Temperature dependence of postmortem MR quantification for soft tissue discrimination.

OBJECTIVES To investigate and correct the temperature dependence of postmortem MR quantification used for soft tissue characterization and differentiation in thoraco-abdominal organs. MATERIAL AND METHODS Thirty-five postmortem short axis cardiac 3-T MR examinations were quantified using a quantification sequence. Liver, spleen, left ventricular myocardium, pectoralis muscle and subcutaneous fat were analysed in cardiac short axis images to obtain mean T1, T2 and PD tissue values. The core body temperature was measured using a rectally inserted thermometer. The tissue-specific quantitative values were related to the body core temperature. Equations to correct for temperature differences were generated. RESULTS In a 3D plot comprising the combined data of T1, T2 and PD, different organs/tissues could be well differentiated from each other. The quantitative values were influenced by the temperature. T1 in particular exhibited strong temperature dependence. The correction of quantitative values to a temperature of 37 °C resulted in better tissue discrimination. CONCLUSION Postmortem MR quantification is feasible for soft tissue discrimination and characterization of thoraco-abdominal organs. This provides a base for computer-aided diagnosis and detection of tissue lesions. The temperature dependence of the T1 values challenges postmortem MR quantification. Equations to correct for the temperature dependence are provided. KEY POINTS • Postmortem MR quantification is feasible for soft tissue discrimination and characterization • Temperature dependence of the T1 values challenges the MR quantification approach • The results provide the basis for computer-aided postmortem MRI diagnosis • Diagnostic criteria may also be applied for living patients.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

Deficit actual tool use in schizophrenia is linked to structural alterations in key regions of planning and executing of tool use and connecting fibers

Introduction: Schizophrenia patients frequently suffer from complex motor abnormalities including fine and gross motor disturbances, abnormal involuntary movements, neurological soft signs and parkinsonism. These symptoms occur early in the course of the disease, continue in chronic patients and may deteriorate with antipsychotic medication. Furthermore gesture performance is impaired in patients, including the pantomime of tool use. Whether schizophrenia patients would show difficulties of actual tool use has not yet been investigated. Human tool use is complex and relies on a network of distinct and distant brain areas. We therefore aim to test if schizophrenia patients had difficulties in tool use and to assess associations with structural brain imaging using voxel based morphometry (VBM) and tract based spatial statistics (TBSS). Methode: In total, 44 patients with schizophrenia (DSM-5 criteria; 59% men, mean age 38) underwent structural MR imaging and performed the Tool-Use test. The test examines the use of a scoop and a hammer in three conditions: pantomime (without the tool), demonstration (with the tool) and actual use (with a recipient object). T1-weighted images were processed using SPM8 and DTI-data using FSL TBSS routines. To assess structural alterations of impaired tool use we first compared gray matter (GM) volume in VBM and white matter (WM) integrity in TBSS data of patients with and without difficulties of actual tool use. Next we explored correlations of Tool use scores and VBM and TBSS data. Group comparisons were family wise error corrected for multiple tests. Correlations were uncorrected (p < 0.001) with a minimum cluster threshold of 17 voxels (equivalent to a map-wise false positive rate of alpha < 0.0001 using a Monte Carlo procedure). Results: Tool use was impaired in schizophrenia (43.2% pantomime, 11.6% demonstration, 11.6% use). Impairment was related to reduced GM volume and WM integrity. Whole brain analyses detected an effect in the SMA in group analysis. Correlations of tool use scores and brain structure revealed alterations in brain areas of the dorso-dorsal pathway (superior occipital gyrus, superior parietal lobule, and dorsal premotor area) and the ventro-dorsal pathways (middle occipital gyrus, inferior parietal lobule) the action network, as well as the insula and the left hippocampus. Furthermore, significant correlations within connecting fiber tracts - particularly alterations within the bilateral corona radiata superior and anterior as well as the corpus callosum -were associated with Tool use performance. Conclusions: Tool use performance was impaired in schizophrenia, which was associated with reduced GM volume in the action network. Our results are in line with reports of impaired tool use in patients with brain lesions particularly of the dorso-dorsal and ventro-dorsal stream of the action network. In addition an effect of tool use on WM integrity was shown within fiber tracts connecting regions important for planning and executing tool use. Furthermore, hippocampus is part of a brain system responsible for spatial memory and navigation.The results suggest that structural brain alterations in the common praxis network contribute to impaired tool use in schizophrenia.