Silvia Born

Extraction of Airways From CT (EXACT'09)

This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part of the airway tree. Finally, the reference airway trees are constructed by taking the union of all correctly extracted branch segments. Fifteen airway tree extraction algorithms from different research groups are evaluated on a diverse set of twenty chest computed tomography (CT) scans of subjects ranging from healthy volunteers to patients with severe pathologies, scanned at different sites, with different CT scanner brands, models, and scanning protocols. Three performance measures covering different aspects of segmentation quality were computed for all participating algorithms. Results from the evaluation showed that no single algorithm could extract more than an average of 74% of the total length of all branches in the reference standard, indicating substantial differences between the algorithms. A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.

Illustrative Stream Surfaces

Stream surfaces are an intuitive approach to represent 3D vector fields. In many cases, however, they are challenging objects to visualize and to understand, due to a high degree of self-occlusion. Despite the need for adequate rendering methods, little work has been done so far in this important research area. In this paper, we present an illustrative rendering strategy for stream surfaces. In our approach, we apply various rendering techniques, which are inspired by the traditional flow illustrations drawn by Dallmann and Abraham & Shaw in the early 1980s. Among these techniques are contour lines and halftoning to show the overall surface shape. Flow direction as well as singularities on the stream surface are depicted by illustrative surface streamlines. ;To go beyond reproducing static text book images, we provide several interaction features, such as movable cuts and slabs allowing an interactive exploration of the flow and insights into subjacent structures, e.g., the inner windings of vortex breakdown bubbles. These methods take only the parameterized stream surface as input, require no further preprocessing, and can be freely combined by the user. We explain the design, GPU-implementation, and combination of the different illustrative rendering and interaction methods and demonstrate the potential of our approach by applying it to stream surfaces from various flow simulations.

Visual Analysis of Cardiac 4D MRI Blood Flow Using Line Predicates

Four-dimensional MRI is an in vivo flow imaging modality that is expected to significantly enhance the understanding of cardiovascular diseases. Among other fields, 4D MRI provides valuable data for the research of cardiac blood flow and with that the development, diagnosis, and treatment of various cardiac pathologies. However, to gain insights from larger research studies or to apply 4D MRI in the clinical routine later on, analysis techniques become necessary that allow to robustly identify important flow characteristics without demanding too much time and expert knowledge. Heart muscle contractions and the particular complexity of the flow in the heart imply further challenges when analyzing cardiac blood flow. Working toward the goal of simplifying the analysis of 4D MRI heart data, we present a visual analysis method using line predicates. With line predicates precalculated integral lines are sorted into bundles with similar flow properties, such as velocity, vorticity, or flow paths. The user can combine the line predicates flexibly and by that carve out interesting flow features helping to gain overview. We applied our analysis technique to 4D MRI data of healthy and pathological hearts and present several flow aspects that could not be shown with current methods. Three 4D MRI experts gave feedback and confirmed the additional benefit of our method for their understanding of cardiac blood flow.

Illustrative visualization of cardiac and aortic blood flow from 4D MRI data

In the last years, illustrative methods have found their way into flow visualization since they communicate difficult information in a comprehensible way. This is of great benefit especially in domains where the audience does not necessarily have flow expertise. One such domain is the medical field where the development of 4D MR imaging (for in-vivo 3D blood flow measurement) lead to an increased demand for easy flow analysis techniques. The goal and the challenge is to transfer the data into simple visualizations supporting the physician with flow interpretation and decision making. In this work, we take one step towards this goal. We present an approach for the illustrative visualization of steady flow features occurring in 4D MRI data of heart and aorta. Like shown in manually created illustrations, we restrict our visualization to the main data characteristics and do not depict every flow detail. The input for our method are flow features extracted from a datasets complete set of streamlines with the help of line predicates. We create an abstract depiction of these line bundles by selecting a set of bundle representatives reflecting the most important flow aspects. These lines are rendered as three-dimensional arrows that are fused in areas where they represent the same flow. Since vortices are another important flow information for a physician, we identify these regions in the 4D MRI data and display them as unobtrusive, tube-like structures. A hatching texture provides for a visual effect of rotational blood flow. By applying our illustration technique to diverse flow structures of several 4D MRI datasets, we demonstrate that the abstract visualization is useful to gain an easier insight into the data. Feedback of medical experts confirmed the usefulness and revealed limitations of our work. The images are restricted to the essential flow features and, therefore, clearer and less cluttered. Our method has great potential and offers many possible applications, e.g., in comparative visualization and also beyond the medical domain.

Illustrative hybrid visualization and exploration of anatomical and functional brain data

Common practice in brain research and brain surgery involves the multi‐modal acquisition of brain anatomy and brain activation data. These highly complex three‐dimensional data have to be displayed simultaneously in order to convey spatial relationships. Unique challenges in information and interaction design have to be solved in order to keep the visualization sufficiently complete and uncluttered at the same time. The visualization method presented in this paper addresses these issues by using a hybrid combination of polygonal rendering of brain structures and direct volume rendering of activation data. Advanced rendering techniques including illustrative display styles and ambient occlusion calculations enhance the clarity of the visual output. The presented rendering pipeline produces real‐time frame rates and offers a high degree of configurability. Newly designed interaction and measurement tools are provided, which enable the user to explore the data at large, but also to inspect specific features closely. We demonstrate the system in the context of a cognitive neurosciences dataset. An initial informal evaluation shows that our visualization method is deemed useful for clinical research.

Visual 4D MRI blood flow analysis with line predicates

4D MRI is an in vivo flow imaging modality which has the potential to significantly enhance diagnostics and therapy of cardiovascular diseases. However, current analysis methods demand too much time and expert knowledge in order to apply 4D MRI in the clinics or larger clinical studies. One missing piece are methods allowing to gain a quick overview of the flow datas main properties. We present a line predicate approach that sorts precalculated integral lines, which capture the complete flow dynamics, into bundles with similar properties. We introduce several streamline and pathline predicates that allow to structure the flow according to various features useful for blood flow analysis, such as, e.g., velocity distribution, vortices, and flow paths. The user can combine these predicates flexibly and by that create flow structures that help to gain overview and carve out special features of the current dataset. We show the usefulness of our approach by means of a detailed discussion of 4D MRI datasets of healthy and pathological aortas.

Extrapolation in the analysis of lung aeration by computed tomography: a validation study

IntroductionComputed tomography (CT) is considered the gold standard for quantification of global or regional lung aeration and lung mass. Quantitative CT, however, involves the exposure to ionizing radiation and requires manual image processing. We recently evaluated an extrapolation method which calculates quantitative CT parameters characterizing the entire lung from only 10 reference CT-slices thereby reducing radiation exposure and analysis time. We hypothesized that this extrapolation method could be further validated using CT-data from pigs and sheep, which have a different thoracic anatomy.MethodsWe quantified volume and mass of the total lung and differently aerated lung compartments in 168 ovine and 55 porcine whole-lung CTs covering lung conditions from normal to gross deaeration. Extrapolated volume and mass parameters were compared to the respective values obtained by whole-lung analysis. We also tested the accuracy of extrapolation for all possible numbers of CT slices between 15 and 5. Bias and limits of agreement (LOA) were analyzed by the Bland-Altman method.ResultsFor extrapolation from 10 reference slices, bias (LOA) for the total lung volume and mass of sheep were 18.4 (-57.2 to 94.0) ml and 4.2 (-21.8 to 30.2) grams, respectively. The corresponding bias (LOA) values for pigs were 5.1 (-55.2 to 65.3) ml and 1.6 (-32.9 to 36.2) grams, respectively. All bias values for differently aerated lung compartments were below 1% of the total lung volume or mass and the LOA never exceeded ± 2.5%. Bias values diverged from zero and the LOA became considerably wider when less than 10 reference slices were used.ConclusionsThe extrapolation method appears robust against variations in thoracic anatomy, which further supports its accuracy and potential usefulness for clinical and experimental application of quantitative CT.

A Survey of Cardiac 4D PC-MRI Data Processing

Cardiac four‐dimensional phase‐contrast magnetic resonance imaging (4D PC‐MRI) acquisitions have gained increasing clinical interest in recent years. They allow to non‐invasively obtain extensive information about patient‐specific hemodynamics, and thus have a great potential to improve the diagnosis, prognosis and therapy planning of cardiovascular diseases. A dataset contains time‐resolved, three‐dimensional blood flow directions and strengths, making comprehensive qualitative and quantitative data analysis possible. Quantitative measures, such as stroke volumes, help to assess the cardiac function and to monitor disease progression. Qualitative analysis allows to investigate abnormal flow characteristics, such as vortices, which are correlated to different pathologies. Processing the data comprises complex image processing methods, as well as flow analysis and visualization. In this work, we mainly focus on the aorta. We provide an overview of data measurement and pre‐processing, as well as current visualization and quantification methods. This allows other researchers to quickly catch up with the topic and take on new challenges to further investigate the potential of 4D PC‐MRI data.

Computed tomographic assessment of lung weights in trauma patients with early posttraumatic lung dysfunction

IntroductionQuantitative computed tomography (qCT)-based assessment of total lung weight (Mlung) has the potential to differentiate atelectasis from consolidation and could thus provide valuable information for managing trauma patients fulfilling commonly used criteria for acute lung injury (ALI). We hypothesized that qCT would identify atelectasis as a frequent mimic of early posttraumatic ALI.MethodsIn this prospective observational study, Mlung was calculated by qCT in 78 mechanically ventilated trauma patients fulfilling the ALI criteria at admission. A reference interval for Mlung was derived from 74 trauma patients with morphologically and functionally normal lungs (reference). Results are given as medians with interquartile ranges.ResultsThe ratio of arterial partial pressure of oxygen to the fraction of inspired oxygen was 560 (506 to 616) mmHg in reference patients and 169 (95 to 240) mmHg in ALI patients. The median reference Mlung value was 885 (771 to 973) g, and the reference interval for Mlung was 584 to 1164 g, which matched that of previous reports. Despite the significantly greater median Mlung value (1088 (862 to 1,342) g) in the ALI group, 46 (59%) ALI patients had Mlung values within the reference interval and thus most likely had atelectasis. In only 17 patients (22%), Mlung was increased to the range previously reported for ALI patients and compatible with lung consolidation. Statistically significant differences between atelectasis and consolidation patients were found for age, Lung Injury Score, Glasgow Coma Scale score, total lung volume, mass of the nonaerated lung compartment, ventilator-free days and intensive care unit-free days.ConclusionsAtelectasis is a frequent cause of early posttraumatic lung dysfunction. Differentiation between atelectasis and consolidation from other causes of lung damage by using qCT may help to identify patients who could benefit from management strategies such as damage control surgery and lung-protective mechanical ventilation that focus on the prevention of pulmonary complications.

Stent Maps — Comparative Visualization for the Prediction of Adverse Events of Transcatheter Aortic Valve Implantations

Transcatheter aortic valve implantation (TAVI) is a minimally-invasive method for the treatment of aortic valve stenosis in patients with high surgical risk. Despite the success of TAVI, side effects such as paravalvular leakages can occur postoperatively. The goal of this project is to quantitatively analyze the co-occurrence of this complication and several potential risk factors such as stent shape after implantation, implantation height, amount and distribution of calcifications, and contact forces between stent and surrounding structure. In this paper, we present a two-dimensional visualization (stent maps), which allows (1) to comprehensively display all these aspects from CT data and mechanical simulation results and (2) to compare different datasets to identify patterns that are typical for adverse effects. The area of a stent map represents the surface area of the implanted stent - virtually straightened and uncoiled. Several properties of interest, like radial forces or stent compression, are displayed in this stent map in a heatmap-like fashion. Important anatomical landmarks and calcifications are plotted to show their spatial relation to the stent and possible correlations with the color-coded parameters. To provide comparability, the maps of different patient datasets are spatially adjusted according to a corresponding anatomical landmark. Also, stent maps summarizing the characteristics of different populations (e.g. with or without side effects) can be generated. Up to this point several interesting patterns have been observed with our technique, which remained hidden when examining the raw CT data or 3D visualizations of the same data. One example are obvious radial force maxima between the right and non-coronary valve leaflet occurring mainly in cases without leakages. These observations confirm the usefulness of our approach and give starting points for new hypotheses and further analyses. Because of its reduced dimensionality, the stent map data is an appropriate input for statistical group evaluation and machine learning methods.