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![Field free point (FFP) trajectory modulation. Temporal progress of FFP and SPION position in laboratory system (xFFP(t),xs(t)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$x_{\mathrm{FFP}}(t), x_{\mathrm{s}}(t)$$\end{document}) and reference frame of the nanoparticles (xFFP′(t),xs′(t)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$x_{\mathrm{FFP}}^{\prime }(t), x_{\mathrm{s}}^{\prime }(t)$$\end{document}) for static and moving SPIONs. The modulation of the FFP trajectory in the SPIONs’ reference system xFFP′(t)=xFFP(t)+vst\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$x_{\mathrm{FFP}}^{\prime }(t) = x_{\mathrm{FFP}}(t) + v_{\mathrm{s}} t$$\end{document} is caused by the particles’ motion in the laboratory system.](publication/349592997/figure/fig2/AS:995344980668417@1614320144281/Field-free-point-FFP-trajectory-modulation-Temporal-progress-of-FFP-and-SPION-position.png)
Field free point (FFP) trajectory modulation. Temporal progress of FFP and SPION position in laboratory system (xFFP(t),xs(t)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$x_{\mathrm{FFP}}(t), x_{\mathrm{s}}(t)$$\end{document}) and reference frame of the nanoparticles (xFFP′(t),xs′(t)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$x_{\mathrm{FFP}}^{\prime }(t), x_{\mathrm{s}}^{\prime }(t)$$\end{document}) for static and moving SPIONs. The modulation of the FFP trajectory in the SPIONs’ reference system xFFP′(t)=xFFP(t)+vst\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$x_{\mathrm{FFP}}^{\prime }(t) = x_{\mathrm{FFP}}(t) + v_{\mathrm{s}} t$$\end{document} is caused by the particles’ motion in the laboratory system.
Source publication
Changes in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symp...
Citations
... We strive to identify closely aligned values between the flap and recipient vessels. [3][4][5] Patientspecific factors such as heart rate and blood pressure must be factored in; individuals with bradycardia or hypotension may exhibit distinct flow velocity values. Similarly, fever in a patient may manifest systemic inflammatory responses that could introduce bias during ultrasound assessment. ...
Background
Color-coded duplex sonography (CCDS) is a widely proposed noninvasive diagnostic tool in microsurgery. CCDS has been applied to lower extremity salvage cases to define appropriate blood flow velocity criteria for achieving arterial success in diabetic foot and complex microsurgery cases. This study aimed to compare the success ratio of free flaps when using CCDS versus cases where CCDS was not used.
Methods
We included complex microsurgery cases from 2019 to 2021. These cases were subsequently categorized into two groups: group A consisted of cases where CCDS parameters were applied, whereas group B comprised cases where CCDS was not performed at all.
Results
The study encompassed 14 cases (11 men and three women). The age range varied from 23 to 62 years, with an average age of 42. Using CCDS analysis and planning demonstrated improved outcomes in comparison with cases where CCDS was not performed, albeit without statistical significance ( P = 0.064).
Conclusions
The application of CCDS proves to be beneficial in the realm of microsurgery. Although not achieving statistical significance, our data imply that CCDS utilization holds promise for enhancing microsurgical procedures.
... This is much faster than the traditional 99m Tc-MAA studies with scintigraphy or SPECT, which typically requires three hours. Newer MPI approaches exploit a doppler-like effect from the magnetic nanoparticles to measure blood flow velocity [121], which can minimize certain imaging artifacts in MPI. ...
Magnetic particle imaging (MPI) is a new tracer-based imaging modality that is useful in diagnosing various pathophysiology related to the vascular system and for sensitive tracking of cytotherapies. MPI uses nonradioactive and easily assimilated nanometer-sized iron oxide particles as tracers. MPI images the nonlinear Langevin behavior of the iron oxide particles and has allowed for the sensitive detection of iron oxide-labeled therapeutic cells in the body. This review will provide an overview of MPI technology, the tracer, and its use in vascular imaging and cytotherapies using molecular targets.
... Depth attenuation is a challenge for many imaging methods, including optical, ultrasound, and nuclear medicine. MPI's unique physics makes it an ideal tracer imaging method with applications in angiography, cell tracking, and perfusion imaging [7]- [17]. ...
Magnetic Particle Imaging (MPI) is a noninvasive imaging modality that exploits the saturation properties of superparamagnetic iron oxide particles (SPIOs). A major thrust of MPI research aims to sharpen the magnetic resolution of biocompatible SPIOs, which will be crucial for affordable and safe clinical translation. We recently reported on a new class of MPI tracers ---called superferromagnetic iron oxide nanoparticles (SFMIOs) --- which offer much sharper magnetic saturation curves. SFMIOs experimentally demonstrate 10-fold improvement in both resolution and sensitivity. However, superferromagnetism is a relatively unexplored branch of physics and the nanoscale physics and dynamics of SFMIOs remain a mystery. Here we show experimentally that chaining of SPIOs can explain SFMIO's boost in SNR and resolution. We show how concentration, viscosity, transmit amplitude, and pre-polarization time can all affect SPIO chain formation and SFMIO behavior. These experiments will inform strategies on SFMIO chemical synthesis as well as SFMIO data acquisition pulse sequences.
Magnetic particle imaging (MPI) is an emerging non‐invasive tomographic technique based on the response of magnetic nanoparticles (MNPs) to oscillating drive fields at the center of a static magnetic gradient. In contrast to magnetic resonance imaging (MRI), which is driven by uniform magnetic fields and projects the anatomic information of the subjects, MPI directly tracks and quantifies MNPs in vivo without background signals. Moreover, it does not require radioactive tracers and has no limitations on imaging depth. This article first introduces the basic principles of MPI and important features of MNPs for imaging sensitivity, spatial resolution, and targeted biodistribution. The latest research aiming to optimize the performance of MPI tracers is reviewed based on their material composition, physical properties, and surface modifications. While the unique advantages of MPI have led to a series of promising biomedical applications, recent development of MPI in investigating vascular abnormalities in cardiovascular and cerebrovascular systems, and cancer are also discussed. Finally, recent progress and challenges in the clinical translation of MPI are discussed to provide possible directions for future research and development.
Objective:
Magnetic particle imaging (MPI) visualizes the spatial distribution of magnetic nanoparticles. MPI already provides excellent temporal and good spatial resolution, however, to achieve translation into clinics, further advances in the fields of sensitivity, image reconstruction and tracer performance are needed. In this work, we propose a novel concept to enhance the MPI signal and image resolution by a purely passive receive coil insert for a preclinical MPI system.
Approach:
The passive dual coil resonator (pDCR) provides frequency-selective signal enhancement. This is enabled by the adaptable resonance frequency of the pDCR network, which is galvanically isolated from the MPI system and composed of two coaxial solenoids connected via a capacitor. The pDCR aims to enhance frequency components related to high mixing orders, which are crucial to achieve high spatial resolution.
Main results:
In this study, system matrix measurements and image acquisitions of a resolution phantom are carried out to evaluate the performance of the pDCR compared to the integrated receive unit of the preclinical MPI and a dedicated rat-sized receive coil. Frequency-selective signal increase and spatial resolution enhancement are demonstrated.
Significance:
Common dedicated receive coils come along with noise-matched receive networks, which makes them costly and difficult to reproduce. The presented pDCR is a purely passive coil insert that gets along without any additional receive electronics. Therefore, it is cost-efficient, easy-to-handle and adaptable to other MPI scanners and potentially other applications providing the basis for a new breed of passive MPI receiver systems.
