Cartilage T2 assessment at 3-T MR imaging: in vivo differentiation of normal hyaline cartilage from reparative tissue after two cartilage repair procedures--initial experience

PURPOSE: To prospectively compare cartilage T2 values after microfracture therapy (MFX) and matrix-associated autologous chondrocyte transplantation (MACT) repair procedures. MATERIALS AND METHODS: The study had institutional review board approval by the ethics committee of the Medical University of Vienna; informed consent was obtained. Twenty patients who underwent MFX or MACT (10 in each group) were enrolled. For comparability, patients of each group were matched by mean age (MFX, 40.0 years +/- 15.4 [standard deviation]; MACT, 41.0 years +/- 8.9) and postoperative interval (MFX, 28.6 months +/- 5.2; MACT, 27.4 months +/- 13.1). Magnetic resonance (MR) imaging was performed with a 3-T MR imager, and T2 maps were calculated from a multiecho spin-echo measurement. Global, as well as zonal, quantitative T2 values were calculated within the cartilage repair area and within cartilage sites determined to be morphologically normal articular cartilage. Additionally, with consideration of the zonal organization, global regions of interest were subdivided into deep and superficial areas. Differences between cartilage sites and groups were calculated by using a three-way analysis of variance. RESULTS: Quantitative T2 assessment of normal native hyaline cartilage showed similar results for all patients and a significant trend of increasing T2 values from deep to superficial zones (P < .05). In cartilage repair areas after MFX, global mean T2 was significantly reduced (P < .05), whereas after MACT, mean T2 was not reduced (P > or = .05). For zonal variation, repair tissue after MFX showed no significant trend between different depths (P > or = .05), in contrast to repair tissue after MACT, in which a significant increase from deep to superficial zones (P < .05) could be observed. CONCLUSION: Quantitative T2 mapping seems to reflect differences in repair tissues formed after two surgical cartilage repair procedures. (c) RSNA, 2008.

Efficient team actions: Outline of a theory of teams in sport

So far, social psychology in sport has preliminary focused on team cohesion, and many studies and meta analyses tried to demonstrate a relation between cohesiveness of a team and it's performance. How a team really co-operates and how the individual actions are integrated towards a team action is a question that has received relatively little attention in research. This may, at least in part, be due to a lack of a theoretical framework for collective actions, a dearth that has only recently begun to challenge sport psychologists. In this presentation a framework for a comprehensive theory of teams in sport is outlined and its potential to integrate the following presentations is put up for discussion. Based on a model developed by von Cranach, Ochsenbein and Valach (1986), teams are information processing organisms, and team actions need to be investigated on two levels: the individual team member and the group as an entity. Elements to be considered are the task, the social structure, the information processing structure and the execution structure. Obviously, different task require different social structures, communication and co-ordination. From a cognitivist point of view, internal representations (or mental models) guide the behaviour mainly in situations requiring quick reactions and adaptations, were deliberate or contingency planning are difficult. In sport teams, the collective representation contains the elements of the team situation, that is team task and team members, and of the team processes, that is communication and co-operation. Different meta-perspectives may be distinguished and bear a potential to explain the actions of efficient teams. Cranach, M. von, Ochsenbein, G., & Valach, L. (1986).The group as a self-active system: Outline of a theory of group action. European Journal of Social Psychology, 16, 193-229.

Foundations of stochastic geometry and theory of random sets

The first section of this chapter starts with the Buffon problem, which is one of the oldest in stochastic geometry, and then continues with the definition of measures on the space of lines. The second section defines random closed sets and related measurability issues, explains how to characterize distributions of random closed sets by means of capacity functionals and introduces the concept of a selection. Based on this concept, the third section starts with the definition of the expectation and proves its convexifying effect that is related to the Lyapunov theorem for ranges of vector-valued measures. Finally, the strong law of large numbers for Minkowski sums of random sets is proved and the corresponding limit theorem is formulated. The chapter is concluded by a discussion of the union-scheme for random closed sets and a characterization of the corresponding stable laws.

Voter Participation in the 1998 Bundestag Elections: A Theoretical Modification and Empirical Application of Downs’ Theory of Voter Participation

This article seeks to contribute to the illumination of the so-called 'paradox of voting' using the German Bundestag elections of 1998 as an empirical case. Downs' model of voter participation will be extended to include elements of the theory of subjective expected utility (SEU). This will allow a theoretical and empirical exploration of the crucial mechanisms of individual voters' decisions to participate, or abstain from voting, in the German general election of 1998. It will be argued that the infinitely low probability of an individual citizen's vote to decide the election outcome will not necessarily reduce the probability of electoral participation. The empirical analysis is largely based on data from the ALLBUS 1998. It confirms the predictions derived from SEU theory. The voters' expected benefits and their subjective expectation to be able to influence government policy by voting are the crucial mechanisms to explain participation. By contrast, the explanatory contribution of perceived information and opportunity costs is low.