@phdthesis{Gorelashvili2019,
  author    = {Gorelashvili, Maximilian Georg},
  title     = {Investigation of megakaryopoiesis and the acute phase of ischemic stroke by advanced fluorescence microscopy},
  doi       = {10.25972/OPUS-18600},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-186002},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2019},
  abstract  = {In mammals, anucleate platelets circulate in the blood flow and are primarily responsible for maintaining functional hemostasis. Platelets are generated in the bone marrow (BM) by megakaryocytes (MKs), which mainly reside directly next to the BM sinusoids to release proplatelets into the blood. MKs originate from hematopoietic stem cells and are thought to migrate from the endosteal to the vascular niche during their maturation, a process, which is, despite being intensively investigated, still not fully understood. Long-term intravital two photon microscopy (2PM) of MKs and vasculature in murine bone marrow was performed and mean squared displacement analysis of cell migration was performed. The MKs exhibited no migration, but wobbling-like movement on time scales of 3 h. Directed cell migration always results in non-random spatial distribution. Thus, a computational modelling algorithm simulating random MK distribution using real 3D light-sheet fluorescence microscopy data sets was developed. Direct comparison of real and simulated random MK distributions showed, that MKs exhibit a strong bias to vessel-contact. However, this bias is not caused by cell migration, as non-vessel-associated MKs were randomly distributed in the intervascular space. Furthermore, simulation studies revealed that MKs strongly impair migration of other cells in the bone marrow by acting as large-sized obstacles. MKs are thought to migrate from the regions close to the endosteum towards the vasculature during their maturation process. MK distribution as a function of their localization relative to the endosteal regions of the bones was investigated by light sheet fluorescence microscopy (LSFM). The results show no bone-region dependent distribution of MKs. Taken together, the newly established methods and obtained results refute the model of MK migration during their maturation. Ischemia reperfusion (I/R) injury is a frequent complication of cerebral ischemic stroke, where brain tissue damage occurs despite successful recanalization. Platelets, endothelial cells and immune cells have been demonstrated to affect the progression of I/R injury in experimental mouse models 24 h after recanalization. However, the underlying Pathomechanisms, especially in the first hours after recanalization, are poorly understood. Here, LSFM, 2PM and complemental advanced image analysis workflows were established for investigation of platelets, the vasculature and neutrophils in ischemic brains. Quantitative analysis of thrombus formation in the ipsilateral and contralateral hemispheres at different time points revealed that platelet aggregate formation is minimal during the first 8 h after recanalization and occurs in both hemispheres. Considering that maximal tissue damage already is present at this time point, it can be concluded that infarct progression and neurological damage do not result from platelet aggregated formation. Furthermore, LSFM allowed to confirm neutrophil infiltration into the infarcted hemisphere and, here, the levels of endothelial cell marker PECAM1 were strongly reduced. However, further investigations must be carried out to clearly identify the role of neutrophils and the endothelial cells in I/R injury.},
  subject      = {Fluoreszenzmikroskopie},
  language  = {en}
}
@phdthesis{Elhfnawy2019,
  author    = {Elhfnawy, Ahmed},
  title     = {Relation between the length of the internal carotid stenotic segment and ischemic cerebrovascular events as well as white matter lesion load},
  doi       = {10.25972/OPUS-19161},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-191616},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2019},
  abstract  = {Background and Purpose: Internal carotid artery stenosis ≥70\% is a leading cause of ischemic cerebrovascular events. However, a considerable percentage of stroke survivors with symptomatic internal carotid artery stenosis have <70\% stenosis with a vulnerable plaque. Whether the length of internal carotid artery stenosis is associated with high risk of ischemic cerebrovascular events or with white matter lesions is poorly investigated. Our main aim was to investigate the relation between the length of internal carotid artery stenosis and the development of ischemic cerebrovascular events as well as ipsi-, contralateral as well as mean white matter lesion load. Methods: In a retrospective cross-sectional study, 168 patients with 208 internal carotid artery stenosis were identified. The degree and length of internal carotid artery stenosis as well as plaque morphology (hypoechoic, mixed or echogenic) were assessed on ultrasound scans. The white matter lesions were assessed in 4 areas separately, (periventricular and deep white matter lesions on each hemisphere), using the Fazekas scale. The mean white matter lesions load was calculated as the mean of these four values. Results: A statistically significant inverse correlation between the ultrasound-measured length and degree of internal carotid artery stenosis was detected for symptomatic internal carotid artery stenosis ≥70\% (Spearman correlation coefficient ρ = -0.57, p < 0.001, n = 51) but neither for symptomatic internal carotid artery stenosis <70\% (ρ = 0.15, p = 0.45, n = 27) nor for asymptomatic internal carotid artery stenosis (ρ = 0.07, p = 0.64, n = 54). The median (IQR) length for symptomatic internal carotid artery stenosis <70\% and ≥70\% was 17 (15-20) and 15 (12-19) mm (p = 0.06), respectively, while that for symptomatic internal carotid artery stenosis <90\% and symptomatic internal carotid artery stenosis 90\% was 18 (15-21) and 13 (10-16) mm, respectively (p < 0.001). Among patients with internal carotid artery stenosis <70\%, a cut-off length of ≥16 mm was found for symptomatic internal carotid artery stenosis rather than asymptomatic internal carotid artery stenosis with a sensitivity and specificity of 74.1\% and 51.1\%, respectively. Irrespective of the stenotic degree, plaques of the symptomatic internal carotid artery stenosis compared to asymptomatic internal carotid artery stenosis were significantly more often echolucent (43.2 vs. 24.6\%, p = 0.02). The length but not the degree of internal carotid artery stenosis showed a very slight trend toward association with ipsilateral white matter lesions and with mean white matter lesions load. Conclusion: We found a statistically insignificant tendency for the ultrasound-measured length of symptomatic internal carotid artery stenosis <70\% to be longer than that of symptomatic internal carotid artery stenosis ≥70\%. Moreover, the ultrasound-measured length of symptomatic internal carotid artery stenosis <90\% was significantly longer than that of symptomatic internal carotid artery stenosis 90\%. Among patients with symptomatic internal carotid artery stenosis ≥70\%, the degree and length of stenosis were inversely correlated. Furthermore, we have shown that a slight correlation exists between the length of stenosis and the presence of ipsilateral white matter lesions which might be due to microembolisation originating from the carotid plaque. Larger studies are needed before a clinical implication can be drawn from these results.},
  subject      = {Carotisstenose},
  language  = {en}
}
@phdthesis{Pfitzner2019,
  author    = {Pfitzner, Christian},
  title     = {Visual Human Body Weight Estimation with Focus on Clinical Applications},
  isbn      = {978-3-945459-27-0 (online)},
  doi       = {10.25972/OPUS-17484},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-174842},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2019},
  abstract  = {It is the aim of this thesis to present a visual body weight estimation, which is suitable for medical applications. A typical scenario where the estimation of the body weight is essential, is the emergency treatment of stroke patients: In case of an ischemic stroke, the patient has to receive a body weight adapted drug, to solve a blood clot in a vessel. The accuracy of the estimated weight influences the outcome of the therapy directly. However, the treatment has to start as early as possible after the arrival at a trauma room, to provide sufficient treatment. Weighing a patient takes time, and the patient has to be moved. Furthermore, patients are often not able to communicate a value for their body weight due to their stroke symptoms. Therefore, it is state of the art that physicians guess the body weight. A patient receiving a too low dose has an increased risk that the blood clot does not dissolve and brain tissue is permanently damaged. Today, about one-third gets an insufficient dosage. In contrast to that, an overdose can cause bleedings and further complications. Physicians are aware of this issue, but a reliable alternative is missing. The thesis presents state-of-the-art principles and devices for the measurement and estimation of body weight in the context of medical applications. While scales are common and available at a hospital, the process of weighing takes too long and can hardly be integrated into the process of stroke treatment. Sensor systems and algorithms are presented in the section for related work and provide an overview of different approaches. The here presented system -- called Libra3D -- consists of a computer installed in a real trauma room, as well as visual sensors integrated into the ceiling. For the estimation of the body weight, the patient is on a stretcher which is placed in the field of view of the sensors. The three sensors -- two RGB-D and a thermal camera -- are calibrated intrinsically and extrinsically. Also, algorithms for sensor fusion are presented to align the data from all sensors which is the base for a reliable segmentation of the patient. A combination of state-of-the-art image and point cloud algorithms is used to localize the patient on the stretcher. The challenges in the scenario with the patient on the bed is the dynamic environment, including other people or medical devices in the field of view. After the successful segmentation, a set of hand-crafted features is extracted from the patient's point cloud. These features rely on geometric and statistical values and provide a robust input to a subsequent machine learning approach. The final estimation is done with a previously trained artificial neural network. The experiment section offers different configurations of the previously extracted feature vector. Additionally, the here presented approach is compared to state-of-the-art methods; the patient's own assessment, the physician's guess, and an anthropometric estimation. Besides the patient's own estimation, Libra3D outperforms all state-of-the-art estimation methods: 95 percent of all patients are estimated with a relative error of less than 10 percent to ground truth body weight. It takes only a minimal amount of time for the measurement, and the approach can easily be integrated into the treatment of stroke patients, while physicians are not hindered. Furthermore, the section for experiments demonstrates two additional applications: The extracted features can also be used to estimate the body weight of people standing, or even walking in front of a 3D camera. Also, it is possible to determine or classify the BMI of a subject on a stretcher. A potential application for this approach is the reduction of the radiation dose of patients being exposed to X-rays during a CT examination. During the time of this thesis, several data sets were recorded. These data sets contain the ground truth body weight, as well as the data from the sensors. They are available for the collaboration in the field of body weight estimation for medical applications.},
  subject      = {Punktwolke},
  language  = {en}
}