Label-free microscopy enables the possibility of measuring biological samples noninvasively and purely based on endogenous contrast. In particular, quantitative phase microscopy (QPM) can provide signals proportional to the intracellular refractive index with high-throughput. To improve the specificity of these measurements, we coupled QPM with Raman spectroscopy, another label-free modality that provides a signal related to the molecular content of the sample. We then developed a hybrid imaging approach where imaging is restricted to QPM to maintain a high-throughput despite the inherent slow acquisition time of Raman signals, while ensuring that the measured spectrum is representative of the whole cellular content. <p> </p>This approach provides signals for both the morphology, related to the phenotype, and the intracellular molecular content at single-cell level, that we employed to study cell populations under different stimuli. In particular, we studied macrophage cells and their response to a simulated bacterial infection upon exposure to lipopolysaccharide, and show how this approach is able to noninvasively detect the activation state at single-cell level by coupling it with multivariate analysis and machine learning algorithms.
We present applications of a label-free approach to assess the immune response based on the combination of interferometric microscopy and Raman spectroscopy, which makes it possible to simultaneously acquire morphological and molecular information of live cells. We employ this approach to derive statistical models for predicting the activation state of macrophage cells based both on morphological parameters extracted from the high-throughput full-field quantitative phase imaging, and on the molecular content information acquired through Raman spectroscopy. We also employ a system for 3D imaging based on coherence gating, enabling specific targeting of the Raman channel to structures of interest within tissue.
KEYWORDS: Raman spectroscopy, Principal component analysis, Imaging spectroscopy, Statistical analysis, Signal to noise ratio, Signal detection, Sensors, Molecular spectroscopy, Spectroscopy, Biological research
Raman spectroscopy is an optical method providing sample molecular composition, which can be analyzed (by point measurements) or spatially mapped by Raman imaging. These provide different information, signal-to-noise ratios, and require different acquisition times. Here, we quantitatively assess Raman spectral features and compare the two measurement methods by multivariate analysis. We also propose a hybrid method: scanning the beam through the sample but optically binning the signal at one location on the detector. This approach generates significantly more useful spectral signals in terms of peak visibility and statistical information. Additionally, by combination with a complementary imaging mode such as quantitative phase microscopy, hybrid imaging allows high throughput and robust spectral analysis while retaining sample spatial information. We demonstrate the improved ability to discriminate between cell lines when using hybrid scanning compared to typical point mode measurements, by quantitatively evaluating spectra taken from two macrophage-like cell lines. Hybrid scanning also provides better classification capability than the full Raman imaging mode, while providing higher signal-to-noise signals with shorter acquisition times. This hybrid imaging approach is suited for various applications including cytometry, cancer versus noncancer detection, and label-free discrimination of cell types or tissues.
Digital holographic microscopy is an interferometric technique enabling the measurement of the quantitative
phase shifts induced by cell bodies. We correlate the phase signal measured on neurons with calcium
imaging measured by fluorescence on cells loaded with Fluo-4, to monitor responses to glutamate challenges,
which provoke well-known calcium increases through activation of various membrane receptors. A very good
correspondence can be identified between the two signals, showing the links between the phase signal, being a
measure of the intracellular dilution, and the calcium concentration within cells. We then check cell viability
by employing propidium iodide (PI), a fluorescent indicator relying on the cell membrane integrity loss to
assess cell death. Strong intracellular calcium concentration is indeed known to induce excitotoxic effects,
potentially inducing cell death. This enables showing that some cells cannot sustain the calcium saturation
identified in our measurements, leading to subsequent cell death.
Many biological objects are mainly transparent and weakly scattering, thus a promising (and already widely used) way
of imaging them consists in considering optical refractive index variations. The method proposed here permits 3D
imaging of the refractive index distribution with a tomographic approach. Usually, the classical Radon transform does
not sufficiently take into account the physical interaction between light and biological cells, therefore diffraction has to
Diffraction tomography is a method that permits 3D reconstruction of the refractive index, using many captures of the
complex optical field, for example at various angles. Then, the 3D Fourier space can be filled with spatial frequencies
coming from the different views. Our setup consists in rotating the object under fix illumination and detection. The
complex scattered field needed for tomographic reconstruction is obtained from digital holographic microscopy, using
one hologram per angle of view. The method is first validated with a spherical object. Mie scattering theory is used to
simulate the measured field from which the tomographic reconstruction is performed. Experimental results on
microbeads are also presented. The wide capability of 3D imaging using diffraction tomography in biology is shown.
To evaluate the severity of airway pathologies, quantitative dimensioning of airways is of utmost importance. Endoscopic vision gives a projective image and thus no true scaling information can be directly deduced from it. In this article, an approach based on an interferometric setup, a low-coherence laser source and a standard rigid endoscope is presented, and applied to hollow samples measurements. More generally, the use of the low-coherence interferometric setup detailed here could be extended to any other endoscopy-related field of interest, e.g., gastroscopy, arthroscopy and other medical or industrial applications where tri-dimensional topology is required. The setup design with a multiple fibers illumination system is presented. Demonstration of the method ability to operate on biological samples is assessed through measurements on ex vivo pig bronchi.
We present experimental investigation of a new reconstruction method for off-axis digital holographic microscopy
(DHM). This method effectively suppresses the object auto-correlation, commonly called the zero-order term, from
holographic measurements, thereby suppressing the artifacts generated by the intensities of the two beams employed
for interference from complex wavefield reconstruction. The algorithm is based on non-linear filtering, and can be
applied to standard DHM setups, with realistic recording conditions. We study the applicability of the technique under
different experimental configurations, such as topographic images of microscopic specimens or speckle holograms.
Optical tomography provides three-dimensional data of the measured specimen, while quantitative phase
imaging enables measuring the induced phase-shifts. Combining those two technologies makes possible to
get three-dimensional refractive index reconstruction. This can be achieved by introducing a scan in the
measurement process, which can be done in several ways. We present and compare results of tomographic
measurements, taken either in angle-scanning or wavelength-scanning approach, respectively in transmission
or in reflection microscopy, in the framework of digital holographic microscopy.
The limited depth-of-field is a main drawback of microscopy that prevents from observing, for example, thick
semi-transparent objects with all their features in focus. Several algorithms have been developed during the past
years to fuse images having various planes of focus and thus obtain a completely focused image with virtually
extended depth-of-field. We present a comparison of several of these methods in the particular field of digital
holographic microscopy, taking advantage of some of the main properties of holography.
We especially study the extended depth-of-field for phase images reconstructed from the hologram of a
biological specimen. A criterion of spatial measurement on the object is considered, completed with a visual
criterion. The step of distance taken into account to build the stack of images is less than the instrument
Then, preserving the distance of focus associated with each pixel of the image, a three-dimensional representation
is presented after automatic detection of the object. The limits of such a method of extraction of 3D
information are discussed.