Label-free hematology analysis using deep-ultraviolet microscopy

Abstract

<jats:p>Hematological analysis, via a complete blood count (CBC) and microscopy, is critical for screening, diagnosing, and monitoring blood conditions and diseases but requires complex equipment, multiple chemical reagents, laborious system calibration and procedures, and highly trained personnel for operation. Here we introduce a hematological assay based on label-free molecular imaging with deep-ultraviolet microscopy that can provide fast quantitative information of key hematological parameters to facilitate and improve hematological analysis. We demonstrate that this label-free approach yields 1) a quantitative five-part white blood cell differential, 2) quantitative red blood cell and hemoglobin characterization, 3) clear identification of platelets, and 4) detailed subcellular morphology. Analysis of tens of thousands of live cells is achieved in minutes without any sample preparation. Finally, we introduce a pseudocolorization scheme that accurately recapitulates the appearance of cells under conventional staining protocols for microscopic analysis of blood smears and bone marrow aspirates. Diagnostic efficacy is evaluated by a panel of hematologists performing a blind analysis of blood smears from healthy donors and thrombocytopenic and sickle cell disease patients. This work has significant implications toward simplifying and improving CBC and blood smear analysis, which is currently performed manually via bright-field microscopy, and toward the development of a low-cost, easy-to-use, and fast hematological analyzer as a point-of-care device and for low-resource settings.</jats:p>

Label-free lymphocytes reconstitution using side scatter for optimal T cell manufacturing

“…Similarly, sorted SSC low group enriches for CD4 + T cells and naïve T cells while SSC high cluster enriches for CD8 + T, NK and other more-differentiated T cell counterparts including T CM , T EM and T EMRA ( Figures 2D–2G ). Deep-ultraviolet light (UV) has been adopted for label-free molecular imaging (Zeskind et al, 2007) and hematology analysis (Ojaghi et al, 2020) thanks to its shorter wavelength. Thus, it is interesting to study whether UV light (e.g.…”

Hemoglobin quantification in red blood cells via dry mass mapping based on UV absorption

“…Label-free optical techniques to quantify the dry mass and other physical properties of individual cells 10 , 15 , 17 – 22 —in their natural state without requiring additional pretreatment or sample preparation—offer an excellent alternative and have been successfully applied to quantify Hb in RBCs. 5 , 6 , 15 , 21 – 24 For example, quantitative phase imaging (QPI)-based methods 5 , 6 , 17 – 19 , 21 , 23 measure the phase accumulated in biological samples and translate this metric into dry mass density by leveraging the linear relationship between refractive index and mass concentration. 17 QPI methods gained popularity due to their accuracy, sensitivity, and speed, but they lack molecular specificity and cannot clearly distinguish between the different organelles or cellular compartments having different chemical compositions.…”

“…In this letter, we present a comparison of RBC mass mapping, and thereby Hb quantification, at four UV wavelengths: 220, 260, 280, and 300 nm using transmission microscopy images from our multispectral UV imaging system. 24 Note that 220 and 280 nm correspond to regions of high protein absorption, 260 nm corresponds to the absorption peak of nucleic acids, whereas absorption at 300 nm is only significant for Hb. Our previous study 24 leveraged this insight and used 260 nm for WBC identification and 300 nm for Hb analysis.…”

“… 24 Note that 220 and 280 nm correspond to regions of high protein absorption, 260 nm corresponds to the absorption peak of nucleic acids, whereas absorption at 300 nm is only significant for Hb. Our previous study 24 leveraged this insight and used 260 nm for WBC identification and 300 nm for Hb analysis. However, imaging protocols could be greatly simplified if only a single wavelength was necessary to achieve both WBC and RBC (and thus Hb) characterization.…”

Label-free bone marrow white blood cell classification using refractive index tomograms and deep learning

“…To address this issue, several label-free techniques for identifying blood cells have recently been explored, including multiphoton excitation microscopy (Kim et al 2018; Li et al 2010), Raman microscopy (Nitta et al 2020; Orringer et al 2017; Ramoji et al 2012) and hyperspectral imaging (Ojaghi et al 2020; Verebes et al 2013). Each method exploits the endogenous contrast (e.g., Tryptophan, Raman spectra, chromophores) of a specimen with the objective of visualizing and characterizing it without using exogenous agents; however, these modalities require rather complex optical instruments with demanding system alignments and long data acquisition time.…”