional anisotropy (FA) of the DT and collagen volume fraction, which is different to the findings from previous work. We discuss our results in the context of diffusion tensor imaging of articular cartilage. We also demonstrate how appropriate diffusion models have the potential to enable quantitative interpretation of the experimentally measured diffusion-tensor FA in terms of collagen fibre alignment distributions.

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a presentation about immersive visualised simulation systems, image analysis and GPGPU Techonology

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Introduction: 3.0 Tesla MRI offers the potential to quantify the volume fraction and structural texture of cancellous bone, along with quantification of marrow composition, in a single non-invasive examination. This study describes our preliminary investigations to identify parameters which describe cancellous bone structure including the relationships between texture and volume fraction.

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Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc. The geometric and dosimetric accuracy of CTCombine’s output has been assessed by simulating simple and complex treatments applied to a rotated planar phantom and a rotated humanoid phantom and comparing the resulting virtual EPID images with the images acquired using experimental measurements and independent simulations of equivalent phantoms. It is expected that CTCombine will be useful for Monte Carlo studies of EPID dosimetry as well as other EPID imaging applications.