iRegNet: Non-rigid Registration of MRI to Interventional US for Brain-Shift Compensation using Convolutional Neural Networks

Accurate and safe neurosurgical intervention can be affected by intra-operative tissue deformation, known as brain-shift. In this study, we propose an automatic, fast, and accurate deformable method, called iRegNet, for registering pre-operative magnetic resonance images to intra-operative ultrasound volumes to compensate for brain-shift. iRegNet is a robust end-to-end deep learning approach for the non-linear registration of MRI-iUS images in the context of image-guided neurosurgery. Pre-operative MRI (as moving image) and iUS (as fixed image) are first appended to our convolutional neural network, after which a non-rigid transformation field is estimated. The MRI image is then transformed using the output displacement field to the iUS coordinate system. Extensive experiments have been conducted on two multi-location databases, which are the BITE and the RESECT. Quantitatively, iRegNet reduced the mean landmark errors from pre-registration value of (4.18 ± 1.84 and 5.35 ± 4.19 mm) to the lowest value of (1.47 ± 0.61 and 0.84 ± 0.16 mm) for the BITE and RESECT datasets, respectively. Additional qualitative validation of this study was conducted by two expert neurosurgeons through overlaying MRI-iUS pairs before and after the deformable registration. Experimental findings show that our proposed iRegNet is fast and achieves state-of-the-art accuracies outperforming state-of-the-art approaches. Furthermore, the proposed iRegNet can deliver competitive results, even in the case of non-trained images as proof of its generality and can therefore be valuable in intra-operative neurosurgical guidance

Pharmacological Investigations of N-Substituent Variation in Morphine and Oxymorphone: Opioid Receptor Binding, Signaling and Antinociceptive Activity

Morphine and structurally related derivatives are highly effective analgesics, and the mainstay in the medical management of moderate to severe pain. Pharmacological actions of opioid analgesics are primarily mediated through agonism at the mopioid peptide (MOP) receptor, a G protein-coupled receptor. Position 17 in morphine has been one of the most manipulated sites on the scaffold and intensive research has focused on replacements of the 17-methyl group with other substituents. Structural variations at the N-17 of the morphinan skeleton led to a diversity of molecules appraised as valuable and potential therapeutics and important research probes. Discovery of therapeutically useful morphine-like drugs has also targeted the C-6 hydroxyl group, with oxymorphone as one of the clinically relevant opioid analgesics, where a carbonyl instead of a hydroxyl group is present at position 6. Herein, we describe the effect of N-substituent variation in morphine and oxymorphone on in vitro and in vivo biological properties and the emerging structure-activity relationships. We show that the presence of a N-phenethyl group in position 17 is highly favorable in terms of improved affinity and selectivity at the MOP receptor, potent agonism and antinociceptive efficacy. The N-phenethyl derivatives of morphine and oxymorphone were very potent in stimulating G protein coupling and intracellular calcium release through the MOP receptor. In vivo, they were highly effective against acute thermal nociception in mice with marked increased antinociceptive potency compared to the lead molecules. It was also demonstrated that a carbonyl group at position 6 is preferable to a hydroxyl function in these N-phenethyl derivatives, enhancing MOP receptor affinity and agonist potency in vitro and in vivo. These results expand the understanding of the impact of different moieties at the morphinan nitrogen on ligand-receptor interaction, molecular mode of action and signaling, and may be instrumental to the development of new opioid therapeutics

Risk governance in organizations

Dieses Buch dokumentiert 10 Jahre Risk-Governance-Forschung an der Universität Siegen. In 50 Beiträgen reflektieren Forscher und Praktiker Risk Governance vor dem Hintergrund ihrer eigenen Forschungen und/oder Erfahrungen und geben jeweils einen Entwicklungsimpuls für die Zukunft der Risk Governance. Das Buch zeigt die große Bandbreite und Tiefe des Forschungsgebietes auf und diskutiert Grundannahmen, Implementierungsfragen, die Rolle der Risk Governance als Transformationsmotor, ihre Wirkung in den verschiedenen betrieblichen Funktionen, Entwicklungsperspektiven und den Beitrag der Risk Governance zu einer nachhaltigen Ausrichtung von Unternehmen.This book documents 10 years of risk governance research at the University of Siegen. In 50 contributions, researchers and practitioners reflect on risk governance against the background of their own research and/or experience and provide a development impetus for the future of risk governance. The book shows the wide range and depth of the research field and discusses basic assumptions, implementation issues, the role of risk governance as transformation engine, its impact in the various operational functions, development perspectives, and the contribution of risk governance to a sustainable orientation of companies