Abstract
Due to a growing demand for a viable label-free observation method in the biomedical field, many techniques, such as quantitative phase imaging and Raman spectroscopy, have been studied, and a complementary approach, hyperspectral imaging, has also been introduced. We developed a high-speed hyperspectral imaging microscopy imaging method with commercially available apparatus, employing a liquid crystal tunable bandpass filter combined with a pixel-wise machine learning classification. Next, we evaluated the feasibility of the application of this method for stem cell research utilizing neural stem cells. Employing this microscopy method, with a 562 × 562 μm2 field of view, 2048 × 2048 pixel resolution images containing 63 wavelength pixel-wise spectra could be obtained in 30 seconds. The neural stem cells were differentiated into neurons and astroglia (glia), and a four-class cell classification evaluation (including neuronal cell body, glial cell body, process and extracellular region) was conducted under co-cultured conditions. As a result, an average of 88% of the objects of interest were correctly classified, with an average precision of 94%, and more than 99% of the extracellular pixels were correctly segregated. These results indicated that the proposed hyperspectral imaging microscopy is feasible as a label-free observation method for stem cell research.
Highlights
These days in the fields of life science, biology and medicine, there has been a growing demand for label-free observation methods that allow for the assessment of biological materials repeatedly without any toxic effects and without the use of dyes or tags
Considering the growing demand for a viable label-free observation method in the biomedical field, we investigated the feasibility of using the hyperspectral imaging (HSI) method for rapid label-free observation in stem cell research at a practical level
Using our HSI microscopy method, with a 562 × 562 μm[2] field of view, a 2048 × 2048 pixel image containing 63-wavelength spectra can be obtained in 30 seconds, which is far more rapid than Raman spectroscopy (RS) and the laser scanning confocal HSI microscopy method
Summary
These days in the fields of life science, biology and medicine, there has been a growing demand for label-free observation methods that allow for the assessment of biological materials repeatedly without any toxic effects and without the use of dyes or tags. Pluripotent cells can differentiate into different types of cells[1], and there is a dangerous possibility for tumor formation associated with residual undifferentiated cells used in autologous therapy[12] Among these label-free observation methods, quantitative phase imaging (QPI) and Raman spectroscopy (RS) have been intensively studied recently. In recent years, yet another technique, hyperspectral imaging (HSI), which may be applicable to label-free noninvasive observation and complementary to QPI and RS, was introduced in the life science field[20]. In view of the current circumstances regarding HSI, this study was conducted to investigate the feasibility of using the HSI method for rapid label-free observation in stem cell research, employing commercially available apparatus combined with machine learning techniques, utilizing both spectrum and morphological features to identify cells
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