University of Graz

About: University of Graz is a education organization based out in Graz, Steiermark, Austria. It is known for research contribution in the topics: Population & Quantum chromodynamics. The organization has 17934 authors who have published 37489 publications receiving 1110980 citations. The organization is also known as: Carolo Franciscea Graecensis & Karl Franzens Universität.

Histopathologic analysis of foci of signal loss on gradient-echo T2*-weighted MR images in patients with spontaneous intracerebral hemorrhage: evidence of microangiopathy-related microbleeds

Abstract: BACKGROUND AND PURPOSE: Patients with spontaneous intracerebral hemorrhage (ICH) frequently have small areas of signal loss on gradient-echo T2*-weighted MR images, which have been suggested to represent remnants of previous microbleeds. Our aim was to provide histopathologic support for this assumption and to clarify whether the presence and location of microbleeds were associated with microangiopathy. METHODS: We performed MR imaging and correlative histopathologic examination in 11 formalin-fixed brains of patients who had died of an ICH (age range, 45–90 years). RESULTS: Focal areas of signal loss on MR images were noted in seven brains. They were seen in a corticosubcortical location in six brains, in the basal ganglia/thalami in five, and infratentorially in three specimens. Histopathologic examination showed focal hemosiderin deposition in 21 of 34 areas of MR signal loss. No other corresponding abnormalities were found; however, hemosiderin deposits were noted without MR signal changes in two brains. All specimens with MR foci of signal loss showed moderate to severe fibrohyalinosis, and there was additional evidence of amyloid angiopathy in two of those brains. CONCLUSION: Small areas of signal loss on gradient echo T2*-weighted images indicate previous extravasation of blood and are related to bleeding-prone microangiopathy of different origins.

Is It Really Robust

Abstract: Empirical evidence to the robustness of the analysis of variance (ANOVA) concerning violation of the normality assumption is presented by means of Monte Carlo methods. High-quality samples underlying normally, rectangularly, and exponentially distributed basic populations are created by drawing samples which consist of random numbers from respective generators, checking their goodness of fit, and allowing only the best 10% to take part in the investigation. A one-way fixed-effect design with three groups of 25 values each is chosen. Effect-sizes are implemented in the samples and varied over a broad range. Comparing the outcomes of the ANOVA calculations for the different types of distributions, gives reason to regard the ANOVA as robust. Both, the empirical type I error α and the empirical type II error β remain constant under violation. Moreover, regression analysis identifies the factor “type of distribution” as not significant in explanation of the ANOVA results.