Feng Huang, Seyed Ali Hosseini, Gabor Janiga, Dominique Thévenin
Flow fluctuations have recently emerged as a promising hemodynamic metric for understanding the rupture risk of intracranial aneurysms. Several investigations have reported in the literature corresponding flow instabilities using established computational fluid dynamics tools. In this study, the occurrence of flow fluctuations is investigated using either Newtonian or non-Newtonian fluid models in patient-specific intracranial aneurysms using high-resolution lattice Boltzmann method simulations. Flow instabilities are quantified by computing power spectral density, proper orthogonal decomposition and spectral entropy, and fluctuating kinetic energy of velocity fluctuations. Furthermore, these hemodynamic parameters are compared between the ruptured and unruptured aneurysms. Our simulations reveal that the pulsatile inflow through the neck in a ruptured aneurysm is subject to a hydrodynamic instability leading to high-frequency fluctuations around the rupture position throughout the entire cardiac cycle. At other locations, the flow instability is only observed during the deceleration phase; typically, the fluctuations begin there just after peak systole, gradually decay, and the flow returns to its original, laminar pulsatile state during diastole. In the unruptured aneurysm, there is only minimal difference between Newtonian and non-Newtonian results. In the ruptured case, using the non-Newtonian model leads to a considerable increase of the fluctuations within the aneurysm sac.
Tanya Neeraj, Christin Velten, Gabor Janiga, Katharina Zähringer, Reza Namdar, Fathollah Varnik, Dominique Thévenin, Seyed Ali Hosseini
This study aims to validate the lattice Boltzmann method and assess its ability to accurately describe the behavior of gaseous flows in packed beds. To that end, simulations of a model packed bed reactor, corresponding to an experimental bench, are conducted, and the results are directly compared with experimental data obtained by Particle Image Velocimetry measurements. It is found that the lattice Boltzmann solver exhibits very good agreement with experimental measurements. Then, the numerical solver is further used to analyze the effect of the number of packing layers on the flow structure and to determine the minimum bed height above which the changes in flow structure become insignificant. Finally, flow fluctuations in time are discussed. The findings of this study provide valuable insights into the behavior of the gas flow in packed bed reactors, opening the door for further investigations involving additionally chemical reactions, as found in many practical applications.
Soumick Chatterjee, Franziska Gaidzik, Alessandro Sciarra, Hendrik Mattern, Gábor Janiga, Oliver Speck, Andreas Nürnberger, Sahani Pathiraja
In the domain of medical imaging, many supervised learning based methods for segmentation face several challenges such as high variability in annotations from multiple experts, paucity of labelled data and class imbalanced datasets. These issues may result in segmentations that lack the requisite precision for clinical analysis and can be misleadingly overconfident without associated uncertainty quantification. This work proposes the PULASki method as a computationally efficient generative tool for biomedical image segmentation that accurately captures variability in expert annotations, even in small datasets. This approach makes use of an improved loss function based on statistical distances in a conditional variational autoencoder structure (Probabilistic UNet), which improves learning of the conditional decoder compared to the standard cross-entropy particularly in class imbalanced problems. The proposed method was analysed for two structurally different segmentation tasks (intracranial vessel and multiple sclerosis (MS) lesion) and compare our results to four well-established baselines in terms of quantitative metrics and qualitative output. These experiments involve class-imbalanced datasets characterised by challenging features, including suboptimal signal-to-noise ratios and high ambiguity. Empirical results demonstrate the PULASKi method outperforms all baselines at the 5\% significance level. Our experiments are also of the first to present a comparative study of the computationally feasible segmentation of complex geometries using 3D patches and the traditional use of 2D slices. The generated segmentations are shown to be much more anatomically plausible than in the 2D case, particularly for the vessel task.
Samuel Voss, Philipp Berg, Janneck Stahl, Daniel Behme, Gabor Janiga, Rodrigo Lima de Miranda, Eckhard Quandt, Prasanth Velvaluri
Flow diversion has become a key treatment modality for selected intracranial aneurysms, relying on the principle that a dense mesh of stent wires disrupts blood flow into the aneurysm sac, promoting thrombosis and vessel reconstruction. Despite its clinical success, a subset of patients experiences incomplete occlusion or complications. This study investigates innovative helical thin-film implants (HTFIs), aiming to evaluate their flow-diverting efficacy. Highly resolved computational fluid dynamics simulations were performed on two representative patient-specific aneurysm models. Two HTFI design variants were tested at various configurations (two rolling angles and three deployment positions). A total of 28 unsteady hemodynamic simulations were performed, comparing six hemodynamically relevant parameters against the pre-interventional state and a conventional braided flow diverter. The HTFIs induced significant changes in intra-aneurysmal flow. Both designs performed similarly overall, with the shorter configurations (smaller rolling angle) demonstrating superior efficacy. These achieved average hemodynamic reductions of 52.2% and 58.4%, outperforming the benchmark braided flow diverter device (47.4%). Sensitivity to positioning was modest, with the best configuration showing an average variation of only 5.3%, suggesting good robustness despite the helical design's heterogeneous porosity. These findings indicate that HTFIs offer promising flow-diverting capabilities. With further refinement in design and hemodynamic optimization, these implants hold potential as a next-generation alternative for the endovascular treatment of intracranial aneurysms, especially in applications requiring compatibility with smaller delivery systems.