Initial clinical experience with oral manganese (CMC-001) for liver MR imaging.

Contains fulltext : 53230.pdf (publisher's version ) (Closed access)Recently, a new oral liver-specific manganese-based MR agent (CMC-001) has been introduced. This contrast medium is delivered to the liver in high concentrations in the portal vein and very low doses in the hepatic artery, as only small amounts of manganese enter the general circulation. It is taken up by the hepatocytes and excreted in the bile. Our initial experience with the new MR contrast medium in a variety of patients is reported. A total of 20 patients (11 males and 9 females) were studied with MR imaging 2 h after oral ingestion of the contrast agent. Sixteen patients were referred for evaluation of focal liver lesion(s), whereas in the remaining four patients, evaluation of the biliary tract was requested. In the 17 patients without biliary obstruction, there was an increased signal intensity of the liver parenchyma, whereas in the three patients with biliary obstruction, the uptake was delayed. There was excellent visualization of the biliary system on the T1-weighted images in the 16 patients without biliary obstruction referred for evaluation of a focal liver lesion. In seven patients, the uptake was patchy. In patients with focal liver lesions or biliary tract diseases, it is possible to increase the signal intensity of the liver parenchyma after the oral intake of CMC-001. In patients without biliary tract obstruction, the biliary system is easily visualized. Oral manganese seems to be useful in hepatobiliary MRI. Further research is strongly warranted

Towards Verifying Parallel Algorithms and Programs using Coloured Petri Nets

Abstract. Coloured Petri nets have proved to be a useful formalism for modeling distributed algorithms, i.e., algorithms where nodes communicate via message passing. Here we describe an approach for modeling parallel algorithms and programs, i.e., algorithms and programs where processes communicate via shared memory. The model is verified for correctness, here to prove absence of mutual exclusion violations and to find dead- and live-locks. The approach can be used in a model-driven development approach, where code is generated from a model, in a modelextraction approach, where a model is extracted from running code, or using a combination of the two, supporting extracting a model from an abstract description and generation of correct implementation code. We illustrate our idea by applying the technique to a parallel implementation of explicit state-space exploration.

Neural substrates of classically conditioned fear-generalization in humans: a parametric fMRI study

Recent research on classical fear-conditioning in the anxiety disorders has identified overgeneralization of conditioned fear as an important conditioning correlate of anxiety pathology. Unfortunately, only one human neuroimaging study of classically conditioned fear generalization has been conducted, and the neural substrates of this clinically germane process remain largely unknown. The current generalization study employs a clinically validated generalization gradient paradigm, modified for the fMRI environment, to identify neural substrates of classically conditioned generalization that may function aberrantly in clinical anxiety. Stimuli include five rings of gradually increasing size with extreme sizes serving as cues of conditioned danger (CS+) and safety (CS−). The three intermediately sized rings serve as generalization stimuli (GSs) and create a continuum-of-size from CS+ to CS−. Results demonstrate ‘positive’ generalization gradients, reflected by declines in responding as the presented stimulus differentiates from CS+, in bilateral anterior insula, dorsomedial prefrontal cortex, and bilateral inferior parietal lobule. Conversely, ‘negative’ gradients, reflected by inclines in responding as the presented stimulus differentiates from CS+ were instantiated in bilateral ventral hippocampus, ventromedial prefrontal cortex and precuneus cortex. These results as well as those from connectivity analyses are discussed in relation to a working neurobiology of conditioned generalization centered on the hippocampus