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Relaxation-based color magnetic particle imaging for viscosity mapping

机译:基于粘度测绘的基于弛豫的颜色磁性粒子成像

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摘要

Magnetic particle imaging (MPI) uses superparamagnetic iron oxide (SPIO) nanoparticles as biomedical imaging tracers. The potential applications of MPI have recently been broadened by the introduction of "color" MPI techniques that can distinguish different nanoparticles and/or environments, e.g., by exploiting the relaxation behavior of SPIOs. One of the important applications of color MPI techniques is viscosity mapping. In this work, we show relaxation-based color MPI experiments that can distinguish the biologically relevant viscosity range of up to 5 mPa s. To find the optimal drive field parameters for viscosity, we compare color MPI results at three different frequencies. We show that frequencies around 10 kHz are well-suited for viscosity mapping using the multicore cluster Nanomag-MIP nanoparticles, providing a one-to-one mapping between the estimated relaxation time constant and viscosity.
机译:磁性颗粒成像(MPI)使用超顺磁性氧化铁(SPIO)纳米颗粒作为生物医学成像示踪剂。最近通过引入“颜色”MPI技术来扩大MPI的潜在应用,其可以区分不同的纳米颗粒和/或环境,例如,通过利用SPIOS的松弛行为。颜色MPI技术的重要应用之一是粘度测绘。在这项工作中,我们展示了基于弛豫的颜色MPI实验,可以将生物相关的粘度范围与高达5MPa的区分开。要找到粘度的最佳驱动场参数,我们将彩色MPI与三种不同频率进行比较。我们表明,在10kHz约10kHz左右的频率非常适合使用多芯簇纳米磁磁镀米粒子纳米粒子的粘度映射,在估计的弛豫时间恒定和粘度之间提供一对一的映射。

著录项

  • 来源
    《Applied Physics Letters》 |2019年第15期|152403.1-152403.5|共5页
  • 作者单位

    Bilkent Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey|Bilkent Univ Natl Magnet Resonance Res Ctr UMRAM TR-06800 Ankara Turkey;

    Bilkent Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey|Bilkent Univ Natl Magnet Resonance Res Ctr UMRAM TR-06800 Ankara Turkey|Univ Wisconsin Dept Biomed Engn Madison WI 53706 USA|Univ Wisconsin Dept Radiol Madison WI 53706 USA;

    Bilkent Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey|Bilkent Univ Natl Magnet Resonance Res Ctr UMRAM TR-06800 Ankara Turkey|Bilkent Univ Sabuncu Brain Res Ctr Neurosci Program TR-06800 Ankara Turkey;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 22:17:49

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