Superspeed Bolus Visualization for Vascular Magnetic Particle Imaging

Vogel, Patrick; Rückert, Martin; Kampf, Thomas; Herz, Stefan; Stang, Anton; Wöckel, Lucas; Bley, Thorsten Alexander; Dutz, Silvio; Behr, Volker C.

doi:10.1109/tmi.2020.2965724

Cited by 35 publications

(23 citation statements)

References 33 publications

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“…For increasing velocities, temporal blurring will become more prominent, which might lead to an inaccuracy in bolus arrival time estimation and hence, a reduced accuracy in velocity quantification. Recently, Franke et al measured peak flow velocities up to 1.0 m/s exploiting pulsed tracer information 26 and Vogel et al showed images of boluses moving with up to 0.4 m/s in their traveling wave MPI scanner 27 .…”

Section: Discussionmentioning

confidence: 99%

“…As a result, the constraint by peak splitting is not valid anymore, and one could only observe the shifted peak. It has to be noted that the aforementioned bolus tracking techniques [22][23][24][25][26][27] use 3D FFP trajectories for image acquisitions, whereas 1D excitation is applied in the presented experiments. Since the repetition time of a 1D excitation scheme is considerably lower, according to Eq.…”

Section: Discussionmentioning

confidence: 99%

“…Due to its high time resolution with a repetition time T R of 21.5 ms resulting in 46 volumes per second 15 (which can be even higher dependent on the excitation field frequency), magnetic particle imaging is able to quantify blood flow velocities by tracking the tracer bolus in the image space [22][23][24][25][26][27] . Therefore, a series of images has to be acquired with high temporal resolution.…”

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confidence: 99%

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Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

Pantke

Mueller

Reinartz

et al. 2021

Sci Rep

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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 symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

Pantke

Mueller

Reinartz

et al. 2021

Sci Rep

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“…An integrated hybrid system combining MPI and MRI will assure spatial co-registration accuracy. A MPI/MRI Hybrid imaging system has been realized successfully, yet only used for static images and 2D phantom measurements 39,40 .…”

Section: Discussionmentioning

confidence: 99%

Ex vivo magnetic particle imaging of vascular inflammation in abdominal aortic aneurysm in a murine model

Mangarova

Brangsch

Mohtashamdolatshahi

et al. 2020

Sci Rep

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Abdominal aortic aneurysms (AAAs) are currently one of the leading causes of death in developed countries. Inflammation is crucial in the disease progression, having a substantial impact on various determinants in AAAs development. Magnetic particle imaging (MPI) is an innovative imaging modality, enabling the highly sensitive detection of magnetic nanoparticles (MNPs), suitable as surrogate marker for molecular targeting of vascular inflammation. For this study, Apolipoprotein E-deficient-mice underwent surgical implantation of osmotic minipumps with constant Angiotensin II infusion. After 3 and 4 weeks respectively, in-vivo-magnetic resonance imaging (MRI), ex-vivo-MPI and ex-vivo-magnetic particle spectroscopy (MPS) were performed. The results were validated by histological analysis, immunohistology and laser ablation-inductively coupled plasma-mass spectrometry. MR-angiography enabled the visualization of aneurysmal development and dilatation in the experimental group. A close correlation (R = 0.87) with histological area assessment was measured. Ex-vivo-MPS revealed abundant iron deposits in AAA samples and ex-vivo histopathology measurements were in good agreement (R = 0.76). Ex-vivo-MPI and MPS results correlated greatly (R = 0.99). CD68-immunohistology stain and Perls'-Prussian-Blue-stain confirmed the colocalization of macrophages and MNPs. This study demonstrates the feasibility of ex-vivo-MPI for detecting inflammation in AAA. The quantitative ability for mapping MNPs establishes MPI as a promising tool for monitoring inflammatory progression in AAA in an experimental setting. Cardiovascular diseases are currently one of the leading causes of death in the Western world. An abdominal aortic aneurysm (AAA) is defined as a weakening and dilatation of the abdominal aorta, prevailing in the infrarenal portion of the artery. The prevalence of AAA has been on the rise during the last decades as a result of demographic ageing, screening programs and improved clinical imaging techniques 1. The main risk of undetected, asymptomatic aneurysms is progressive expansion, followed by rupture, hemorrhage and death in approximately 80% of the cases 2. The development of AAA involves inflammation as a fundamental process. Chronic inflammation is characterized by the infiltration of inflammatory cell types, mainly macrophages and monocytes in the thrombus and throughout all layers of the aortic wall 3. These cells release several proteolytic enzymes such as matrix metalloproteinases, cytokines and oxidation-derived free radicals, leading to vascular smooth muscle cell apoptosis and degradation of the aortic tunica media 3. In AAA, elastolysis as a result of the

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“…MPI has shown to be a promising tool for a variety of medical application including vascular [6,7,8] and oncological applications [9]. In particular MPI shows great potential in the area of intervention imaging since one can use one tracer to visualize the vessel tree using a blood pool tracer [10,11] and at the same time track medical devices such as guide wires, catheters [12,13], and stents [14].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Magnetization Dynamics for Large Ensembles of Immobilized Magnetic Nanoparticles in Multi-dimensional Magnetic Particle Imaging

Albers,

Knopp,

Möddel

et al. 2021

Preprint

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Magnetic nanoparticles (MNPs) play an important role in biomedical applications including imaging modalities such as magnetic resonance imaging (MRI) and magnetic particle imaging (MPI). The latter one exploits the non-linear magnetization response of a large ensemble of magnetic nanoparticles to magnetic fields which allows determining the spatial distribution of the MNP concentration from measured voltage signals. The image-to-voltage mapping is linear and described by a system matrix. Currently, modeling the voltage signals of large ensembles of MNPs in an MPI environment is not yet accurately possible, especially for liquid tracers in multi-dimensional magnetic excitation fields. As an immediate consequence, the system matrix is still obtained in a time consuming calibration procedure. While the ferrofluidic case can be seen as the typical setting, more recently immobilized and potentially oriented MNPs have received considerable attention. By aligning the particles magnetic easy axis during immobilization one can encode the angle of the particle's magnetic easy axis into the magnetization response providing a sophisticated benchmark system for model-based approaches. In this work we address the modeling problem for immobilized and oriented MNPs in the context of MPI. We investigate a model-based approach where the magnetization response is simulated by a Néel rotation model for the particle's magnetic moments and the ensemble magnetization is obtained by solving a Fokker-Planck equation approach. Since the parameters of the model are a-priori unknown, we investigate different methods for performing a parameter identification and discuss two different models: One where a single function vector is used from the space spanned by the model parameters and another where a superposition of function vectors is considered. We show that our model can much more accurately reproduce the orientation dependent signal response when compared to the equilibrium model, which marks the current state-of-the-art for model-based system matrix simulations in MPI.

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Superspeed Bolus Visualization for Vascular Magnetic Particle Imaging

Cited by 35 publications

References 33 publications

Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

Ex vivo magnetic particle imaging of vascular inflammation in abdominal aortic aneurysm in a murine model

Modeling the Magnetization Dynamics for Large Ensembles of Immobilized Magnetic Nanoparticles in Multi-dimensional Magnetic Particle Imaging

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