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Forschung 2018
(2018)
BACKGROUND:
Shear-induced conformational changes of von Willebrand factor (vWF) may be responsible for coagulation disorder and clot formation inside membrane oxygenators (MOs) during extracorporeal membrane oxygenation (ECMO) therapy.
OBJECTIVE:
The aim was to identify vWF structures inside clinically used MOs and employ computational fluid dynamics to verify the corresponding flow conditions.
METHODS:
Samples from gas exchange membranes (GEM) from MOs were analysed for accumulations of vWF and P-selectin-positive platelets using immunofluorescence techniques. Streamlines and shear rates of the flow around GEMs were computed using a laminar steady Reynolds-Averaged-Navier-Stokes approach.
RESULTS:
Most samples were colonized with equally distributed leukocytes, integrated in thin cobweb-like vWF-structures. Only 25 % of the samples showed extended accumulations of vWF. Computed streamlines showed considerable cross flow between interconnected neighbouring channels. Stagnation points were non-symmetric and contact faces were washed around closely. The occurring maximum shear rates ranged from 2,500 to 3,000 1/s.
CONCLUSIONS:
If pronounced vWF structures are present, shape and extent match the flow computations well. Computed shear rates bear a critical degree of uncertainty due to the improper viscosity model. If flow conditions inside the MO were sufficient to affect vWF, a more consistent distribution of vWF across the samples should be present.
Clot formation within membrane oxygenators (MOs) remains a critical problem during extracorporeal membrane oxygenation (ECMO). The composition of the clots-in particular, the presence of von Willebrand factor (vWF)-may be an indicator for prevalent nonphysiological flow conditions, foreign body reactions, or coagulation abnormalities in critically ill patients. Mats of interwoven gas exchange fibers from randomly collected MOs (PLS, Maquet, Rastatt, Germany) of 21 patients were stained with antibodies (anti-vWF and anti-P-selectin) and counterstained with 4 ',6-diamidino-2-phenylindole. The extent of vWF-loading was correlated with patient and technical data. While 12 MOs showed low vWF-loadings, 9 MOs showed high vWF-loading with highest accumulations close to crossing points of adjacent gas fibers. The presence and the extent of vWF-fibers/"cobwebs," leukocytes, platelet-leukocyte aggregates (PLAs), and P-selectin-positive platelet aggregates were independent of the extent of vWF-loading. However, the highly loaded MOs were obtained from patients with a significantly elevated SOFA score, severe thrombocytopenia, and persistent liver dysfunction. The coagulation abnormalities of these critically ill patients may cause an accumulation of the highly thrombogenic and elongated high-molecular-weight vWF multimers in the plasma which will be trapped in the MOs during the ECMO therapy.
Blood flow in channels of varying diameters <500μm exhibits strong non-linear effects. Multiphase finite volume approaches are feasible, but still computationally costly. Here, the feasibility of applying convolutional neural networks for blood flow prediction in artificial lungs is investigated. Training targets are precomputed using an Eulerian two-phase approach. To match with experimental data, the interphase drag and lift, as well as intraphase shear-thinning are adapted. A recursively branching regression network and convolution/deconvolution networks with plain skip connections and densely connected skips are investigated. A priori knowledge is incorporated in the loss functional to prevent the network from learning non-physical solutions. Inference from neural networks is approximately six orders of magnitude faster than the classical finite volume approach. Even if resulting in comparably coarse flow fields, the neural network predictions can be used as close to convergence initial solutions greatly accelerating classical flow computations.
Modelling blood flow an shear induced coagulation in membraene oxygenators (MO) is challenging. The relevant geometry of oxygenator fibers (OF) and chaining threads is complex and spans several length scales. In relevant scales and regimes blood shows several significant non-Newtonian effects. Existing models are only capable of accounting for some, but not all relevant effects. Additionally, coagulation processes are influencing fluid properties and geometry significantly. Due to the enormous size of the discretised geometries highly detailed viscosity and coagulation properties of blodd flow in MOs. First step is to find a gemoetry dependent viscosity representation on basis of parametric micro channel experiments with anti-coagulated blood. Next step is a statistic coagulation model, based on micro channel experiments with human (re-calcified citrated) whole blood an evaluation of clinically used osygenators. Since shear rate dependent (i.e. viscosity dependet) coagulation in return influences the viscosity, a combined model with suitable implementation in a RANS framework is necessary. Towards this end, micro channel experiments with new and used single OFs triggering coagulation are performed. Structures of multimeric von Willebrand fibers (vWF), as indicator for shear induced coagulation, are compared to computed and measured flow conditions, using immunofluorescence microscopy, RANS-computations and µPIV, respectively. Preliminary examinations in clinically used MOs show good agreement between occurring structures of vWF, cell depositions and computed flow patterns (geometry form µCT-Scans). However, computed shear rates might be to low to actually trigger activation of vWF. The complex geometry of MOs results in huge meshes, which makes RANS with statistical modelling of viscosity and coagulation a reasonable approach. Towards this end, experimental data on micro channel level with evaluation on real application level is crucial. Especially regarding clotting processes, micro fluidic experiments are powerful research tool.
Convolutional Neural Networks for Approximation of Internal Non-Newtonian Multiphase Flow Fields
(2021)
Neural networks (NNs) as an alternative method for universal approximation of differential equations have proven to be computationally efficient and still sufficiently accurate compared to established methods such as the finite volume method (FVM). Additionally, analysing weights and biases can give insights into the underlying physical laws. FVM and NNs are both based upon spacial discretisation. Since a Cartesian and equidistant grid is a raster graphics, image-to-image regression techniques can be used to predict phase velocity fields as well as particle and pressure distributions from simple mass flow boundary conditions. The impact of convolution layer depth and number of channels of a ConvolutionDeconvolution Regression Network (CDRN), on prediction performance of internal non-Newtownian multiphase flows is investigated. Parametric training data with 2055 sets is computed using FVM. To capture significant non-Newtownian effects of a particle-laden fluid (e.g. blood) flowing through small and non-straight channels, an Euler-Euler multiphase approach is used. The FVM results are normalized and mapped onto an equidistant grid as supervised learning target. The investigated NNs consist of n= {3, 5, 7} corresponding encoding/decoding blocks and different skip connections. Regardless of the convolution depth (i.e. number of blocks), the deepest spacial down-sampling via strided convolution is adjusted to result in a 1 × 1 × f · 2nfeature map, with f = {8, 16, 32}. The prediction performance expressed is as channel-averaged normalized root mean squared error (NRMSE). With a NRMSE of < 2 · 10-3, the best preforming NN has f = 32 initial feature maps, a kernel size of k = 4, n = 5 blocks and dense skip connections. Average inference time from this NN takes < 7 · 10-3s. Worst accuracy at NRMSE of approx 9 · 10-3is achieved without any skips, at k = 2, f = 16 and n = 3, but deployment takes only < 2 · 10-3s Given an adequate training, the prediction accuracy improves with convolution depth, where more features have higher impact on deeper NNs. Due to skip connections and batch normalisation, training is similarly efficient, regardless of the depth. This is further improved by blocks with dense connections, but at the price of a drastically larger model. Depending on geometrical complexity, spacial resolution is critical, as it increases the number of learnables and memory requirements massively.
Introduction
Shear induced multimerisation of von-Willebrand-factor (vWF) is supposed to play an important role in coagulation inside extracorporeal membrane oxygenators. However, there is no proof that links observed vWF structures to computed or measured flow conditions.
Methods
The structures of multimeric vWF fibers, observed in clinically used membrane oxygenators is examined using immunofluorescence microscopy (IFM) using Carstairs’ staining method (positive ethics committee vote). The flow around the membrane fibres inside the oxygenator is investigated in terms of shear rate, wall shear velocity and streamlines by using CFD (RANS, Carreau-Yasuda viscosity, geometry remodelled after high-resolution µCT-scans). By interpreting the histological and numerical results in this common context, indications for shear induced coagulation mechanisms can be identified.
Results
The fibre structures of multimeric vWF build regular but not exactly symmetric formations around the contact face (CF) between the crosswise stacked oxygenator fibres (OF), see fig.1B, vWF marked red. Annular around the CF arranged, cells are likely to be found, see fig.1B, nuclei marked blue.
The computed streamlines around the OF show attached flow around the circular fibres. However, the irregular arrangement of real OF produce considerable cross flow between the interconnected neighbouring channels, in contrast to previous 2D-simulations. Thus, the CF are washed around closely by blood, also from neighbouring channels. The wall shear velocity streamlines form regular, slightly asymmetric shapes around the contact faces. The occurring maximum shear rates are in the range of 1,000 1/s.
Discussion
The shapes of vWF structures found in clinically used oxygenators match the computational results in terms of wall shear velocity and streamlines well. The accumulation of cells close to the CF can also be explained by fluid mechanics, as there are small shear gradients and slow velocities. However, occurring shear rates between OFs are too low to trigger multimerisation of vWF. That raises the question where in the circuit the actual activation of vWF is started and how, at least partly chained, vWF multimeres are attracted towards the OF surface. A next step will be the investigation of the actual shear rate triggered (or mediated) multimerisation of vWF. Towards this end, microfluidic experiments with shear triggered coagulation will be performed. Also of big interest is the computation of the flow situation in the oxygenator in proximity to chaining threads, which have been ignored in computations so far. However, first a realistic representation of the effective viscosity in computations is needed, which is not available yet.
Clot formation within membrane oxygenators (MOs) remains a critical problem during extracorporeal membrane oxygenation (ECMO). The composition of the clots—in particular, the presence of von Willebrand factor (vWF)—may be an indicator for prevalent nonphysiological flow conditions, foreign body reactions, or coagulation abnormalities in critically ill patients. Mats of interwoven gas exchange fibers from randomly collected MOs (PLS, Maquet, Rastatt, Germany) of 21 patients were stained with antibodies (anti‐vWF and anti‐P‐selectin) and counterstained with 4′,6‐diamidino‐2‐phenylindole. The extent of vWF‐loading was correlated with patient and technical data. While 12 MOs showed low vWF‐loadings, 9 MOs showed high vWF‐loading with highest accumulations close to crossing points of adjacent gas fibers. The presence and the extent of vWF‐fibers/“cobwebs,” leukocytes, platelet–leukocyte aggregates (PLAs), and P‐selectin‐positive platelet aggregates were independent of the extent of vWF‐loading. However, the highly loaded MOs were obtained from patients with a significantly elevated SOFA score, severe thrombocytopenia, and persistent liver dysfunction. The coagulation abnormalities of these critically ill patients may cause an accumulation of the highly thrombogenic and elongated high‐molecular‐weight vWF multimers in the plasma which will be trapped in the MOs during the ECMO therapy.
Coagulative disorders, especially clotting during extracorporeal membrane oxygenation, are frequent complications. Direct visualization and analysis of deposits in membrane oxygenators using computed tomography (CT) may provide an insight into the underlying mechanisms causing thrombotic events. However, the already established multidetector CT1 (MDCT) method shows major limitations. Here, we demonstrate the feasibility of applying industrial micro-CT (μCT) to circumvent these restrictions. Three clinically used membrane oxygenators were investigated applying both MDCT and μCT.
The scans were analyzed in terms of clot volume and local clot distribution. As validation, the clot volume was also determined from the fluid volume, which could be filled into the respective used oxygenator compared to a new device. In addition, cross-sectional CT images were compared with crosscut oxygenators. Based on the μCT findings, a morphological measure (sphericity) for assessing clot structures in membrane oxygenators is introduced. Furthermore, by comparing MDCT and μCT results, an augmentation of the MDCT method is proposed, which allows for improved clot volume determination in a clinical setting.