Global Constructive Optimization of Vascular Systems

We present a framework for the construction of vascular systems based on optimality principles of theoretical physiology. Given the position and flow distribution of end points of a vascular system, we construct the topology and positions of internal nodes to complete the vascular system in a realistic manner. Optimization is driven by intravascular volume minimization with constraints derived from physiological principles. Direct optimization of a vascular system, including topological changes, is used instead of simulating vessel growth. A good initial topology is found by extracting key information from a previously optimized model with less detail. This technique is used iteratively in a multi-level approach to create a globally optimized vascular system. Most of this work was completed at Fraunhofer MeVis during the summer of 2004

Investigating the loess–palaeosol sequence of Bahlingen-Schönenberg (Kaiserstuhl), southwestern Germany, using a multi-methodological approach

Loess–palaeosol sequences (LPSs) are key archives for the reconstruction of Quaternary environmental conditions, but there is a lack of investigated records from the southern Upper Rhine Graben (southwestern Germany). To close this gap, a LPS at Bahlingen-Schönenberg was investigated at high resolution using a multi-method approach. Infrared stimulated luminescence screening reveals a major hiatus in the lower part of the LPS that according to luminescence dating is older than marine isotope stage (MIS) 4. The section above the hiatus formed by quasi-continuous loess sedimentation between ca. 34 and 27 ka, interrupted by phases of weak reductive pedogenesis. The fact that this pedogenesis is much weaker compared to corresponding horizons in the more northerly part of the Upper Rhine Graben could be due to regionally drier conditions caused by a different atmospheric circulation pattern at the time of deposition. Our results reinforce earlier notions that the major environmental shifts leading into the Last Glacial Maximum (LGM) of southern Central Europe significantly predate the transition of MIS 3 to 2 (ca. 29 ka). In particular, the last massive phase of loess accumulation started several thousand years prior to the arrival of glaciers in the foreland of the Alps, which raises questions regarding the source and transport paths of the dust. It is also noted that no loess dating to the LGM or the time thereafter was observed due to either a lack of deposition or later erosion.Löss-Paläoboden Sequenzen (LPS) sind Schlüsselarchive für die Rekonstruktion von quartären Umweltbedingungen, aber es mangelt an der Untersuchung solcher Abfolgen aus dem südlichen Oberrheingraben. Um diese Lücke zu schließen, wurde eine LPS bei Bahlingen-Schönenberg mit einem multimethodischen Ansatz hochauflösend untersucht. Die Untersuchung mit Infrarot Stimulierter Lumineszenz Screening zeigt einen Hiatus im unteren Teil der LPS, der laut Lumineszenzdatierungen älter ist als das Marine Isotopenstadium (MIS) 4. Der Abschnitt oberhalb des Hiatus bildete sich durch quasi-kontinuierliche Lössablagerung zwischen ca. 34 und 27 ka, unterbrochen von Phasen schwacher reduktiver Pedogenese. Da die Pedogenese im Vergleich zu entsprechenden Horizonten im nördlicheren Teil des Oberrheingrabens viel schwächer ausgeprägt ist, könnte dies auf regional trockenere Bedingungen zurückzuführen sein, verursacht durch ein anderes atmosphärisches Zirkulationsmuster zur Zeit der Ablagerung. Unsere Ergebnisse bestätigen frühere Annahmen, dass die großen Umweltveränderungen, die zum letzten glazialen Maximum (LGM) im südlichen Mitteleuropa führten, deutlich vor dem Übergang von MIS 3 zu 2 (ca. 29 ka) lagen. Insbesondere begann die letzte massive Phase der Lössakkumulation mehrere tausend Jahre vor der Ankunft der Gletscher im Alpenvorland, was Fragen zu den Quellen und Transportwegen des Staubs aufwirft. Es ist auch festzustellen, dass kein Löss aus dem LGM oder der Zeit danach gefunden wurde, entweder aufgrund fehlender Ablagerung oder späterer Erosion

Methodology on Quantification of Sonication Duration for Safe Application of MR Guided Focused Ultrasound for Liver Tumour Ablation

Background and objective Magnetic Resonance Guided Focused Ultrasound (MRgFUS) for liver tumour ablation is a challenging task due to motion caused by breathing and occlusion due the ribcage between the transducer and the tumour. To overcome these challenges, a novel system for liver tumour ablation during free breathing has been designed. Methods The novel TRANS-FUSIMO Treatment System (TTS, EUFP7) interacts with a Magnetic Resonance (MR) scanner and a focused ultrasound transducer to sonicate to a moving target in liver. To meet the requirements of ISO 13485; a quality management system for medical device design, the system needs to be tested for certain process parameters. The duration of sonication and, the delay after the sonication button is activated, are among the parameters that need to be quantified for efficient and safe ablation of tumour tissue. A novel methodology is developed to quantify these process parameters. A computerised scope is programmed in LabVIEW to collect data via hydrophone; where the coordinates of fiber-optic sensor assembly was fed into the TRANS-FUSIMO treatment software via Magnetic Resonance Imaging (MRI) to sonicate to the tip of the sensor, which is synchronised with the clock of the scope, embedded in a degassed water tank via sensor assembly holder. The sonications were executed for 50 W, 100 W, 150 W for 10 s to quantify the actual sonication duration and the delay after the emergency stop by two independent operators for thirty times. The deviation of the system from the predefined specs was calculated. Student's-T test was used to investigate the user dependency. Results The duration of sonication and the delay after the sonication were quantified successfully with the developed method. TTS can sonicate with a maximum deviation of 0.16 s (Std 0.32) from the planned duration and with a delay of 14 ms (Std 0.14) for the emergency stop. Student's T tests indicate that the results do not depend on operators (p > .05). Conclusion The evidence obtained via this protocol is crucial for translation- of-research into the clinics for safe application of MRgFUS. The developed protocol could be used for system maintenance in compliance with quality systems in clinics for daily quality assurance routines

Level set and PDE methods for visualization

Notes from IEEE Visualization 2005 Course #6, Minneapolis, MN, October 25, 2005. Retrieved 3/16/2006 from http://www.cs.drexel.edu/~david/Papers/Viz05_Course6_Notes.pdf.Level set methods, an important class of partial differential equation (PDE) methods, define dynamic surfaces implicitly as the level set (isosurface) of a sampled, evolving nD function. This course is targeted for researchers interested in learning about level set and other PDE-based methods, and their application to visualization. The course material will be presented by several of the recognized experts in the field, and will include introductory concepts, practical considerations and extensive details on a variety of level set/PDE applications. The course will begin with preparatory material that introduces the concept of using partial differential equations to solve problems in visualization. This will include the structure and behavior of several different types of differential equations, e.g. the level set, heat and reaction-diffusion equations, as well as a general approach to developing PDE-based applications. The second stage of the course will describe the numerical methods and algorithms needed to implement the mathematics and methods presented in the first stage, including information on implementing the algorithms on GPUs. Throughout the course the technical material will be tied to applications, e.g. image processing, geometric modeling, dataset segmentation, model processing, surface reconstruction, anisotropic geometric diffusion, flow field post-processing and vector visualization. Prerequisites: Knowledge of calculus, linear algebra, computer graphics, visualization, geometric modeling and computer vision. Some familiarity with differential geometry, differential equations, numerical computing and image processing is strongly recommended, but not required

MRI-based computational hemodynamics in patients with aortic coarctation using the lattice Boltzmann methods : Clinical validation study

PURPOSE: To introduce a scheme based on a recent technique in computational hemodynamics, known as the lattice Boltzmann methods (LBM), to noninvasively measure pressure gradients in patients with a coarctation of the aorta (CoA). To provide evidence on the accuracy of the proposed scheme, the computed pressure drop values are compared against those obtained using the reference standard method of catheterization. MATERIALS AND METHODS: Pre‐ and posttreatment LBM‐based pressure gradients for 12 patients with CoA were simulated for the time point of peak systole using the open source library OpenLB. Four‐dimensional (4D) flow‐sensitive phase‐contrast MRI at 1.5 Tesla was used to acquire flow and to setup the simulation. The vascular geometry was reconstructed using 3D whole‐heart MRI. Patients underwent pre‐ and postinterventional pressure catheterization as a reference standard. RESULTS: There is a significant linear correlation between the pretreatment catheter pressure drops and those computed based on the LBM simulation, [Formula: see text] , [Formula: see text]. The bias was ‐0.58 ± 4.1 mmHg and was not significant ( [Formula: see text] with a 95% confidence interval (CI) of ‐3.22 to 2.06. For the posttreatment results, the bias was larger and at ‐2.54 ± 3.53 mmHg with a 95% CI of ‐0.17 to ‐4.91 mmHg. CONCLUSION: The results indicate a reasonable agreement between the simulation results and the catheter measurements. LBM‐based computational hemodynamics can be considered as an alternative to more traditional computational fluid dynamics schemes for noninvasive pressure calculations and can assist in diagnosis and therapy planning. Level of Evidence: 3 J. Magn. Reson. Imaging 2017;45:139–146