A method to calculate the AC loss of superconducting power devices from the measured AC loss of a short sample is developed. In coils and cables the magnetic field varies spatially. The position dependent field vector is calculated assuming a homogeneous current distribution. From this field profile and the transport current, the local AC loss is calculated. Integration over the conductor length yields the AC loss of the device. The total AC loss of the device is split up in different components. Magnetization loss, transport current loss and the loss due to the combined action of field and current all contribute to the AC loss of the device. Because ways to reduce the AC loss depend on the loss mechanism it is important to know the relative contribution of each component. The method is demonstrated on a prototype transformer coil wound from Bi/sub 2/Sr/sub 2/Ca/sub 2/Cu/sub 3/O/sub x//Ag superconducting tape. Differences between the model assumptions and devices are pointed out. Nevertheless, within the uncertainty margins the calculated AC loss is in agreement with the measured loss of the coil.
Sentinel lymph node biopsy (SLNB) with a superparamagnetic iron oxide (SPIO) tracer was shown to be non-inferior to the standard combined technique in the SentiMAG Multicentre Trial. The MRI subprotocol of this trial aimed to develop a magnetic alternative for pre-operative lymphoscintigraphy (LS). We evaluated the feasibility of using MRI following the administration of magnetic tracer for pre-operative localization of sentinel lymph nodes (SLNs) and its potential for non-invasive identification of lymph node (LN) metastases.Patients with breast cancer scheduled to undergo SLNB were recruited for pre-operative LS, single photon emission CT (SPECT)-CT and SPIO MRI. T1 weighted turbo spin echo and T2 weighted gradient echo sequences were used before and after interstitial injection of magnetic tracer into the breast. SLNs on MRI were defined as LNs with signal drop and direct lymphatic drainage from the injection site. LNs showing inhomogeneous SPIO uptake were classified as metastatic. During surgery, a handheld magnetometer was used for SLNB. Blue or radioactive nodes were also excised. The number of SLNs and MR assessment of metastatic involvement were compared with surgical and histological outcomes.11 patients were recruited. SPIO MRI successfully identified SLNs in 10 of 11 patients vs 11 of 11 patients with LS/SPECT-CT. One patient had metastatic involvement of four LNs, and this was identified in one node on pre-operative MRI.SPIO MRI is a feasible technique for pre-operative localization of SLNs and, in combination with intraoperative use of a handheld magnetometer, provides an entirely radioisotope-free technique for SLNB. Further research is needed for the evaluation of MRI characterization of LN involvement using subcutaneous injection of magnetic tracer.This study is the first to demonstrate that an interstitially administered magnetic tracer can be used both for pre-operative imaging and intraoperative SLNB, with equal performance to imaging and localization with radioisotopes.
An engineering function to describe the AC loss of BSCCO/Ag tape conductors is developed. For a wide range of transport currents and magnetic fields (with different orientation) the loss is described with an uncertainty of 10%. The equation is based on the analytical expressions available, BSCCO/Ag tapes used in power applications at liquid nitrogen temperature are fed with an AC transport current and exposed to an AC magnetic field. The magnetic field in a device has different orientations with respect to the position of the conductor in the device. In this contribution, AC loss measurements for simultaneously applied magnetic field (with different orientation) and transport current are presented for a high quality tape conductor that is used in a transformer coil. The results are separated into a magnetic and a transport current loss component.
Spreading depolarization (SD) is an important phenomenon in stroke and migraine. However, the processes underlying the propagation of SD are still poorly understood, and an elementary model that is both physiological and quantitative is lacking. We show that, during the onset and propagation of SD, the concentration time courses of excitatory substances such as potassium and glutamate can be described with a reaction–diffusion equation. This equation contains four physiological parameters: (1) a concentration threshold for excitation; (2) a release rate; (3) a removal rate; and (4) an effective diffusion constant. Solving this equation yields expressions for the propagation velocity, concentration time courses, and the minimum stimulus that can trigger SD. This framework allows for analyzing experimental results in terms of these four parameters. The derived time courses are validated with measurements of potassium in rat brain tissue.
The clinical application of magnetic nanoparticles is a developing field with promising perspectives in treatment and diagnosis [1]. After the first applications as a contrast agent in MRI, other magnetic methods have been developed for excitation and detection of magnetic nanoparticles. For magnetic detection, the nonlinear behavior of superparamagnetic iron oxides provide excellent contrast in the linear magnetic human body. To exploit these properties, the design of magnetic nanoparticles as well as detection systems has to be optimized for clinical practice. The particles have to provide optimal sensitivity in contrast to tissue, whereas the signal-to-noise ratio and applicability of a measurement system are important for successful clinical implementation. In this contribution a setup is presented that is able to assess these both elements for sentinel lymph node mapping. Small intact biological samples, such as lymph nodes, can be measured at room temperature to characterize the magnetic nanoparticle content by differential magnetometry. Furthermore, the system can be used as a tool to analyze the magnetic properties of nanoparticles, providing insight in the quality for nonlinear particle detection.
