Sylvia Glaßer

Computer-aided diagnosis in breast DCE-MRI—Quantification of the heterogeneity of breast lesions

PURPOSE In our study we aim at the quantification of the heterogeneity for differential diagnosis of breast lesions in MRI. MATERIALS AND METHODS We tested a software tool for quantification of heterogeneity. The software tool provides a three-dimensional analysis of the whole breast lesion. The lesions were divided in regions with similar perfusion characteristics. Voxels were merged to the same region, if the perfusion parameters (wash-in, wash-out, integral, peak enhancement and time to peak) correlated to 99%. We evaluated 68 lesions from 50 patients. 31 lesions proved to be benign (45.6%) and 37 malignant (54.4%). We included small lesions which could only be detected with MRI. RESULTS The analysis of heterogeneity showed significant differences (p<0.005; AUC 0.7). Malignant lesions were more heterogeneous than benign ones. Significant differences were also found for morphologic parameters such as shape (p<0.001) and margin (p<0.007). The analysis of the enhancement dynamics did not prove successful in lesion discrimination. CONCLUSION Our study indicates that the region analysis for quantification of heterogeneity may be a helpful additional method to differentiate benign lesions from malignant ones.

Combined Visualization of Wall Thickness and Wall Shear Stress for the Evaluation of Aneurysms

For an individual rupture risk assessment of aneurysms, the aneurysms wall morphology and hemodynamics provide valuable information. Hemodynamic information is usually extracted via computational fluid dynamic (CFD) simulation on a previously extracted 3D aneurysm surface mesh or directly measured with 4D phase-contrast magnetic resonance imaging. In contrast, a noninvasive imaging technique that depicts the aneurysm wall in vivo is still not available. Our approach comprises an experiment, where intravascular ultrasound (IVUS) is employed to probe a dissected saccular aneurysm phantom, which we modeled from a porcine kidney artery. Then, we extracted a 3D surface mesh to gain the vessel wall thickness and hemodynamic information from a CFD simulation. Building on this, we developed a framework that depicts the inner and outer aneurysm wall with dedicated information about local thickness via distance ribbons. For both walls, a shading is adapted such that the inner wall as well as its distance to the outer wall is always perceivable. The exploration of the wall is further improved by combining it with hemodynamic information from the CFD simulation. Hence, the visual analysis comprises a brushing and linking concept for individual highlighting of pathologic areas. Also, a surface clustering is integrated to provide an automatic division of different aneurysm parts combined with a risk score depending on wall thickness and hemodynamic information. In general, our approach can be employed for vessel visualization purposes where an inner and outer wall has to be adequately represented.

Vessel Visualization with Volume Rendering

Volume rendering allows the direct visualization of scanned volume data, and can reveal vessel abnormalitiesmore faithfully. In this overview, we will present a pipeline model for direct volume rendering systems, which focus on vascular structures. We will cover the fields of data pre-processing, classification of the volume via transfer functions, and finally rendering the volume in 2D and 3D. For each stage in the pipeline, different techniques are discussed to support the diagnosis of vascular diseases. Next to various general methods we will present two case studies, in which the systems are optimized for two different medical issues. At the end, we discuss current trends in volume rendering and their implications for vessel visualization.

Automatic Transfer Function Specification for Visual Emphasis of Coronary Artery Plaque

Cardiovascular imaging with current multislice spiral computed tomography (MSCT) technology enables a non‐invasive evaluation of the coronary arteries. Contrast‐enhanced MSCT angiography with high spatial resolution allows for a segmentation of the coronary artery tree. We present an automatically adapted transfer function (TF) specification to highlight pathologic changes of the vessel wall based on the segmentation result of the coronary artery tree. The TFs are combined with common visualization techniques, such as multiplanar reformation and direct volume rendering for the evaluation of coronary arteries in MSCT image data. The presented TF‐based mapping of CT values in Hounsfield Units (HU) to color and opacity leads to a different color coding for different plaque types. To account for varying HU values of the vessel lumen caused by the contrast medium, the TFs are adapted to each dataset by local histogram analysis. We describe an informal evaluation with three board‐certified radiologists which indicates that the represented visualizations guide the users attention to pathologic changes of the vessel wall as well as provide an overview about spatial variations.

3D Regression Heat Map Analysis of Population Study Data

Epidemiological studies comprise heterogeneous data about a subject group to define disease-specific risk factors. These data contain information (features) about a subjects lifestyle, medical status as well as medical image data. Statistical regression analysis is used to evaluate these features and to identify feature combinations indicating a disease (the target feature). We propose an analysis approach of epidemiological data sets by incorporating all features in an exhaustive regression-based analysis. This approach combines all independent features w.r.t. a target feature. It provides a visualization that reveals insights into the data by highlighting relationships. The 3D Regression Heat Map, a novel 3D visual encoding, acts as an overview of the whole data set. It shows all combinations of two to three independent features with a specific target disease. Slicing through the 3D Regression Heat Map allows for the detailed analysis of the underlying relationships. Expert knowledge about disease-specific hypotheses can be included into the analysis by adjusting the regression model formulas. Furthermore, the influences of features can be assessed using a difference view comparing different calculation results. We applied our 3D Regression Heat Map method to a hepatic steatosis data set to reproduce results from a data mining-driven analysis. A qualitative analysis was conducted on a breast density data set. We were able to derive new hypotheses about relations between breast density and breast lesions with breast cancer. With the 3D Regression Heat Map, we present a visual overview of epidemiological data that allows for the first time an interactive regression-based analysis of large feature sets with respect to a disease.

Glyph-based visualization of myocardial perfusion data and enhancement with contractility and viability information

Perfusion data characterize the regional blood flow in human tissue. In the diagnosis of the Coronary Heart Disease, they are acquired to detect hypoperfused regions of the myocardium (heart muscle) at an early stage or to evaluate the hemodynamical relevance of a known pathologic vessel narrowing. For each voxel in the data, a time-intensity curve describes the enhancement of a contrast agent. Parameters derived from these curves characterize the regional perfusion and have to be integrated for diagnosis. The diagnostic evaluation of this multi-field data is challenging and time-consuming due to its complexity. We tackle this problem by developing a glyph-based integrated visualization of perfusion parameters in 3D-space with the patient-individual ventricular anatomy as context information. Besides the assessment of myocardial perfusion, current cardiac imaging technology allows for the investigation of myocardial contractility as well as for the detection of non-viable tissue. The combined inspection of these data supports diagnosis finding and therapy planning by allowing for the discrimination of healthy, hypoperfused and non-viable tissue as well as between non-viable and temporarily inactive tissue. To facilitate such an inspection, we apply registration methods that cope with differences in orientation and coverage between these three datasets. We enhance the glyph-based visualization of perfusion parameters by integrating parameters describing the myocardial contractility and viability.

Experimental investigation of intravascular OCT for imaging of intracranial aneurysms.

PurposeRupture risk assessment of an intracranial aneurysm (IA) is an important factor for indication of therapy. Until today, there is no suitable objective prediction method. Conventional imaging modalities cannot assess the IA’s vessel wall. We investigated the ability of intravascular optical coherence tomography (OCT) as a new tool for the characterization and evaluation of IAs.Materials and methodsAn experimental setup for acquisition of geometrical aneurysm parameters was developed. Object of basic investigation was a silicone phantom with six IAs from patient data. For structural information, three circle of Willis were dissected and imaged postmortem. All image data were postprocessed by medical imaging software.ResultsGeometrical image data of a phantom with six different IAs were acquired. The geometrical image data showed a signal loss, e.g., in aneurysms with a high bottleneck ratio. Imaging data of vessel specimens were evaluated with respect to structural information that is valuable for the characterization of IAs. Those included thin structures (intimal flaps), changes of the vessel wall morphology (intimal thickening, layers), adjacent vessels, small vessel outlets, arterial branches and histological information.ConclusionIntravascular OCT provides new possibilities for diagnosis and rupture assessment of IAs. However, currently used imaging system parameters have to be adapted and new catheter techniques have to be developed for a complete assessment of the morphology of IAs.

Fluid-Structure Simulations of a Ruptured Intracranial Aneurysm: Constant versus Patient-Specific Wall Thickness.

Computational Fluid Dynamics is intensively used to deepen the understanding of aneurysm growth and rupture in order to support physicians during therapy planning. However, numerous studies considering only the hemodynamics within the vessel lumen found no satisfactory criteria for rupture risk assessment. To improve available simulation models, the rigid vessel wall assumption has been discarded in this work and patient-specific wall thickness is considered within the simulation. For this purpose, a ruptured intracranial aneurysm was prepared ex vivo, followed by the acquisition of local wall thickness using μCT. The segmented inner and outer vessel surfaces served as solid domain for the fluid-structure interaction (FSI) simulation. To compare wall stress distributions within the aneurysm wall and at the rupture site, FSI computations are repeated in a virtual model using a constant wall thickness approach. Although the wall stresses obtained by the two approaches—when averaged over the complete aneurysm sac—are in very good agreement, strong differences occur in their distribution. Accounting for the real wall thickness distribution, the rupture site exhibits much higher stress values compared to the configuration with constant wall thickness. The study reveals the importance of geometry reconstruction and accurate description of wall thickness in FSI simulations.

The FAUST framework: Free-form annotations on unfolding vascular structures for treatment planning

Abstract For complex interventions, such as stenting of a cerebral aneurysm, treatment planning is mandatory. Sketching can support the physician as it involves an active involvement with complex spatial relations and bears a great potential to improve communication. These sketches are employed as direct annotation on 2D medical image data and print outs, respectively. Annotating 3D planning models is more difficult due to possible occlusions of the complex spatial anatomy of vascular structures. Furthermore, the annotations should adapt accordingly to view changes and deforming structures. Therefore, we developed the FAUST framework, which allows creating 3D annotations by freely sketching in the 3D environment. Additionally to generic annotations, the physician is supported to create the most common treatment options with sketching single strokes only. We allow an interactive unfolding of vascular structures with adapting annotations to still convey their meta information. Our framework is realized on the zSpace, which combines a semi-immersive stereoscopic display and a stylus with ray-based interaction techniques. We conducted a user study with computer scientists, carried out a demo session with a neuroradiologist and assessed the performance. The user study revealed a positive rating of the interaction techniques and a high sense of presence. The neuroradiologist stated that our framework can support treatment planning and leads to a better understanding of anatomical structures. Our performance evaluation showed that our sketching approach is usable in real-time with a large number of annotations. Furthermore, our approach can be adapted to a wider range of applications including medical documentation.

Virtual Inflation of the Cerebral Artery Wall for the Integrated Exploration of OCT and Histology Data: Virtual Inflation of the Cerebral Artery Wall for the Integrated Exploration of OCT and Histology Data

Intravascular imaging provides new insights into the condition of vessel walls. This is crucial for cerebrovascular diseases including stroke and cerebral aneurysms, where it may present an important factor for indication of therapy. In this work, we provide new information of cerebral artery walls by combining ex vivo optical coherence tomography (OCT) imaging with histology data sets. To overcome the obstacles of deflated and collapsed vessels due to the missing blood pressure, the lack of co‐alignment as well as the geometrical shape deformations due to catheter probing, we developed the new image processing method virtual inflation. We locally sample the vessel wall thickness based on the (deflated) vessel lumen border instead of the vessels centerline. Our method is embedded in a multi‐view framework where correspondences between OCT and histology can be highlighted via brushing and linking yielding OCT signal characteristics of the cerebral artery wall and its pathologies. Finally, we enrich the data views with a hierarchical clustering representation which is linked via virtual inflation and further supports the deduction of vessel wall pathologies.