EC78-1737 Broadleaf Trees for Nebraska

This extension circular shows and describes broadleaf trees that will grow in Nebraska. It should prove valuable when selecting a tree best suited for a specific area and purpose. Most of this publication is devoted to detailed descriptions of tree species. In addition, the main points of tree placement, tree planting and tree care are discussed

Optimizing imaging and reducing radiation exposure during complex aortic endovascular procedures

Improvements in endovascular technologies and development of custom-made fenestrated and branched endografts currently allow clinicians to treat complex aortic lesions such as thoraco-abdominal and aortic arch aneurysms once treatable with open repair only. These advances are leading to an increase in the complexity of endovascular procedures which can cause long operation times and high levels of radiation exposure. This in turn places pressure on the vascular surgery community to display more superior interventional skills and radiological practices. Advanced imaging technology in this context represents a strong pillar in the treatment toolbox for delivering the best care at the lowest risk level. Delivering the best patient care while managing the radiation and iodine contrast media risks, especially in frail and renal impaired populations, is the challenge aortic surgeons are facing. Modern hybrid rooms are equipped with a wide range of new imaging applications such as fusion imaging and cone-beam computed tomography (CBCT). If these technologies contribute to reducing radiation, they can be complex and intimidating to master. The aim of this review is to discuss the fundamentals of good radiological practices and to describe the various imaging tools available to the aortic surgeon, both those available today and those we anticipate will be available in the near future, from equipment to software, to perform safe and efficient complex endovascular procedures

Functional MRI-derived priors for solving the EEG/MEG inverse problem

Introduction Because of their excellent temporal accuracy (of the order of 1 ms), electroencephalography (EEG) and magnetoencephalography (MEG) provide the most relevant data for studying the temporal dynamics of brain activity. However, difficulties arise when trying to localize the electromagnetic sources of this activity from EEG/MEG scalp recordings. This mathematical inverse problem is indeed ill-posed and largely underdetermined. An efficient way of constraining the problem and thereby reducing the solution space is to perform a regularization. By taking some anatomical and/or functional a priori knowledge into account, the regularization process may yield a more consistent localization of the electromagnetic sources. Anatomical priors have already been used (e.g., [1]) but only few regularization methods (e.g., [2]) have introduced functional information so far. In this study, we propose a new multimodal approach for solving the EEG/MEG inverse problem. This method involves