19 resultados para Spin-orbit resonance
Resumo:
Diseases of paranasal sinuses and nasal passages in horses can be a diagnostic challenge because of the complex anatomy of the head and limitations of many diagnostic modalities. Our hypothesis was that magnetic resonance (MR) imaging would provide excellent anatomical detail and soft tissue resolution, and would be accurate in the diagnosis of diseases of the paranasal sinuses and nasal passages in horses. Fourteen horses were imaged. Inclusion criteria were lesions located to the sinuses or nasal passages that underwent MR imaging and subsequent surgical intervention and/or histopathologic examination. A low field, 0.3 tesla open magnet was used. Sequences in the standard protocol were fast spin echo T2 sagittal and transverse, spin echo T1 transverse, short-tau inversion recovery (STIR) dorsal, gradient echo 3D T1 MPR dorsal (plain and contrast enhanced), spin echo T1 fatsat (contrast enhanced). Mean scan time to complete the examination was 53 min (range 39-99 min). Lesions identified were primary or secondary sinusitis (six horses), paranasal sinus cyst (four horses), progressive ethmoid hematoma (two horses), and neoplasia (two horses). The most useful sequences were fast spin echo T2 transverse and sagittal, STIR dorsal and FE3D MPR (survey and contrast enhanced). Fluid accumulation, mucosal thickening, presence of encapsulated contents, bone deformation, and thickening were common findings observed in MR imaging. In selected horses, magnetic resonance imaging is a useful tool in diagnosing lesions of the paranasal sinuses and nasal passages.
Resumo:
The population of space debris increased drastically during the last years. These objects have become a great threat for active satellites. Because the relative velocities between space debris and satellites are high, space debris objects may destroy active satellites through collisions. Furthermore, collisions involving massive objects produce large number of fragments leading to significant growth of the space debris population. The long term evolution of the debris population is essentially driven by so-called catastrophic collisions. An effective remediation measure in order to stabilize the population in Low Earth Orbit (LEO) is therefore the removal of large, massive space debris. To remove these objects, not only precise orbits, but also more detailed information about their attitude states will be required. One important property of an object targeted for removal is its spin period, spin axis orientation and their change over time. Rotating objects will produce periodic brightness variations with frequencies which are related to the spin periods. Such a brightness variation over time is called a light curve. Collecting, but also processing light curves is challenging due to several reasons. Light curves may be undersampled, low frequency components due to phase angle and atmospheric extinction changes may be present, and beat frequencies may occur when the rotation period is close to a multiple of the sampling period. Depending on the method which is used to extract the frequencies, also method-specific properties have to be taken into account. The astronomical Institute of the University of Bern (AIUB) light curve database will be introduced, which contains more than 1,300 light curves acquired over more than seven years. We will discuss properties and reliability of different time series analysis methods tested and currently used by AIUB for the light curve processing. Extracted frequencies and reconstructed phases for some interesting targets, e.g. GLONASS satellites, for which also SLR data were available for the period confirmation, will be presented. Finally we will present the reconstructed phase and its evolution over time of a High-Area-to-Mass-Ratio (HAMR) object, which AIUB observed for several years.
Resumo:
Purpose To investigate whether nonhemodynamic resonant saturation effects can be detected in patients with focal epilepsy by using a phase-cycled stimulus-induced rotary saturation (PC-SIRS) approach with spin-lock (SL) preparation and whether they colocalize with the seizure onset zone and surface interictal epileptiform discharges (IED). Materials and Methods The study was approved by the local ethics committee, and all subjects gave written informed consent. Eight patients with focal epilepsy undergoing presurgical surface and intracranial electroencephalography (EEG) underwent magnetic resonance (MR) imaging at 3 T with a whole-brain PC-SIRS imaging sequence with alternating SL-on and SL-off and two-dimensional echo-planar readout. The power of the SL radiofrequency pulse was set to 120 Hz to sensitize the sequence to high gamma oscillations present in epileptogenic tissue. Phase cycling was applied to capture distributed current orientations. Voxel-wise subtraction of SL-off from SL-on images enabled the separation of T2* effects from rotary saturation effects. The topography of PC-SIRS effects was compared with the seizure onset zone at intracranial EEG and with surface IED-related potentials. Bayesian statistics were used to test whether prior PC-SIRS information could improve IED source reconstruction. Results Nonhemodynamic resonant saturation effects ipsilateral to the seizure onset zone were detected in six of eight patients (concordance rate, 0.75; 95% confidence interval: 0.40, 0.94) by means of the PC-SIRS technique. They were concordant with IED surface negativity in seven of eight patients (0.88; 95% confidence interval: 0.51, 1.00). Including PC-SIRS as prior information improved the evidence of the standard EEG source models compared with the use of uninformed reconstructions (exceedance probability, 0.77 vs 0.12; Wilcoxon test of model evidence, P < .05). Nonhemodynamic resonant saturation effects resolved in patients with favorable postsurgical outcomes, but persisted in patients with postsurgical seizure recurrence. Conclusion Nonhemodynamic resonant saturation effects are detectable during interictal periods with the PC-SIRS approach in patients with epilepsy. The method may be useful for MR imaging-based detection of neuronal currents in a clinical environment. (©) RSNA, 2016 Online supplemental material is available for this article.