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Item type:Publication, Access status: with files , Eignung und Unsicherheiten geometrischer und fluiddynamischer Parameter zur Rupturrisikoabschätzung zerebraler Aneurysmen(2020); Cerebral aneurysms are abnormal bulges of blood vessels in the brain that, if ruptured, can cause severe damage - from motor and cognitive failure to death. The choice of a suitable therapy for a diagnosed aneurysm is currently largely dependent on the size and location of the aneurysm. In contrast, hemodynamic and mechanical properties of the vascular system are not currently used in clinical practice for the risk assessment of aneurysms, but could be of great diagnostic value, especially for the assessment of small aneurysms with regard to the assessment of formation, growth and ultimately rupture. Furthermore, a major problem in understanding aneurysms with regard to the exact mechanisms leading to rupture is that only a few image data sets of individual aneurysm structures exist at different points in time. The different developmental stages of a single aneurysm are therefore difficult to analyze, making it difficult to formulate and verify propositions regarding the factors that determine development and rupture. This problem was the motivation for this work, which is why we worked on the exact calculation of geometric deformation of aneurysms, the reliable calculation of fluid-mechanical parameters and a extrapolated temporal development of aneurysm structures. Typically, only limited ground-truth data sets are available in this field of research. Therefore, the goal for this work was to base the analysis on verifiable datasets as much as possible, which motivated the development of a hardware phantom. The phantom simulates the fluid-mechanical characteristics of an aneurysm and material properties of the vessel wall and serves as a ground truth data set for all studies presented. The flow phantom was measured with different imaging modalities (MRI, CT, DSA), so that medical image data (which are common in this research field) are available, which represent the geometry and temporal geometric deformation. First, these data were used to develop a reliable method for the calculation of volumes and deformation of aneurysm geometries. Although previous studies have tried to quantify aneurysm pulsation based on temporally resolved image data, artifacts of the used imaging modalities have not been addressed, so it is not clear to what extent the measured values correspond to a true deformation. In addition, in previous studies no ground-truth data sets were used to verify the generated results, which leaves the reliability regarding the quantified values open. In order to approach the reliable calculation of fluid mechanical parameters, a fluid mechanical calculation setup was set up using the Ground-Truth data set, which enables a reliable simulation and calculation of fluid mechanical parameters. The previously acquired knowledge of exact phantom geometry, deformation and fluid mechanical boundary conditions (inflow velocity, etc.) was used to verify the calculated results. Based on this calculation setup, patient-specific geometries, which were collected at the University Medical Center Hamburg-Eppendorf (Clinic and Polyclinic for Neuroradiological Diagnostics and Intervention), could be simulated and parameters, which correlated with an increased risk of rupture in previous studies, could be evaluated. This was carried out in the sense of a parameter study with the aim of identifying boundary conditions that could have a falsifying influence on the produced results, which could explain the partial contradiction of currently published studies. In addition, different developmental stages of aneurysms were constructed and the geometric shape was simulated so that the fluid mechanical properties that change over the development process could be analysed.Publicationtype: Doctoral Thesis308 964 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A new cerebral vessel benchmark dataset (CAPUT) for validation of image-based aneurysm deformation estimation algorithms(Macmillan Publishers Limited, part of Springer Nature, 2018-10-30); ; ; Hemodynamic properties and deformation of vessel structures are assumed to be correlated to the initiation, development, and rupture of cerebral aneurysms. Therefore, precise quantification of wall motion is essential. However, using standard-of-care imaging data, approaches for patient-specific estimation of pulsatile deformation are prone to uncertainties due to, e.g., contrast agent inflow-related intensity changes and small deformation compared to the image resolution. A ground truth dataset that allows evaluating and finetuning algorithms for deformation estimation is lacking. We designed a flow phantom with deformable structures that resemble cerebral vessels and exhibit physiologically plausible deformation. The deformation was simultaneously recorded using a flat panel CT and a video camera, yielding video data with higher resolution and SNR, which was used to compute 'ground truth' structure deformation measures. The dataset was further applied to evaluate registration-based deformation estimation. The results illustrate that registration approaches can be used to estimate deformation with adequate precision. Yet, the accuracy depended on the registration parameters, illustrating the need to evaluate and finetune deformation estimation approaches by ground truth data. To fill the existing gap, the acquired benchmark dataset is provided freely available as the CAPUT (Cerebral Aneurysm PUlsation Testing) dataset, accessible at https://www.github.com/IPMI-ICNS-UKE/CAPUT .Publicationtype: Journal ArticleScopus© Citations 1 366 421 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Analysis of the influence of imaging-related uncertainties on cerebral aneurysm deformation quantification using a no-deformation physical flow phantom(Nature Publishing Group, 2018-07-20); ; ; ; Cardiac-cycle related pulsatile aneurysm motion and deformation is assumed to provide valuable information for assessing cerebral aneurysm rupture risk. Accordingly, numerous studies addressed quantification of cerebral aneurysm wall motion and deformation. Most of them utilized in vivo imaging data, but image-based aneurysm deformation quantification is subject to pronounced uncertainties: unknown ground-truth deformation; image resolution in the order of the expected deformation; direct interplay between contrast agent inflow and image intensity. To analyze the impact of the uncertainties on deformation quantification, a multi-imaging modality ground-truth phantom study is performed. A physical flow phantom was designed that allowed simulating pulsatile flow through a variety of modeled cerebral vascular structures. The phantom was imaged using different modalities [MRI, CT, 3D-RA] and mimicking physiologically realistic flow conditions. Resulting image data was analyzed by an established registration-based approach for automated wall motion quantification. The data reveals severe dependency between contrast media inflow-related image intensity changes and the extent of estimated wall deformation. The study illustrates that imaging-related uncertainties affect the accuracy of cerebral aneurysm deformation quantification, suggesting that in vivo imaging studies have to be accompanied by ground-truth phantom experiments to foster data interpretation and to prove plausibility of the applied image analysis algorithms.Publicationtype: Journal ArticleScopus© Citations 5 355 308 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Systematic analysis of jurkat T-cell deformation in fluorescence microscopy data(Springer, 2017-03); ; ; ; In the adaptive immune system, Calcium (Ca2+) is acting as a fundamental on-switch. Fluorescence microscopy is used to study the underlying mechanisms. However, living cells introduce motion and for the analysis of (sub-)cellular Ca2+ activity a precise motion analysis is necessary. We present an image based workflow to detect and analyze cell motion. We evaluate our approach on Jurkat T-cells using cell motion as observed from actual time series of cell images. Results indicate, that our method is able to detect deformation with an error of 0.2222 ± 0.086μm which is in the range of the image resolution, showing that accurate cell deformation detection is possible and feasible.Publicationtype: Conference Paper119 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A modular framework for post-processing and analysis of fluorescence microscopy image sequences of subcellular calcium dynamics(Springer, 2015-03); ; ; ; Calcium (Ca2+) signaling is essential for activation of Tlymphocytes and can be understood as fundamental on-switch for the adaptive immune system. The activation is supposed to start by initial spatially and temporally localized Ca2+ signals. Imaging and analysis of these signals require high spatio-temporal resolution fluorescence microscopy – which, in turn, results in the need for an efficient and reliable post-processing and analysis workflow of the acquired image data. Started with a well established but time-consuming post-processing process, we report on our efforts to automatize and optimize it. The efforts led to a modular post-processing and analysis framework, which is presented. In addition, the influence of instances of the main blocks of the framework (e.g. bleaching correction, deconvolution) on Ca2+ dynamics analysis measures is evaluated.Publicationtype: Conference Paper85