Detection of posttraumatic pneumothorax using electrical impedance tomography-An observer-blinded study in pigs with blunt chest trauma.

INTRODUCTION: Posttraumatic pneumothorax (PTX) is often overseen in anteroposterior chest X-ray. Chest sonography and Electrical Impedance Tomography (EIT) can both be used at the bedside and may provide complementary information. We evaluated the performance of EIT for diagnosing posttraumatic PTX in a pig model. METHODS: This study used images from an existing database of images acquired from 17 mechanically ventilated pigs, which had sustained standardized blunt chest trauma and had undergone repeated thoracic CT and EIT. 100 corresponding EIT/CT datasets were randomly chosen from the database and anonymized. Two independent and blinded observers analyzed the EIT data for presence and location of PTX. Analysis of the corresponding CTs by a radiologist served as reference. RESULTS: 87/100 cases had at least one PTX detected by CT. Fourty-two cases showed a PTX > 20% of the sternovertebral diameter (PTXtrans20), whereas 52/100 PTX showed a PTX>3 cm in the craniocaudal diameter (PTXcc3), with 20 cases showing both a PTXtranscc and a PTXcc3. We found a very low agreement between both EIT observers considering the classification overall PTX/noPTX (κ = 0.09, p = 0.183). For PTXtrans20, sensitivity was 59% for observer 1 and 17% for observer 2, with a specificity of 48% and 50%, respectively. For PTXcc3, observer 1 showed a sensitivity of 60% with a specificity of 51% while the sensitivity of observer 2 was 17%, with a specificity of 89%. By programming a semi-automatized detection algorithm, we significantly improved the detection rate of PTXcc3, with a sensitivity of 73% and a specificity of 70%. However, detection of PTXtranscc was not improved. CONCLUSION: In our analysis, visual interpretation of EIT without specific image processing or comparison with baseline data did not allow clinically useful diagnosis of posttraumatic PTX. Multimodal imaging approaches, technical improvements and image postprocessing algorithms might improve the performance of EIT for diagnosing PTX in the future.

Interactive comparison of scalar fields based on largest contours with applications to flow visualization.

Understanding fluid flow data, especially vortices, is still a challenging task. Sophisticated visualization tools help to gain insight. In this paper, we present a novel approach for the interactive comparison of scalar fields using isosurfaces, and its application to fluid flow datasets. Features in two scalar fields are defined by largest contour segmentation after topological simplification. These features are matched using a volumetric similarity measure based on spatial overlap of individual features. The relationships defined by this similarity measure are ranked and presented in a thumbnail gallery of feature pairs and a graph representation showing all relationships between individual contours. Additionally, linked views of the contour trees are provided to ease navigation. The main render view shows the selected features overlapping each other. Thus, by displaying individual features and their relationships in a structured fashion, we enable exploratory visualization of correlations between similar structures in two scalar fields. We demonstrate the utility of our approach by applying it to a number of complex fluid flow datasets, where the emphasis is put on the comparison of vortex related scalar quantities.

Generalized streak lines: analysis and visualization of boundary induced vortices.

We present a method to extract and visualize vortices that originate from bounding walls of three-dimensional time-dependent flows. These vortices can be detected using their footprint on the boundary, which consists of critical points in the wall shear stress vector field. In order to follow these critical points and detect their transformations, affected regions of the surface are parameterized. Thus, an existing singularity tracking algorithm devised for planar settings can be applied. The trajectories of the singularities are used as a basis for seeding particles. This leads to a new type of streak line visualization, in which particles are released from a moving source. These generalized streak lines visualize the particles that are ejected from the wall. We demonstrate the usefulness of our method on several transient fluid flow datasets from computational fluid dynamics simulations.