Light scattering and morphology of the lymphocyte as applied to flow cytometry for distinguishing healthy and infected individuals

Microphysiological Drug-Testing Platform for Identifying Responses to Prodrug Treatment in Primary Leukemia

Despite increasing survival rates of pediatric leukemia patients over the past decades, the outcome of some leukemia subtypes has remained dismal. Drug sensitivity and resistance testing on patient-derived leukemia samples provide important information to tailor treatments for high-risk patients. However, currently used well-based drug screening platforms have limitations in predicting the effects of prodrugs, a class of therapeutics that require metabolic activation to become effective. To address this issue, a microphysiological drug-testing platform is developed that enables co-culturing of patient-derived leukemia cells, human bone marrow mesenchymal stromal cells, and human liver microtissues within the same microfluidic platform. This platform also enables to control the physical interaction between the diverse cell types. Herein, it is made possible to recapitulate hepatic prodrug activation of ifosfamide in their platform, which is very difficult in traditional well-based assays. By testing the susceptibility of primary patient-derived leukemia samples to the prodrug ifosfamide, sample-specific sensitivities to ifosfamide in primary leukemia samples are identified. The microfluidic platform is found to enable the recapitulation of physiologically relevant conditions and the testing of prodrugs including short-lived and unstable metabolites. The platform holds great potential for clinical translation and precision chemotherapy selection.

Multi-angle pulse shape detection of scattered light in flow cytometry for label-free cell cycle classification

Flow cytometers are robust and ubiquitous tools of biomedical research, as they enable high-throughput fluorescence-based multi-parametric analysis and sorting of single cells. However, analysis is often constrained by the availability of detection reagents or functional changes of cells caused by fluorescent staining. Here, we introduce MAPS-FC (multi-angle pulse shape flow cytometry), an approach that measures angle- and time-resolved scattered light for high-throughput cell characterization to circumvent the constraints of conventional flow cytometry. In order to derive cell-specific properties from the acquired pulse shapes, we developed a data analysis procedure based on wavelet transform and k-means clustering. We analyzed cell cycle stages of Jurkat and HEK293 cells by MAPS-FC and were able to assign cells to the G1, S, and G2/M phases without the need for fluorescent labeling. The results were validated by DNA staining and by sorting and re-analysis of isolated G1, S, and G2/M populations. Our results demonstrate that MAPS-FC can be used to determine cell properties that are otherwise only accessible by invasive labeling. This approach is technically compatible with conventional flow cytometers and paves the way for label-free cell sorting.

Layer-based, depth-resolved computation of attenuation coefficients and backscattering fractions in tissue using optical coherence tomography

Structural optical coherence tomography (OCT) images of tissue stand to benefit from greater functionalization and quantitative interpretation. The OCT attenuation coefficient µ, an analogue of the imaged sample's scattering coefficient, offers potential functional contrast based on the relationship of µ to sub-resolution physical properties of the sample. Attenuation coefficients are computed either by fitting a representative µ over several depth-wise pixels of a sample's intensity decay, or by using previously-developed depth-resolved attenuation algorithms by Girard et al. [Invest. Ophthalmol. Vis. Sci.52, 7738 (2011). 10.1167/iovs.10-6925] and Vermeer et al. [Biomed. Opt. Express5, 322 (2014). 10.1364/BOE.5.000322]. However, the former method sacrifices axial information in the tomogram, while the latter relies on the stringent assumption that the sample's backscattering fraction, another optical property, does not vary along depth. This assumption may be violated by layered tissues commonly observed in clinical imaging applications. Our approach preserves the full depth resolution of the attenuation map but removes its dependence on backscattering fraction by performing signal analysis inside individual discrete layers over which the scattering properties (e.g., attenuation and backscattering fraction) vary minimally. Although this approach necessitates the detection of these layers, it removes the constant-backscattering-fraction assumption that has constrained quantitative attenuation coefficient analysis in the past, and additionally yields a layer-resolved backscattering fraction, providing complementary scattering information to the attenuation coefficient. We validate our approach using automated layer detection in layered phantoms, for which the measured optical properties were in good agreement with theoretical values calculated with Mie theory, and show preliminary results in tissue alongside corresponding histological analysis. Together, accurate backscattering fraction and attenuation coefficient measurements enable the estimation of both particle density and size, which is not possible from attenuation measurements alone. We hope that this improvement to depth-resolved attenuation coefficient measurement, augmented by a layer-resolved backscattering fraction, will increase the diagnostic power of quantitative OCT imaging.

Integration of light scattering with machine learning for label free cell detection

Light scattering has been used for label-free cell detection. The angular light scattering patterns from the cells are unique to them based on the cell size, nucleus size, number of mitochondria, and cell surface roughness. The patterns collected from the cells can then be classified based on different image characteristics. We have also developed a machine learning (ML) method to classify these cell light scattering patterns. As a case study we have used this light scattering technique integrated with the machine learning to analyze staurosporine-treated SH-SY5Y neuroblastoma cells and compare them to non-treated control cells. Experimental results show that the ML technique can provide a classification accuracy (treated versus non-treated) of over 90%. The predicted percentage of the treated cells in a mixed solution is within 5% of the reference (ground-truth) value and the technique has the potential to be a viable method for real-time detection and diagnosis.

Assessment of internal refractive index profile of stochastically inhomogeneous nuclear models via analysis of two-dimensional optical scattering patterns

SIGNIFICANCE

Optical scattering signals obtained from tissue constituents contain a wealth of structural information. Conventional intensity features, however, are mostly dictated by the overall morphology and mean refractive index of these constituents, making it very difficult to exclusively sense internal refractive index fluctuations.

AIM

We perform a systematic analysis to elucidate how changes in internal refractive index profile of cell nuclei can best be detected via optical scattering.

APPROACH

We construct stochastically inhomogeneous nuclear models and numerically simulate their azimuth-resolved scattering patterns. We then process these two-dimensional patterns with the goal of identifying features that directly point to subnuclear structure.

RESULTS

Azimuth-dependent intensity variations over the side scattering range provide significant insights into subnuclear refractive index profile. A particular feature we refer to as contrast ratio is observed to be highly sensitive to the length scale and extent of refractive index fluctuations; further, this feature is not susceptible to changes in the overall size and mean refractive index of nuclei, thereby allowing for selective tracking of subnuclear structure that can be linked to chromatin distribution.

CONCLUSIONS

Our analysis will potentially pave the way for scattering-based assessment of chromatin reorganization that is considered to be a key hallmark of precancer progression.

Relation between clinical mature and immature lymphocyte cells in human peripheral blood and their spatial label free scattering patterns

A single living cell's light scattering pattern (LSP) in the horizontal plane, which has been denoted as the cell's "2D fingerprint," may provide a powerful label-free detection tool in clinical applications. We have recently studied the LSP in spatial scattering planes, denoted as the cell's "3D fingerprint," for mature and immature lymphocyte cells in human peripheral blood. The effects of membrane size, morphology, and the existence of the nucleus on the spatial LSP are discussed. In order to distinguish clinical label-free mature and immature lymphocytes, the special features of the spatial LSP are studied by statistical method in both the spatial and frequency domains. Spatial LSP provides rich information on the cell's morphology and contents, which can distinguish mature from immature lymphocyte cells and hence ultimately it may be a useful label-free technique for clinical leukemia diagnosis.

Scattering pulse of label free fine structure cells to determine the size scale of scattering structures

Scattering pulse is sensitive to the morphology and components of each single label-free cell. The most direct detection result, label free cell's scattering pulse is studied in this paper as a novel trait to recognize large malignant cells from small normal cells. A set of intrinsic scattering pulse calculation method is figured out, which combines both hydraulic focusing theory and small particle's scattering principle. Based on the scattering detection angle ranges of widely used flow cytometry, the scattering pulses formed by cell scattering energy in forward scattering angle 2°-5° and side scattering angle 80°-110° are discussed. Combining the analysis of cell's illuminating light energy, the peak, area, and full width at half maximum (FWHM) of label free cells' scattering pulses for fine structure cells with diameter 1-20 μm are studied to extract the interrelations of scattering pulse's features and cell's morphology. The theoretical and experimental results show that cell's diameter and FWHM of its scattering pulse agree with approximate linear distribution; the peak and area of scattering pulse do not always increase with cell's diameter becoming larger, but when cell's diameter is less than about 16 μm the monotone increasing relation of scattering pulse peak or area with cell's diameter can be obtained. This relationship between the features of scattering pulse and cell's size is potentially a useful but very simple criterion to distinguishing malignant and normal cells by their sizes and morphologies in label free cells clinical examinations.

Aqueous cell differentiation in anterior uveitis using Fourier-domain optical coherence tomography

PURPOSE

The differential diagnosis of a patient presenting with anterior uveitis is broad and can present a diagnostic challenge. In this study, we evaluate the characteristic findings of inflammatory cells on optical coherence tomography (OCT) both in vitro and in vivo.

METHODS

Blood from two healthy volunteers was prepared using standardized methods for cell sorting with a flow cytometer (FASCAria). Neutrophils, lymphocytes, monocytes, and red blood cells were placed in suspension and scanned with a 26-kHz Fourier-domain OCT system (RTVue) with 5-μm axial resolution. Custom software algorithms were used to identify cells based on their reflectance distribution. These algorithms were then applied to OCT images obtained from uveitis patients with active anterior chamber inflammation.

RESULTS

On OCT images the cells appeared as hyperreflective spots. In vitro, cell reflectance was statistically significantly different between all of the cell types (neutrophils, monocytes, lymphocytes, and red blood cells, P < 0.001, Mann-Whitney test). In vivo, the relationship between underlying disease and cell type imaged on OCT was highly statistically significant, with human leukocyte antigen (HLA)-B27-associated uveitis patients having a predominantly polymorphonuclear pattern on OCT and sarcoidosis and inflammatory bowel disease patients having a predominantly mononuclear pattern on OCT (P < 0.001, Fisher's exact test).

CONCLUSIONS

These in vitro and in vivo data demonstrate the potential of OCT to evaluate cells in the anterior chamber of patients noninvasively. Optical coherence tomography may be a useful adjunct to guide the diagnosis and treatment of ocular inflammatory conditions.