Numerical simulation of deformable particles in a Coulter counter

Assessing a heterogeneous model for accounting for endovascular devices in hemodynamic simulations of cerebral aneurysms

The heterogeneous model developed by Berod et al [Int J Numer Method Biomed Eng 38, 2021] for representing the hemodynamic effects of endovascular prostheses is applied to a series of 10 patient specific cerebral aneurysms, 6 being treated by flow diverters, 4 being equipped with WEBs. Two markers correlated with the medical outcome of the treatment are used to assess the potential of the model, namely the saccular mean velocity and the inflow rate at the neck of the aneurysm. The comparison with the corresponding wire-resolved simulations is very favorable in both cases, and the model-based simulations also retrieve the jetting-type flows generated downstream of the struts. Noteworthy, the very same model was used for representing the flow diverters and the WEBs, showing the versatility and robustness of the heterogeneous modeling of the devices.

New erythrocyte parameters derived from the Coulter principle relate with red blood cell properties-A pilot study in diabetes mellitus

In routine hematological instruments, blood cells are counted and sized by monitoring the impedance signals induced during their passage through a Coulter orifice. However, only signals associated with centered paths in the aperture are considered for analysis, while the rejected measurements, caused by near-wall trajectories, can provide additional information on red blood cells (RBC), as recent publications suggest. To assess usefulness of two new parameters in describing alterations in RBC properties, we performed a pilot study to compare blood samples from patients with diabetes mellitus (DM), frequent pathological condition associated with impairment in RBC deformability, versus controls. A total of 345 blood samples were analyzed: 225 in the DM group and 120 in the control group. A diagram of [Formula: see text] and [Formula: see text], the two new parameters derived from the analysis of impedancemetry pulses, was used to compare distribution of RBC subpopulations between groups. To discriminate RBC from DM and control individuals, based on our multiparametric analysis, we built a score from variables derived from [Formula: see text] matrix which showed good performances: area under the receiving operating characteristic curve 0.948 (0.920-0.970), p<0.0001; best discriminating value: negative predictive value 94.7%, positive predictive value was 78.4%. These results seem promising to approach RBC alterations in routine laboratory practice. The related potential clinically relevant outcomes remain to be investigated.

"Lollipop" particle counting immunoassay based on antigen-powered CRISPR-Cas12a dual signal amplification for the sensitive detection of deoxynivalenol in the environment and food samples

Deoxynivalenol is one of the most widely distributed mycotoxins in cereals and poses tremendous threats to the agricultural environment and public health. Therefore, it is particularly important to develop sensitive and interference-resistant deoxynivalenol analysis methods. Here, we establish a "Lollipop" particle counting immunoassay (LPCI) based on antigen-powered CRISPR-Cas12a dual signal amplification. LPCI achieves high sensitivity and accuracy through antigen-powered CRISPR-Cas dual signal amplification combined with particle counting immunoassay. This strategy not only broadens the applicability of the CRISPR-Cas system in the field of non-nucleic acid target detection; it also improves the sensitivity of particle counting immunoassay. The introduction of a polystyrene "lollipop" immunoassay carrier further enables efficiently simultaneous pre-treatment of multiple samples and overcomes complex matrix interference in real samples. The linear detection range of LPCI for deoxynivalenol was 0.1-500 ng/mL with a detection limit of 0.061 ng/mL. The platform greatly broadens the scope of the CRISPR-Cas sensor for the detection of non-nucleic acid hazards in the environment and food samples.

A heterogeneous model of endovascular devices for the treatment of intracranial aneurysms

Numerical computations of hemodynamics inside intracranial aneurysms treated by endovascular braided devices such as flow-diverters contribute to understanding and improving such treatment procedures. Nevertheless, these simulations yield high computational and meshing costs due to the heterogeneity of length scales between the dense weave of the fine struts of the device and the arterial volume. Homogeneous strategies developed over the last decade to circumvent this issue substitute local dissipations due to the wires with a global effect in the form of a pressure-drop across the device surface. However, these methods cannot accurately reproduce the flow-patterns encountered near the struts, the latter strongly dictating the intra-saccular flow environment. In this work, a versatile theoretical framework which aims at correctly reproducing the local flow heterogeneities due to the wires while keeping memory consumption, meshing and computational times as low as possible is introduced. This model reproduces the drag forces exerted by the device struts onto the fluid, thus producing local and heterogeneous effects on the flow. Extensive validation for various flow and geometric configurations using an idealized device is performed. To further illustrate the method capabilities, a real patient-specific aneurysm endovascularly treated with a flow-diverter is used, enabling quantitative comparisons with classical approaches for both intra-saccular velocities and computational costs reduction. The proposed heterogeneous model endeavors to bridge the gap between computational fluid dynamics and clinical applications and ushers in a new era of numerical treatment planning with minimally costing computational tools.

Detecting cells rotations for increasing the robustness of cell sizing by impedance measurements, with or without machine learning

The Coulter principle is a widespread technique for sizing red blood cells (RBCs) in hematological analyzers. It is based on the monitoring of the electrical perturbations generated by cells passing through a micro-orifice, in which a concentrated electrical field is imposed by two electrodes. However, artifacts associated with near-wall passages in the sensing region are known to skew the statistics for RBCs sizing. This study presents numerical results that emphasize the link between the cell flow-induced rotation in the detection area and the error in its measured volume. Based on these observations, two methods are developed to identify and reject pulses impaired by cell rotation. In the first strategy, the filtering is allowed by a metric computed directly from the waveform. In the second, a numerical database is employed to train a neural network capable of detecting if the cell has experienced a rotation, given its electrical pulse. Detecting and rejecting rotation-associated pulses are shown to provide results comparable to hydrodynamical focusing, which enforces cells to flow in the center of the orifice, the gold standard implementation of the Coulter principle.

Numerical simulation of time-resolved 3D phase-contrast magnetic resonance imaging

A numerical approach is presented to efficiently simulate time-resolved 3D phase-contrast Magnetic resonance Imaging (or 4D Flow MRI) acquisitions under realistic flow conditions. The Navier-Stokes and Bloch equations are simultaneously solved with an Eulerian-Lagrangian formalism. A semi-analytic solution for the Bloch equations as well as a periodic particle seeding strategy are developed to reduce the computational cost. The velocity reconstruction pipeline is first validated by considering a Poiseuille flow configuration. The 4D Flow MRI simulation procedure is then applied to the flow within an in vitro flow phantom typical of the cardiovascular system. The simulated MR velocity images compare favorably to both the flow computed by solving the Navier-Stokes equations and experimental 4D Flow MRI measurements. A practical application is finally presented in which the MRI simulation framework is used to identify the origins of the MRI measurement errors.

Positional dependence of particles and cells in microfluidic electrical impedance flow cytometry: origin, challenges and opportunities

Microfluidic electrical impedance flow cytometry is now a well-known and established method for single-cell analysis. Given the richness of the information provided by impedance measurements, this non-invasive and label-free approach can be used in a wide field of applications ranging from simple cell counting to disease diagnostics. One of its major limitations is the variation of the impedance signal with the position of the cell in the sensing area. Indeed, identical particles traveling along different trajectories do not result in the same data. The positional dependence can be considered as a challenge for the accuracy of microfluidic impedance cytometers. On the other hand, it has recently been regarded by several groups as an opportunity to estimate the position of particles in the microchannel and thus take a further step in the logic of integrating sensors in so-called "Lab-on-a-chip" devices. This review provides a comprehensive overview of the physical grounds of the positional dependence of impedance measurements. Then, both the developed strategies to reduce position influence in impedance-based assays and the recent reported technologies exploiting that dependence for the integration of position detection in microfluidic devices are reviewed.