Publications by authors named "Laura R Croft"

Purpose: Magnetic particle imaging (MPI) is a new imaging technology that directly detects superparamagnetic iron oxide nanoparticles. The technique has potential medical applications in angiography, cell tracking, and cancer detection. In this paper, the authors explore how nanoparticle relaxation affects image resolution.

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Magnetic particle imaging (MPI) shows promise for medical imaging, particularly in angiography of patients with chronic kidney disease. As the first biomedical imaging technique that truly depends on nanoscale materials properties, MPI requires highly optimized magnetic nanoparticle tracers to generate quality images. Until now, researchers have relied on tracers optimized for MRI T2(∗) -weighted imaging that are sub-optimal for MPI.

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Magnetic Particle Imaging (MPI) is a new tracer imaging modality that is gaining significant interest from NMR and MRI researchers. While the physics of MPI differ substantially from MRI, it employs hardware and imaging concepts that are familiar to MRI researchers, such as magnetic excitation and detection, pulse sequences, and relaxation effects. Furthermore, MPI employs the same superparamagnetic iron oxide (SPIO) contrast agents that are sometimes used for MR angiography and are often used for MRI cell tracking studies.

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One quarter of all iodinated contrast X-ray clinical imaging studies are now performed on Chronic Kidney Disease (CKD) patients. Unfortunately, the iodine contrast agent used in X-ray is often toxic to CKD patients' weak kidneys, leading to significant morbidity and mortality. Hence, we are pioneering a new medical imaging method, called Magnetic Particle Imaging (MPI), to replace X-ray and CT iodinated angiography, especially for CKD patients.

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Magnetic particle imaging (MPI) is a new imaging modality that noninvasively images the spatial distribution of superparamagnetic iron oxide nanoparticles (SPIOs). MPI has demonstrated high contrast and zero attenuation with depth, and MPI promises superior safety compared to current angiography methods, X-ray, computed tomography, and magnetic resonance imaging angiography. Nanoparticle relaxation can delay the SPIO magnetization, and in this work we investigate the open problem of the role relaxation plays in MPI scanning and its effect on the image.

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Background: The three-dimensional saddle shape of the mitral annulus is well characterized in animals and humans, but the impact of annular nonplanarity on valve function or mechanics is poorly understood. In this study, we investigated the impact of the saddle shaped mitral annulus on the mechanics of the P2 segment of the posterior mitral leaflet.

Methods: Eight porcine mitral valves (n = 8) were studied in an in-vitro left heart simulator with an adjustable annulus that could be changed from flat to different degrees of saddle.

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Objective: Leaflet prolapse resulting from acute chordal rupture is one presentation of fibroelastic deficiency that is associated with minimal leaflet changes in the prolapsing segment. Minimizing resection and preserving leaflet tissue may be an optimal surgical strategy. We examined the importance of the leaflet preservation concept by comparing resective and nonresective surgical procedures in practice today.

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Background: The edge-to-edge repair to correct mitral regurgitation (MR) has shown substandard results in cases of ischemic MR or dilated cardiomyopathy.

Methods: Ten porcine mitral valves were investigated in a left heart simulator (120 mm Hg, 5 L/min). Pathologic conditions of a dilated ventricle were simulated by using an annular model capable of three levels of dilation (normal, 56%, and 120%) and by displacing papillary muscles (PMs) 10 mm in the apical, lateral, and posterior directions.

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Background: Although edge-to-edge repair is an established adjunctive procedure, there is still debate on its long-term durability and efficacy.

Methods: Fifteen porcine mitral valves were studied in a physiologic left heart simulator with a variable size annulus (dilated = 8.22 cm2, normal = 6.

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