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- Fischbach, M., et al.
(author)
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The influence of peritoneal surface area on dialysis adequacy
- 2005
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In: Perit Dial Int. - 0896-8608. ; 25 Suppl 3
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Journal article (peer-reviewed)abstract
- In children, the prescription of peritoneal dialysis is based mainly on the choice of the peritoneal dialysis fluid, the intraperitoneal fill volume (mL/m2 body surface area (BSA)], and the contact time. The working mode of the peritoneal membrane as a dialysis membrane is more related to a dynamic complex structure than to a static hemodialyzer. Thus, the peritoneal surface area impacts on dialysis adequacy. In fact, the peritoneal surface area may be viewed as composed of three exchange entities: the anatomic area, the contact area, and the vascular area. First, in infants, the anatomic area appears to be two-fold larger than in adults when expressed per kilogram body weight. On the other hand, the anatomic area becomes independent of age when expressed per square meter BSA. Therefore, scaling of the intraperitoneal fill volume by BSA (m2) is necessary to prevent a too low ratio of fill volume to exchange area, which would result in a functional "hyperpermeable" peritoneal exchange. Second, the contact area, also called the wetted membrane, is only a portion of the anatomic area, representing 30% to 60% of this area in humans, as measured by computed tomography. Both posture and fill volume may affect the extent of recruitment of contact area. Finally, the vascular area is influenced by the availability of both the anatomic area and the recruited contact area. This surface is governed essentially by both peritonealvascular perfusion, represented by the mesenteric vascular flow and, hence, by the number of perfused capillaries available for exchange. This vascular area is dynamically affected by different factors, such as composition of the peritoneal fluid, the fill volume, and the production of inflammatory agents. Peritoneal dialysis fluids that will be developed in the future for children should allow an optimization of the fill volume owing to a better tolerance in terms of lower achieved intraperitoneal pressure for a given fill volume. Moreover, future peritoneal dialysis fluids should protect the peritoneal membrane from hyperperfusion (lower glucose degradation products).
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- Seidemo, Anina, et al.
(author)
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Tissue response curve shape analysis of dynamic glucose enhanced (DGE) and dynamic contrast enhanced (DCE) MRI in patients with brain tumor
- 2023
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In: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 36:6
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Journal article (peer-reviewed)abstract
- Dynamic glucose enhanced (DGE) MRI is used to study the signal intensity time course (tissue response curve) after D-glucose injection. D-glucose has potential as a biodegradable alternative or complement to gadolinium-based contrast agents, with DGE being comparable to dynamic contrast enhanced (DCE) MRI. However, the tissue uptake kinetics as well as the detection methods of DGE differ from DCE, and it is relevant to compare these techniques in terms of spatiotemporal enhancement patterns. This study aims to develop a DGE analysis method based on tissue response curve shapes, and to investigate whether DGE MRI provides similar or complementary information to DCE MRI. Eleven patients with suspected gliomas were studied. Tissue response curves were measured for DGE and DCE MRI at 7 tesla and the area under curve (AUC) was assessed. Seven types of response curve shapes were postulated and subsequently identified by deep learning to create color-coded “curve maps” showing the spatial distribution of different curve types. DGE AUC values were significantly higher in lesions than in normal tissue (p
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| 7. |
- Seidemo, Anina, et al.
(author)
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Towards robust glucose chemical exchange saturation transfer imaging in humans at 3 T: Arterial input function measurements and the effects of infusion time
- 2022
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In: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 35:2, s. 4624-4624
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Journal article (peer-reviewed)abstract
- Dynamic glucose-enhanced (DGE) magnetic resonance imaging (MRI) has shown potential for tumor imaging using D-glucose as a biodegradable contrast agent. The DGE signal change is small at 3 T (around 1 and accurate detection is hampered by motion. The intravenous D-glucose injection is associated with transient side effects that can indirectly generate subject movements. In this study, the aim was to study DGE arterial input functions (AIFs) in healthy volunteers at 3 T for different scanning protocols, as a step towards making the glucose chemical exchange saturation transfer (glucoCEST) protocol more robust. Two different infusion durations (1.5 and 4.0 min) and saturation frequency offsets (1.2 and 2.0 ppm) were used. The effect of subject motion on the DGE signal was studied by using motion estimates retrieved from standard retrospective motion correction to create pseudo-DGE maps, where the apparent DGE signal changes were entirely caused by motion. Furthermore, the DGE AIFs were compared with venous blood glucose levels. A significant difference (p = 0.03) between arterial baseline and postinfusion DGE signal was found after D-glucose infusion. The results indicate that the measured DGE AIF signal change depends on both motion and blood glucose concentration change, emphasizing the need for sufficient motion correction in glucoCEST imaging. Finally, we conclude that a longer infusion duration (e.g. 3–4 min) should preferably be used in glucoCEST experiments, because it can minimize the glucose infusion side effects without negatively affecting the DGE signal change.
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- Harth, E. M., et al.
(author)
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The effect of macromolecular architecture in nanomaterials : A comparison of site isolation in porphyrin core dendrimers and their isomeric linear analogues
- 2002
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In: Journal of the American Chemical Society. - : American Chemical Society (ACS). - 0002-7863 .- 1520-5126. ; 124:15, s. 3926-3938
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Research review (peer-reviewed)abstract
- The influence of macromolecular architecture on the physical properties of polymeric materials has been studied by comparing poly(benzyl ether) dendrons with their exact linear analogues. The results clearly confirm the anticipation that dendrimers are unique when compared to other architectures. Physical properties, from hydrodynamic volume to crystallinity, were shown to be different, and in a comparative study of core encapsulation in macromolecules of different architecture, energy transduction from the polymer backbone to a porphyrin core was shown to be different for dendrimers as compared to that of isomeric four- or eight-arm star polymers. Fluorescence excitation revealed strong, morphology dependent intramolecular energy transfer in the three macromolecular isomers investigated, Even at high generations, the dendrimers exhibited the most efficient energy transfer, thereby indicating that the dendritic architecture affords superior site isolation to the central porphyrin it surrounds.
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- Helms, Sandra, et al.
(author)
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Classification of Methods for the Indication of Change Propagation - a Literature Review
- 2014
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In: Proceedings of International Design Conference - Design 2014.
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Conference paper (peer-reviewed)abstract
- In today’s globalized and competitive world, product development processes need to be innovative, effective and efficient. Engineering changes (EC) are an unavoidable part of product development and are both source of innovation and costs. Every innovation derives from a change, but at the same time unnecessary and late changes can be the reason for sky-rocketing costs [Fricke 2000]. Therefore, companies have to find a balance between having too many changes which are costly and time-consuming, and having too few which might lead to missed opportunities with regards to improving quality and being innovative. One particular aspect of changes in engineering design is their risk of propagating further through the product. Engineering change propagation (ECP) can occur wherever there are dependencies within the product and thus a change to one part of the system will trigger subsequent changes in other parts [Yang 2011]. To tackle the problem of unwanted ECP, various methods that aim at supporting designers with the assessment of alternative change options have been developed in recent years. These methods, however, often apply to different scopes and intend at answering different questions. There are academic papers that include a listing and discussion of the various methods that are out in literature such as the one from Jaratt et al. (2011). Moreover, authors that introduce their own method in their paper often refer to other already existing methods. However, most of these papers not exclusively consider the methods that are able to deal with ECP but rather consider the broader field of EC. Also, there is no classified overview in literature that provides deeper insights into what aspects of the various methods differ or are similar. Having such a classified overview at hand with methods that can handle ECP a quicker comparison and assessment of those methods can take place and can therefore save precious time. Hence, this work’s objective is to find methods that can indicate change propagation and to analyse how these differ to each. Therefore, the research questions to be answered are; (RQ 1) what methods in literature to EC propagation do already exist and (RQ 2) based on the findings from RQ 1, how do the so found methods differ to each other?Based on the definitions from Jarratt et al. [Jarratt 2011] and Conrat [Conrat 1998], ECs are in this work defined as modifications in forms, fits, materials, dimensions, functions, drawings or software of a product or component that has already been released during the production design process. ECs include the connected process changes and can be of any size or type, can involve any people, and can take any length of time. EC propagation, based on Tang et al.’s [Tang 2008] and Koh et al.’s [Koh 2012] definition, originates from the relationships or dependencies between items, such as between components, parameters, functions, etc., and describes the process by which a change to one part or element of an existing system configuration or design results in one or more additional changes to the system, when those changes would not have otherwise been required.
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| 12. |
- Helms, Sandra, et al.
(author)
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Procedure Model for the Indication of Change Propagation
- 2014
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In: Proceedings of International Design Conference - Design 2014.
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Conference paper (peer-reviewed)abstract
- Engineering changes (EC) occur within the product development and account for up to 50% of its capacities [Lindemann 1998]. Despite the fact that ECs are necessary to improve a product’s quality and that they often are the source for innovation [Fricke 2000], ECs are also costly and bear the risk of propagating further through the product. Propagation occur when a change to one part of the system will trigger subsequent changes in other parts [Yang 2011]. In recent years, many methods on change propagation have been developed which aim at supporting designers assessing alternative change options. These methods, however, often apply to different scopes and intend at answering different questions, which makes it difficult to know which one to choose for one’s own specific situation. For instance, some methods aim at indicating potential change propagation paths so that product designers can see what other components are to be affected in the course of the initiated change, others, on the contrary, aim at calculating the risk for a change to propagate. Some methods are delimited to certain stages during product development such as the conceptual design phase, whereas others can be applied throughout all product development stages. Some methods map physical components, whereas others are able to map functional or parameter linkages in a product, etc. Hence, the methods developed in recent years differ to each other with regards to various aspects such as purpose or expected outcome. This means that, depending on the situation and intention of the product developer, not all methods are equally suitable. Thus, product developers who find themselves in a situation where alternative ways of implementing a change in order to meet the new requirement or to correct faults are available might question themselves what methods are out there that can support them and which of them is the most suitable. Therefore, this work’s objective is to develop a procedure model for product developers that can be used as a guide to decide what method for EC propagation fits best to their specific application environment and shall therefore be chosen.This paper’s definition of ECs is based on the definitions from Jarratt et al. [Jarratt 2011] and Conrat [Conrat 1998]: ECs are modifications in forms, fits, materials, dimensions, functions, drawings or software of a product or component that has already been released during the production design process. ECs include the connected process changes and can be of any size or type, can involve any people, and can take any length of time. This paper’s definition of EC propagation is based on Tang et al.’s [Tang 2008] and Koh et al.’s [Koh 2012] definition: EC propagation originates from the relationships or dependencies between items, such as between components, parameters, functions, etc., and describes the process by which a change to one part or element of an existing system configuration or design results in one or more additional changes to the system, when those changes would not have otherwise been required.
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- Knutsson, Linda, et al.
(author)
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Arterial Input Functions and Tissue Response Curves in Dynamic Glucose-Enhanced (DGE) Imaging: Comparison Between glucoCEST and Blood Glucose Sampling in Humans
- 2018
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In: Tomography : a journal for imaging research. - : MDPI AG. - 2379-1381. ; 4:4, s. 164-171
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Journal article (peer-reviewed)abstract
- Dynamic glucose-enhanced (DGE) imaging uses chemical exchange saturation transfer magnetic resonance imaging to retrieve information about the microcirculation using infusion of a natural sugar (D-glucose). However, this new approach is not yet well understood with respect to the dynamic tissue response. DGE time curves for arteries, normal brain tissue, and cerebrospinal fluid (CSF) were analyzed in healthy volunteers and compared with the time dependence of sampled venous plasma blood glucose levels. The arterial response curves (arterial input function [AIF]) compared reasonably well in shape with the time curves of the sampled glucose levels but could also differ substantially. The brain tissue response curves showed mainly negative responses with a peak intensity that was of the order of 10 times smaller than the AIF peak and a shape that was susceptible to both noise and partial volume effects with CSF, attributed to the low contrast-to-noise ratio. The CSF response curves showed a rather large and steady increase of the glucose uptake during the scan, due to the rapid uptake of D-glucose in CSF. Importantly, and contrary to gadolinium studies, the curves differed substantially among volunteers, which was interpreted to be caused by variations in insulin response. In conclusion, while AIFs and tissue response curves can be measured in DGE experiments,partial volume effects, low concentration of D-glucose in tissue, and osmolality effects between tissue and blood may prohibit quantification of normal tissue perfusion parameters. However, separation of tumor responses from normal tissue responses would most likely be feasible.
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