Objective quantification of the vocal fold vascular pattern: comparison of narrow band imaging and white light endoscopy.

No clinical standard procedure has yet been defined to quantify the vascular pattern of vocal folds. Subjective classification trials have shown a lot of promise. Narrow band imaging (NBI) as an endoscopic imaging tool is useful, because it shows the vascular structure clearer than white light endoscopy (WL) alone. Endoscopic images of 74 human vocal folds (NBI and WL) were semi-automatically evaluated after image processing with respect to pixels of vessels and mucosa by the software MeVisLab. The ratios of vessel/mucosa pixels were compared. Using NBI, more vocal fold vessels are visible compared with WL alone (p = 0.000). There may be a difference between the right and left vocal folds due to the handedness of the examiner (p = 0.033) without any interaction between the method (NBI/WL) and the side (right/left) (p = 0.467). MeVisLab is a suitable tool for the objective quantification of the vessel/mucosa ratio for NBI and WL endoscopic images. NBI is an appropriate endoscopic tool for examination of diseases of vocal folds with changes in the vascular pattern. There is evidence that the handedness of the examiner may have an influence on the quality of the examination between the right and left vocal folds.

Experimental investigation of intravascular OCT for imaging of intracranial aneurysms.

PURPOSE: Rupture 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 METHODS: An 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. RESULTS: Geometrical 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. CONCLUSION: Intravascular 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.

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 subject's 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.

Occlusion-free Blood Flow Animation with Wall Thickness Visualization.

We present the first visualization tool that combines pathlines from blood flow and wall thickness information. Our method uses illustrative techniques to provide occlusion-free visualization of the flow. We thus offer medical researchers an effective visual analysis tool for aneurysm treatment risk assessment. Such aneurysms bear a high risk of rupture and significant treatment-related risks. Therefore, to get a fully informed decision it is essential to both investigate the vessel morphology and the hemodynamic data. Ongoing research emphasizes the importance of analyzing the wall thickness in risk assessment. Our combination of blood flow visualization and wall thickness representation is a significant improvement for the exploration and analysis of aneurysms. As all presented information is spatially intertwined, occlusion problems occur. We solve these occlusion problems by dynamic cutaway surfaces. We combine this approach with a glyph-based blood flow representation and a visual mapping of wall thickness onto the vessel surface. We developed a GPU-based implementation of our visualizations which facilitates wall thickness analysis through real-time rendering and flexible interactive data exploration mechanisms. We designed our techniques in collaboration with domain experts, and we provide details about the evaluation of the technique and tool.

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

For an individual rupture risk assessment of aneurysms, the aneurysm's 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.

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.