Intravascular optical coherence tomography (OCT) as an additional tool for the assessment of stent structures

Evaluation of the vascular stent position, shape and correct expansion has a high relevance in therapy and diagnosis. Hence, the wall apposition in vessel areas with differing diameters and the appearance of torsions or structural defects of the implant body caused by catheter based device dropping are of special interest. Neurovascular implants like braided flow diverter and laser cut stents consist of metal struts and wires with diameters of about 40 µm. Depending on the implants material composition, visibility is poor with conventional 2D X-ray fluoroscopic and radiographic imaging. The metal structures of the implants also lead to artifacts in 3D X-ray images and can hamper the assessment of the device position. We investigated intravascular optical coherence tomography (OCT) as a new imaging tool for the evaluation of the vascular stent position, its shape and its correct expansion for 3 different vascular implants

Occlusion-free Blood Flow Animation with Wall Thickness Visualization

International audienceWe 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

From imaging to hemodynamics – how reconstruction kernels influence the blood flow predictions in intracranial aneurysms

Computational fluid dynamics (CFD) is increasingly used by biomedical engineering groups to understand and predict the blood flow within intracranial aneurysms and support the physician during therapy planning. However, due to various simplifications, its acceptance remains limited within the medical community. To quantify the influence of the reconstruction kernels employed for reconstructing 3D images from rotational angiography data, different kernels are applied to four datasets with patient-specific intracranial aneurysms. Sharp, normal and smooth reconstructions were evaluated. Differences of the resulting 24 segmentations and the impact on the hemodynamic predictions are quantified to provide insights into the expected error ranges. A comparison of the segmentations yields strong differences regarding vessel branches and diameters. Further, sharp kernels lead to smaller ostium areas than smooth ones. Analyses of hemodynamic predictions reveal a clear time and space dependency, while mean velocity deviations range from 3.9 to 8%. The results reveal a strong influence of reconstruction kernels on geometrical aneurysm models and the subsequent hemodynamic parameters. Thus, patient-specific blood flow predictions require a carefully selected reconstruction kernel and appropriate recommendations need to be formulated

Combining visual analytics and case-based reasoning for rupture risk assessment of intracranial aneurysms

Purpose!#!Medical case-based reasoning solves problems by applying experience gained from the outcome of previous treatments of the same kind. Particularly for complex treatment decisions, for example, incidentally found intracranial aneurysms (IAs), it can support the medical expert. IAs bear the risk of rupture and may lead to subarachnoidal hemorrhages. Treatment needs to be considered carefully, since it may entail unnecessary complications for IAs with low rupture risk. With a rupture risk prediction based on previous cases, the treatment decision can be supported.!##!Methods!#!We present an interactive visual exploration tool for the case-based reasoning of IAs. In presence of a new aneurysm of interest, our application provides visual analytics techniques to identify the most similar cases with respect to morphology. The clinical expert can obtain the treatment, including the treatment outcome, for these cases and transfer it to the aneurysm of interest. Our application comprises a heatmap visualization, an adapted scatterplot matrix and fully or partially directed graphs with a circle- or force-directed layout to guide the interactive selection process. To fit the demands of clinical applications, we further integrated an interactive identification of outlier cases as well as an interactive attribute selection for the similarity calculation. A questionnaire evaluation with six trained physicians was used.!##!Result!#!Our application allows for case-based reasoning of IAs based on a reference data set. Three classifiers summarize the rupture state of the most similar cases. Medical experts positively evaluated the application.!##!Conclusion!#!Our case-based reasoning application combined with visual analytic techniques allows for representation of similar IAs to support the clinician. The graphical representation was rated very useful and provides visual information of the similarity of the k most similar cases