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Optimization of Pulse Sequences in Magnetic Resonance Lymphography of Axillary Lymph Nodes Using Magnetic Nanoparticles

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Magnetic resonance imaging pulse sequences have an important role in detection of lymph nodes using magnetic nanoparticles as a contrast agent. Current imaging sequences lack an optimum pulse sequence based on lymph node relaxation times after accumulation of magnetic nanoparticles. This deficiency is due to the limited information regarding the particle uptake in tissues, and their related magnetic properties used by magnetic resonance imaging. The aim of this study is to optimize the imaging pulse sequences based on in vivo measurement of relaxation times for obtaining the best contrast-enhanced images of axillary lymph nodes. In vivo studies were performed on normal rats on a 1.5 T clinical magnetic resonance imaging system. The used contrast agent was dextran coated iron oxide nanoparticles with a mean diameter of 20 nm. Relaxation time measurements were performed for enhanced (after injection) and nonenhanced axillary lymph nodes, and the surrounding tissue. Since magnetic resonance signal depends highly on tissue parameters; T1, T2, and T2*, as well as magnetic resonance acquisition parameters; repetition time and echo time, knowing the tissue characteristics is important in order to design a right magnetic resonance protocol for each application. Based on our proposed approach, the relaxivity characteristic of the lymph node after accumulation of a contrast agent and its corresponding relaxation rate is used to define optimum imaging parameters (i.e., repetition time and echo time) for maximum contrast. According to these imaging parameter values, various T1, T2, T2* and proton density weighted sequences were applied. Optimum pulse sequences were found to be T2*-weighted fast gradient echo, T1-weighted fast spoiled gradient echo and proton density-weighted fast spin echo sequences.
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Document Type: Research Article

Publication date: 2009-07-01

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  • Journal for Nanoscience and Nanotechnology (JNN) is an international and multidisciplinary peer-reviewed journal with a wide-ranging coverage, consolidating research activities in all areas of nanoscience and nanotechnology into a single and unique reference source. JNN is the first cross-disciplinary journal to publish original full research articles, rapid communications of important new scientific and technological findings, timely state-of-the-art reviews with author's photo and short biography, and current research news encompassing the fundamental and applied research in all disciplines of science, engineering and medicine.
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