Virtual reality ultrasound imaging of the normal and abnormal fetal central nervous system

OBJECTIVES: In fetal ultrasound imaging, teaching and experience are of paramount importance to improve prenatal detection rates of fetal abnormalities. Yet both aspects depend on exposure to normal and, in particular, abnormal 'specimens'. We aimed to generate a number of simple virtual reality (VR) objects of the fetal central nervous system for use as educational tools. METHODS: We applied a recently proposed algorithm for the generation of fetal VR object movies to the normal and abnormal fetal brain and spine. Interactive VR object movies were generated from ultrasound volume data from normal fetuses and fetuses with typical brain or spine anomalies. Pathognomonic still images from all object movies were selected and annotated to enable recognition of these features in the object movies. RESULTS: Forty-six virtual reality object movies from 22 fetuses (two with normal and 20 with abnormal brains) were generated in an interactive display format (QuickTime) and key images were annotated. The resulting .mov files are available for download from the website of this journal. CONCLUSIONS: VR object movies can be generated from educational ultrasound volume datasets, and may prove useful for teaching and learning normal and abnormal fetal anatomy.

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.

The foundations of computer assisted surgery

Using navigation systems in general orthopaedic surgery and, in particular, knee replacement is becoming more and more accepted. This paper describes the basic technological concepts of modern computer assisted surgical systems. It explains the variation in currently available systems and outlines research activities that will potentially influence future products. In general, each navigation system is defined by three components: (1) the therapeutic object is the anatomical structure that is operated on using the navigation system, (2) the virtual object represents an image of the therapeutic object, with radiological images or computer generated models potentially being used, and (3) last but not least, the navigator acquires the spatial position and orientation of instruments and anatomy thus providing the necessary data to replay surgical action in real-time on the navigation system's screen.

Flow-Centric, Back-In-Time Debugging

Conventional debugging tools present developers with means to explore the run-time context in which an error has occurred. In many cases this is enough to help the developer discover the faulty source code and correct it. However, rather often errors occur due to code that has executed in the past, leaving certain objects in an inconsistent state. The actual run-time error only occurs when these inconsistent objects are used later in the program. So-called back-in-time debuggers help developers step back through earlier states of the program and explore execution contexts not available to conventional debuggers. Nevertheless, even back-in-time debuggers do not help answer the question, ``Where did this object come from?'' The Object-Flow Virtual Machine, which we have proposed in previous work, tracks the flow of objects to answer precisely such questions, but this VM does not provide dedicated debugging support to explore faulty programs. In this paper we present a novel debugger, called Compass, to navigate between conventional run-time stack-oriented control flow views and object flows. Compass enables a developer to effectively navigate from an object contributing to an error back-in-time through all the code that has touched the object. We present the design and implementation of Compass, and we demonstrate how flow-centric, back-in-time debugging can be used to effectively locate the source of hard-to-find bugs.

Disrupting frontal eye-field activity impairs memory recall

A large body of research demonstrated that participants preferably look back to the encoding location when retrieving visual information from memory. However, the role of this 'looking back to nothing' is still debated. The goal of the present study was to extend this line of research by examining whether an important area in the cortical representation of the oculomotor system, the frontal eye field (FEF), is involved in memory retrieval. To interfere with the activity of the FEF, we used inhibitory continuous theta burst stimulation (cTBS). Before stimulation was applied, participants encoded a complex scene and performed a short-term (immediately after encoding) or long-term (after 24 h) recall task, just after cTBS over the right FEF or sham stimulation. cTBS did not affect overall performance, but stimulation and statement type (object vs. location) interacted. cTBS over the right FEF tended to impair object recall sensitivity, whereas there was no effect on location recall sensitivity. These findings suggest that the FEF is involved in retrieving object information from scene memory, supporting the hypothesis that the oculomotor system contributes to memory recall.

Bone images from dual-energy subtraction chest radiography in the detection of rib fractures

To assess the sensitivity and image quality of chest radiography (CXR) with or without dual-energy subtracted (ES) bone images in the detection of rib fractures.

Determination of Pelvic Orientation from Ultrasound Images Using Patch-SSMs and a Hierarchical Speed of Sound Compensation Strategy

In the field of computer assisted orthopedic surgery (CAOS) the anterior pelvic plane (APP) is a common concept to determine the pelvic orientation by digitizing distinct pelvic landmarks. As percutaneous palpation is - especially for obese patients - known to be error-prone, B-mode ultrasound (US) imaging could provide an alternative means. Several concepts of using ultrasound imaging to determine the APP landmarks have been introduced. In this paper we present a novel technique, which uses local patch statistical shape models (SSMs) and a hierarchical speed of sound compensation strategy for an accurate determination of the APP. These patches are independently matched and instantiated with respect to associated point clouds derived from the acquired ultrasound images. Potential inaccuracies due to the assumption of a constant speed of sound are compensated by an extended reconstruction scheme. We validated our method with in-vitro studies using a plastic bone covered with a soft-tissue simulation phantom and with a preliminary cadaver trial.

Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.