Background and objective In-vivo MRI-guided drug delivery concept is a personalized technique towards cancer treatment. A major bottleneck of this method, is the weak magnetic response of nanoparticles. A crucial improvement is the usage of paramagnetic nanoparticles aggregates since they can easier manipulated in human arteries than isolated particles. However its significance, not a comprehensive study to estimate the mean length and time to aggregate exists. Methods The present detailed numerical study includes all major discrete and continues forces and moments of the nanoscale in a global model. The effort is given in summarizing the effects of particle diameter and concentration, and magnetic field magnitude to comprehensive relations. Therefore, several cases with nanoparticles having various diameters and concentrations are simulated as magnetic field increases. Results It is found that aggregations with maximum length equal to 2000nm can be formed. In addition, the increase of the concentration leads to a decrease in the amount of the isolated particles. Consequently, 33% of the particles are isolated for the concentration of 2.25mg/ml while 13% for the concentration of 10mg/ml. Moreover, the increase of the permanent magnetic field and diameter of particles gives rise to an asymptotic behavior in the number of isolated particles. Furthermore, the mean length of aggregates scales linear with diameter and magnetic field, however, concentration increase results in a weaker effect. The larger aggregation that is formed is composed by 21 particles. Smaller time is needed for the completion of the aggregation process with larger particles. Additionally, the increase of the magnitude of the magnetic field leads to a decrease in the aggregation time process. Therefore, 8.5ms are needed for the completion of the aggregation process for particles of 100nm at B=0.1T while 7ms at B=0.9T. Surprisedly, the mean time to aggregate is of the same order as in microparticles, although, with an opposite trend. Conclusions In this study, the evolution of the mean length of aggregations as well as the completion time of the aggregation process in the nano and micro range is evaluated. The present results could be useful to improve the magnetic nanoparticles assisted drug delivery method in order to minimize the side effects from the convectional cancer treatments like radiation and chemotherapy.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.cmpb.2020.105778 | DOI Listing |
Background: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and validate an explainable machine learning model to evaluate overall health status in patients with comorbid CHD and depression.
View Article and Find Full Text PDFJ Magn Reson Imaging
January 2025
Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, China.
Background: Multifrequency MR elastography (mMRE) enables noninvasive quantification of renal stiffness in patients with chronic kidney disease (CKD). Manual segmentation of the kidneys on mMRE is time-consuming and prone to increased interobserver variability.
Purpose: To evaluate the performance of mMRE combined with automatic segmentation in assessing CKD severity.
Chem Asian J
January 2025
University of Macau, Institute of Applied Physics and Materials Engineering, MACAO.
In recent years, carbon dots (CDs) with fluorescence imaging function have been widely used in biomedicine, electronic manufacturing and environmental monitoring. However, monochromatic fluorescence is often limited by the application environment and loses its effectiveness. Here, we carefully designed white fluorescent CDs (WF-CDs) by solvothermal method, which is used for fluorescence imaging applications under different environmental conditions.
View Article and Find Full Text PDFRadiology
January 2025
From the Department of Radiology, University of Washington, UW Medical Center-Montlake, Seattle, Wash (D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC), University of Washington, Seattle, Wash (D.M.); Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (M.v.A.); Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (M.H.); Department of Radiology, Mayo Clinic, Rochester, Minn (T.L., E.E.W.); Departments of Cardiology and Radiology, Royal Brompton Hospital, London, United Kingdom (E.D.N.); School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom (E.D.N.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (B.D.A.); Department of Radiology, University of Cagliari, Cagliari, Italy (L.S.); Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1 Postbus 30 001, 9700 RB Groningen, the Netherlands (R.V.); Department of Medical Imaging, University Medical Imaging Toronto, University of Toronto, Toronto, Ontario, Canada (K.H.); and Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.H.).
Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through image acquisition, reconstruction, and interpretation, extending to prognostication and reporting. Despite the development of many cardiac imaging AI algorithms, AI tools are at various stages of development and face challenges for clinical implementation. This scientific statement, endorsed by several societies in the field, provides an overview of the current landscape and challenges of AI applications in cardiac CT and MRI.
View Article and Find Full Text PDFDalton Trans
January 2025
Institut für Anorganische und Analytische Chemie, Universität Münster, Corrensstraße 30, 48149 Münster, Germany.
The cadmium-rich intermetallic compounds RhCd ( = Ca, Sr, Y, La-Nd, Sm-Lu) were synthesized from the elements in sealed tantalum tubes. The elements were reacted in an induction furnace and the samples were post-annealed to increase phase purity and crystallinity. The RhCd phases crystallize with the cubic CeCrAl type structure, space group 3̄.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!