Background-Interpretation of dobutamine stress echocardiography (DSE) is subjective and strongly dependent on the skills of the reader. Strain-rate imaging (SRI) by tissue Doppler may objectively analyze regional myocardial function. This study investigated SRI markers of stress-induced ischemia and analyzed their applicability in a clinical setting. Methods and Results-DSE was performed in 44 patients with known or suspected coronary artery disease. Simultaneous perfusion scintigraphy served as a "gold standard" to define regional ischemia. All patients underwent coronary angiography. Segmental strain and strain rate were analyzed at all stress levels by measuring amplitude and timing of deformation and visual curved M-mode analysis. Results were compared with conventional stress echo reading. In nonischemic segments, peak systolic strain rate increased significantly with dobutamine stress (Ϫ1.6Ϯ0.6 s Ϫ1 versus Ϫ3.4Ϯ1.4 s

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Summary:Ictal pleasant feelings are a rare sign of focal epilepsies. The most popular description was performed by Dostojevskij, who reported an aura by Myshken in one of his books. No convincing evidence has been published concerning the cerebral localization of ictal happiness. In this study, the findings of 11 patients with ictal pleasant feelings are described. In eight patients, the origin of the focal epileptic activity was found in the temporal lobe (most often temporal inferior basal); in three patients, frontal or parietal lobe in addition to temporal lobe involvement was found. According to our findings ictal happiness is a localizing sign pointing to the ictal involvement of temporal mesiobasal areas. Lateralization to the right temporal lobe was found in seven and to the left temporal lobe in four patients.

Multivariate image analysis has shown potential for classification between Alzheimer's disease (AD) patients and healthy controls with a high-diagnostic performance. As image analysis of positron emission tomography (PET) and single photon emission computed tomography (SPECT) data critically depends on appropriate data preprocessing, the focus of this work is to investigate the impact of data preprocessing on the outcome of the analysis, and to identify an optimal data preprocessing method. In this work, technetium-99methylcysteinatedimer ( 99m Tc-ECD) SPECT data sets of 28 AD patients and 28 asymptomatic controls were used for the analysis. For a series of different data preprocessing methods, which includes methods for spatial normalization, smoothing, and intensity normalization, multivariate image analysis based on principal component analysis (PCA) and Fisher discriminant analysis (FDA) was applied. Bootstrap resampling was used to investigate the robustness of the analysis and the classification accuracy, depending on the data preprocessing method. Depending on the combination of preprocessing methods, significant differences regarding the classification accuracy were observed. For 99m Tc-ECD SPECT data, the optimal data preprocessing method in terms of robustness and classification accuracy is based on affine registration, smoothing with a Gaussian of 12 mm full width half maximum, and intensity normalization based on the 25% brightest voxels within the whole-brain region.