Magnetic Particle Imaging (MPI) is an emerging imaging technique that uses magnetic nanoparticles as tracers. In order to analyze the quality of nanoparticles developed for MPI, a Magnetic Particle Spectrometer (MPS) is often employed. In this paper, we describe results for predictions of the nanoparticle harmonic spectra obtained in a MPS using three models: the first uses the Langevin function, which does not take into account finite magnetic relaxation; the second model uses the magnetization equation by Shliomis (Sh), which takes into account finite magnetic relaxation using a constant characteristic time scale; and the third model uses the magnetization equation derived by Martsenyuk, Raikher, and Shliomis (MRSh), which takes into account the effect of magnetic field magnitude on the magnetic relaxation time. We make comparisons between these models and with experiments in order to illustrate the effects of field-dependent relaxation in the MPS. The models results suggest that finite relaxation results in a significant drop in signal intensity (magnitude of individual harmonics) and in faster spectral decay. Interestingly, when field dependence of the magnetic relaxation time was taken into account, through the MRSh model, the simulations predict a significant improvement in the performance of the nanoparticles, as compared to the performance predicted by the Sh equation. The comparison between the predictions from models and experimental measurements showed excellent qualitative as well as quantitative agreement up to the 19th harmonic using the Sh and MRSh equations, highlighting the potential of ferrohydrodynamic modeling in MPI.
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http://dx.doi.org/10.1063/1.4935158 | DOI Listing |
Sci Rep
January 2025
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, J5, 68159, Mannheim, Germany.
Inflammatory processes have been implicated in the pathophysiology of depression. In human studies, inflammation has been shown to act as a critical disease modifier, promoting susceptibility to depression and modulating specific endophenotypes of depression. However, there is scant documentation of how inflammatory processes are associated with neural activity in patients with depression.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Pediatric Cardiology, Istanbul Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istanbul 34303, Turkey.
: Cardiac magnetic resonance (CMR) plays a central role in the diagnosis and follow-up of acute myocarditis (AM). In this study, we aimed to evaluate baseline and follow-up CMR findings and associated factors in children with AM. : A retrospective analysis of CMR in pediatric patients with clinical presentations suggestive of myocarditis was performed.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
We propose a non-magnetic transparent heating film based on silver nanowires (Ag-NWs) for application in spin-exchange relaxation-free (SERF) magnetic field measurement devices. To achieve ultra-high sensitivity in atomic magnetometers, the atoms within the alkali metal vapor cell must be maintained in a stable and uniform high-temperature environment. Ag-NWs, as a transparent conductive material with exceptional electrical conductivity, are well suited for this application.
View Article and Find Full Text PDFPlants (Basel)
December 2024
School of Data Science and Artificial Intelligence, Jilin Engineering Normal University, Changchun 130052, China.
The precise identification of maize kernel varieties is essential for germplasm resource management, genetic diversity conservation, and the optimization of agricultural production. To address the need for rapid and non-destructive variety identification, this study developed a novel interpretable machine learning approach that integrates low-field nuclear magnetic resonance (LF-NMR) with morphological image features through an optimized support vector machine (SVM) framework. First, LF-NMR signals were obtained from eleven maize kernel varieties, and ten key features were extracted from the transverse relaxation decay curves.
View Article and Find Full Text PDFEur J Radiol
January 2025
Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu Province 214062, China. Electronic address:
Purpose: To construct a nomogram combining Kaiser score (KS), synthetic MRI (syMRI) parameters, apparent diffusion coefficient (ADC), and clinical features to distinguish benign and malignant breast lesions better.
Methods: From December 2022 to February 2024, a retrospective cohort of 168 patients with breast lesions diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 4 by ultrasound and/or mammography was included. The research population was divided into the training set (n = 117) and the validation set (n = 51) by random sampling with a ratio of 7:3.
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