Particle classification from light scattering with the scanning flow cytometer

Integrating optical and electrical sensing with machine learning for advanced particle characterization

Particle classification plays a crucial role in various scientific and technological applications, such as differentiating between bacteria and viruses in healthcare applications or identifying and classifying cancer cells. This technique requires accurate and efficient analysis of particle properties. In this study, we investigated the integration of electrical and optical features through a multimodal approach for particle classification. Machine learning classifier algorithms were applied to evaluate the impact of combining these measurements. Our results demonstrate the superiority of the multimodal approach over analyzing electrical or optical features independently. We achieved an average test accuracy of 94.9% by integrating both modalities, compared to 66.4% for electrical features alone and 90.7% for optical features alone. This highlights the complementary nature of electrical and optical information and its potential for enhancing classification performance. By leveraging electrical sensing and optical imaging techniques, our multimodal approach provides deeper insights into particle properties and offers a more comprehensive understanding of complex biological systems.

Biophysical investigation of living monocytes in flow by collaborative coherent imaging techniques

We implemented a completely label-free biophysical (morphometric and optical) property characterization of living monocytes in flow, using measurements obtained from two coherent imaging techniques: a pure light scattering approach to obtain an optical signature (OS) of cells, and a digital holography (DH) approach to achieve optical cell reconstructions in flow. A precise 3D cell alignment platform, taking advantage of viscoelastic fluid properties and microfluidic channel geometry, was used to investigate the OS of cells to achieve their refractive index, ratio of the nucleus over cytoplasm, and overall cell dimension. Further quantitative phase-contrast reconstructions by DH were employed to calculate surface area, dry mass, and biovolume of monocytes by using the OS outcomes as input parameters. The results show significantly different biophysical cell properties, confirming the possibility to differentiate monocytes from other cell classes in flow, thus avoiding chemical cell staining or labeling, which are nowadays used.

Single-cell screening of multiple biophysical properties in leukemia diagnosis from peripheral blood by pure light scattering

Histology and histopathology are based on the morphometric observations of quiescent cells. Their diagnostic potential could largely benefit from a simultaneous screening of intrinsic biophysical properties at single-cell level. For such a purpose, we analyzed light scattering signatures of individual mononuclear blood cells in microfluidic flow. In particular, we extracted a set of biophysical properties including morphometric (dimension, shape and nucleus-to-cytosol ratio) and optical (optical density) ones to clearly discriminate different cell types and stages. By considering distinctive ranges of biophysical properties along with the obtained relative cell frequencies, we can identify unique cell classes corresponding to specific clinical conditions (p < 0.01). Based on such a straightforward approach, we are able to discriminate T-, B-lymphocytes, monocytes and beyond that first results on different stages of lymphoid and myeloid leukemia cells are presented. This work shows that the simultaneous screening of only three biophysical properties enables a clear distinction between pathological and physiological mononuclear blood stream cells. We believe our approach could represent a useful tool for a label-free analysis of biophysical single-cell signatures.

Label-free analysis of mononuclear human blood cells in microfluidic flow by coherent imaging tools

The investigation of the physical properties of peripheral blood mononuclear cells (PBMC) is of great relevance, as they play a key role in regulating human body health. Here we report the possibility to characterize human PBMC in their physiological conditions in a microfluidic-based measurement system. A viscoelastic polymer solution is adopted for 3D alignment of individual cells inflow. An optical signature (OS) acquisition of each flowing cell is performed using a wide angle light scattering apparatus. Besides, a quantitative phase imaging (QPI) holographic system is employed with the aim (i) to check the position in flow of individual cells using a holographic 3D cell tracking method; and (ii) to estimate their 3D morphometric features, such as their refractive index (RI). Results obtained by combining OS and QPI have been compared with literature values, showing good agreement. The results confirm the possibility to obtain sub-micrometric details of physical cell properties in microfluidic flow, avoiding chemical staining or fluorescent labelling.

Evaluating the liquid path stability of a flow cytometer

Precision in flow cytometry depends on many factors, the first of which is accurate and stable positioning of the hydrodynamically focused cells. However, no method exists to evaluate the stability of laminar flow and single-cell flow in the flow chamber of the flow cytometer directly because of the small size of the rectangular channel of the flow chamber. In this paper, a method of high-speed particle image velocimetry is proposed to solve this problem. The velocity stability of the particles in the flow chamber is used to evaluate the flow stability of the fluid path of the flow cytometer. The side scattering images of particles are obtained by a high-speed camera. Upon exposure, cells were imaged at random positions in the flow cell, resulting in four different types of the images: blank, inadequate, normal, or overlapped. Normal images were identified utilizing a grey cluster analysis algorithm based on trapezoid whitenization weight functions. A mid-point method is applied to determine the length of the particle track at a fixed exposure time. The variation of the trajectory lengths of the normal images are used to evaluate the stability of the liquid path. Experiments are carried out to verify the feasibility of our method in which different diameter microspheres at different flow rates. The results indicate that the standard deviation and relative standard deviation of the trajectory lengths can be used as the evaluation indices of the liquid path stability of the flow cytometer. © 2016 International Society for Advancement of Cytometry.

A quantitative method for measurement of HL-60 cell apoptosis based on diffraction imaging flow cytometry technique

A quantitative method for measurement of apoptosis in HL-60 cells based on polarization diffraction imaging flow cytometry technique is presented in this paper. Through comparative study with existing methods and the analysis of diffraction images by a gray level co-occurrence matrix algorithm (GLCM), we found 4 GLCM parameters of contrast (CON), cluster shade (CLS), correlation (COR) and dissimilarity (DIS) exhibit high sensitivities as the apoptotic rates. It was further demonstrated that the CLS parameter correlates significantly (R(2) = 0.899) with the degree of nuclear fragmentation and other three parameters showed a very good correlations (R(2) ranges from 0.69 to 0.90). These results demonstrated that the new method has the capability for rapid and accurate extraction of morphological features to quantify cellular apoptosis without the need for cell staining.

Analysis of cellular objects through diffraction images acquired by flow cytometry

It was found that the diffraction images acquired along the side scattering directions with objects in a cell sample contain pattern variations at both the global and local scales. We show here that the global pattern variation is associated with the categorical size and morphological heterogeneity of the imaged objects. An automated image processing method has been developed to separate the acquired diffraction images into three types of global patterns. Combined with previously developed method for quantifying local texture pattern variations, the new method allows fully automated analysis of diffraction images for rapid and label-free classification of cells according to their 3D morphology.

Optofluidics incorporating actively controlled micro- and nano-particles

The advent of optofluidic systems incorporating suspended particles has resulted in the emergence of novel applications. Such systems operate based on the fact that suspended particles can be manipulated using well-appointed active forces, and their motions, locations and local concentrations can be controlled. These forces can be exerted on both individual and clusters of particles. Having the capability to manipulate suspended particles gives users the ability for tuning the physical and, to some extent, the chemical properties of the suspension media, which addresses the needs of various advanced optofluidic systems. Additionally, the incorporation of particles results in the realization of novel optofluidic solutions used for creating optical components and sensing platforms. In this review, we present different types of active forces that are used for particle manipulations and the resulting optofluidic systems incorporating them. These systems include optical components, optofluidic detection and analysis platforms, plasmonics and Raman systems, thermal and energy related systems, and platforms specifically incorporating biological particles. We conclude the review with a discussion of future perspectives, which are expected to further advance this rapidly growing field.

Easy method to determine refractive indices of microspheres and in micro-regions of inhomogeneous media

We describe an innovative method which can accurately determine the refractive index (RI) of individual microspheres by immersing the microspheres in a medium and analyzing their phase-contrast microscopic images. Compared with the current techniques for microsphere RI measurement, the method has several advantages: it is simple and easy and it cannot only measure the RI of each individual microsphere but also perform measurement simultaneously on all the microspheres in the same field of view. In measurement, microspheres are not required to be suspended in a specific liquid but in any medium with known RI which is appropriate for the microspheres or even just in atmosphere. By using microspheres with known RI as sensors, the method can also be used for rapid in situ measurement of the local RI of inhomogeneous media. In this paper, we describe the principle of the method and the experiments of using the method to measure the RI of individual microspheres. Its applications for sensing instantaneous RI/concentration/temperature variation in critical situations such as anywhere in mixing flows or living biological specimens are also presented.

Utilization of microparticles in next-generation assays for microflow cytometers

Micron-sized particles have primarily been used in microfabricated flow cytometers for calibration purposes and proof-of-concept experiments. With increasing frequency, microparticles are serving as a platform for assays measured in these small analytical devices. Light scattering has been used to measure the agglomeration of antibody-coated particles in the presence of an antigen. Impedance detection is another technology being integrated into microflow cytometers for microparticle-based assays. Fluorescence is the most popular detection method in flow cytometry, enabling highly sensitive multiplexed assays. Finally, magnetic particles have also been used to measure antigen levels using a magnetophoretic micro-device. We review the progress of microparticle-based assays in microflow cytometry in terms of the advantages and limitations of each approach.

High speed classification of individual bacterial cells using a model-based light scatter system and multivariate statistics

We describe a model-based instrument design combined with a statistical classification approach for the development and realization of high speed cell classification systems based on light scatter. In our work, angular light scatter from cells of four bacterial species of interest, Bacillus subtilis, Escherichia coli, Listeria innocua, and Enterococcus faecalis, was modeled using the discrete dipole approximation. We then optimized a scattering detector array design subject to some hardware constraints, configured the instrument, and gathered experimental data from the relevant bacterial cells. Using these models and experiments, it is shown that optimization using a nominal bacteria model (i.e., using a representative size and refractive index) is insufficient for classification of most bacteria in realistic applications. Hence the computational predictions were constituted in the form of scattering-data-vector distributions that accounted for expected variability in the physical properties between individual bacteria within the four species. After the detectors were optimized using the numerical results, they were used to measure scatter from both the known control samples and unknown bacterial cells. A multivariate statistical method based on a support vector machine (SVM) was used to classify the bacteria species based on light scatter signatures. In our final instrument, we realized correct classification of B. subtilis in the presence of E. coli,L. innocua, and E. faecalis using SVM at 99.1%, 99.6%, and 98.5%, respectively, in the optimal detector array configuration. For comparison, the corresponding values for another set of angles were only 69.9%, 71.7%, and 70.2% using SVM, and more importantly, this improved performance is consistent with classification predictions.

Measurement and analysis of angle-resolved scatter from small particles in a cylindrical microchannel

Scatter of a two-dimensional Gaussian beam of a rectangular cross section by individual particles suspended in a fluid in a cylindrical channel is modeled by using a full-wave approach. First, the internal and scattered fields associated with the cylindrical channel and the two-dimensional Gaussian beam are computed. The spatial variations of the computed electromagnetic field inside the channel indicate that particles and cells of sizes relevant to flow cytometry are subjected to essentially plane-wave illumination, and hence Lorenz-Mie theory is applicable for spherical particles. Further, it is assumed that the perturbation of the electromagnetic field in the channel that is due to the presence of a particle is negligible, allowing us to ignore the interactive scatter of the particle and the channel (they are electromagnetically uncoupled). This approximation is valid when the particle intercepts a small fraction of the total energy inside the channel and when the particle or cell has a low relative refractive index. Measurements of scatter from the channel agree with the analytical model and are used to determine the location of detectors to measure scatter from particles in the channel. Experimental results of accumulated scatter from single latex spheres flowing in the channel show good agreement with computed results, thereby validating the internal field and uncoupled scatter models.

Determination of complex refractive index of polystyrene microspheres from 370 to 1610 nm

We introduce an inverse method for determining simultaneously the real and imaginary refractive indices of microspheres based on integrating sphere measurements of diffuse reflectance and transmittance, and Monte Carlo modelling in conjunction with the Mie theory. The results for polystyrene microspheres suspended in water are presented.

Angular distribution of light scattered by single biological cells and oriented particle agglomerates

We used a flow cytometer together with an intensified CCD camera to record spatially resolved light scattering from micrometer-sized single particles and single oriented particle agglomerates. Experimental differential cross sections of an oriented dumbbell made from two identical polystyrene spheres were compared with theoretical values calculated within the discrete dipole approximation, and good agreement was achieved. Furthermore, characteristic two-dimensional patterns of the scattered-light intensity were recorded for single blood cells, yielding information on the cells' shape and volume. Besides flow cytometry, we observed and analyzed differential light scatter of particle clusters of known size, shape, and orientation located within an optical trap.

Mathematical modeling the kinetics of cell distribution in the process of ligand-receptor binding

A statistical approach is presented to model the kinetics of cell distribution in the process of ligand-receptor binding on cell surfaces. The approach takes into account the variation of the amount of receptors on cells assuming the homogeneity of monovalent binding sites and ligand molecules. The analytical expressions for the kinetics of cell distribution have been derived in the reaction-limited approximation. In order to demonstrate the applicability of the mathematical model, the kinetics of binding the rabbit, anti-mouse IgG with Ig-receptors of the murine hybridoma cells has been measured. Anti-mouse IgG was labeled with fluorescein isothiocyanate (FITC). The kinetics of cell distribution on ligand-receptor complexes was observed during the reaction process by real-time measuring of the fluorescence and light-scattering traces of individual cells with the scanning flow cytometer. The experimental data were fitted by the mathematical model in order to obtain the binding rate constant and the initial cell distribution on the amount of receptors.

Individual Escherichia coli cells studied from light scattering with the scanning flow cytometer

BACKGROUND

Flow cytometry is a powerful tool for the analysis of individual particles in a flow. Differential light scattering (an indicatrix) was used for many years to obtain morphologic information about microorganisms. The indicatrices play the same role for individual particle recognition as a spectrum for substance characterization. We combined two techniques to analyze the indicatrix of the cells for the purpose of developing a database of light-scattering functions of cells.

METHODS

The scanning flow cytometer (SFC) allows the measurement of the entire indicatrix of individual particles at polar angles ranging from 5 degrees to 100 degrees. In this work, light-scattering properties of Escherichia coli have been studied both experimentally and theoretically with the SFC and the T-matrix method, respectively. The T-matrix method was used because of the nonspherical shape of E. coli cells, which were modeled by a prolate spheroid.

RESULTS

The indicatrices of E. coli cells were stimulated with T-matrix method at polar angles ranging from 10 degrees to 60 degrees. The absolute cross-section of light scattering of E. coli has been determined comparing the cross section of polystyrene particles modeled by a homogeneous sphere. The E. coli indicatrices were compared for logarithmic and stationary phases of cell growth.

CONCLUSIONS

The indicatrices of E. coli were reproducible and could be used for identification of these cells in biologic suspensions. The angular location of the indicatrix minimum can be used in separation of cells in logarithmic and stationary phases. To use effectively the indicatrices for that purpose, the light-scattering properties of other microorganisms have to be studied.