Semi-automated generation of individual computational models of the human head and torso from MR images.

PURPOSE: Simulating the interaction of the human body with electromagnetic fields is an active field of research. Individualized models are increasingly being used, as anatomical differences affect the simulation results. We introduce a processing pipeline for creating individual surface-based models of the human head and torso for application in simulation software based on unstructured grids. The pipeline is designed for easy applicability and is publicly released on figshare. METHODS: The pipeline covers image acquisition, segmentation, generation of segmentation masks, and surface mesh generation of the single, external boundary of each structure of interest. Two gradient-echo sequences are used for image acquisition. Structures of the head and body are segmented using several atlas-based approaches. They consist of bone/skull, subarachnoid cerebrospinal fluid, gray matter, white matter, spinal cord, lungs, the sinuses of the skull, and a combined class of all other structures including skin. After minor manual preparation, segmentation images are processed to segmentation masks, which are binarized images per segmented structure free of misclassified voxels and without an internal boundary. The proposed workflow is applied to 2 healthy subjects. RESULTS: Individual differences of the subjects are well represented. The models are proven to be suitable for simulation of the RF electromagnetic field distribution. CONCLUSION: Image segmentation, creation of segmentation masks, and surface mesh generation are highly automated. Manual interventions remain for preparing the segmentation images prior to segmentation mask generation. The generated surfaces exhibit a single boundary per structure and are suitable inputs for simulation software.

Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia.

BACKGROUND: The approach to apply multivariate pattern analyses based on neuro imaging data for outcome prediction holds out the prospect to improve therapeutic decisions in mental disorders. Patients suffering from panic disorder with agoraphobia (PD/AG) often exhibit an increased perception of bodily sensations. The purpose of this investigation was to assess whether multivariate classification applied to a functional magnetic resonance imaging (fMRI) interoception paradigm can predict individual responses to cognitive behavioral therapy (CBT) in PD/AG. METHODS: This analysis is based on pretreatment fMRI data during an interoceptive challenge from a multicenter trial of the German PANIC-NET. Patients with DSM-IV PD/AG were dichotomized as responders (n = 30) or non-responders (n = 29) based on the primary outcome (Hamilton Anxiety Scale Reduction ≥50%) after 6 weeks of CBT (2 h/week). fMRI parametric maps were used as features for response classification with linear support vector machines (SVM) with or without automated feature selection. Predictive accuracies were assessed using cross validation and permutation testing. The influence of methodological parameters and the predictive ability for specific interoception-related symptom reduction were further evaluated. RESULTS: SVM did not reach sufficient overall predictive accuracies (38.0-54.2%) for anxiety reduction in the primary outcome. In the exploratory analyses, better accuracies (66.7%) were achieved for predicting interoception-specific symptom relief as an alternative outcome domain. Subtle information regarding this alternative response criterion but not the primary outcome was revealed by post hoc univariate comparisons. CONCLUSION: In contrast to reports on other neurofunctional probes, SVM based on an interoception paradigm was not able to reliably predict individual response to CBT. Results speak against the clinical applicability of this technique.

Functional implications of novel human acid sphingomyelinase splice variants.

BACKGROUND: Acid sphingomyelinase (ASM) hydrolyses sphingomyelin and generates the lipid messenger ceramide, which mediates a variety of stress-related cellular processes. The pathological effects of dysregulated ASM activity are evident in several human diseases and indicate an important functional role for ASM regulation. We investigated alternative splicing as a possible mechanism for regulating cellular ASM activity. METHODOLOGY/PRINCIPAL FINDINGS: We identified three novel ASM splice variants in human cells, termed ASM-5, -6 and -7, which lack portions of the catalytic- and/or carboxy-terminal domains in comparison to full-length ASM-1. Differential expression patterns in primary blood cells indicated that ASM splicing might be subject to regulatory processes. The newly identified ASM splice variants were catalytically inactive in biochemical in vitro assays, but they decreased the relative cellular ceramide content in overexpression studies and exerted a dominant-negative effect on ASM activity in physiological cell models. CONCLUSIONS/SIGNIFICANCE: These findings indicate that alternative splicing of ASM is of functional significance for the cellular stress response, possibly representing a mechanism for maintaining constant levels of cellular ASM enzyme activity.