This paper directly compares the resolution, sensitivity, and imaging contrasts of stimulated Raman scattering (SRS) and coherent anti-Stokes Raman scattering (CARS) integrated into the same microscope platform. The results show that CARS has a better spatial resolution, SRS gives better contrasts and spectral resolution, and both methods have similar sensitivity.
Stimulated Raman scattering (SRS) and coherent anti-Stokes Raman scattering (CARS) microscopy are the most widely used coherent Raman scattering imaging technologies. Hyperspectral SRS and CARS imaging offer Raman spectral information at every pixel, which enables better separation of different chemical compositions. Although both techniques require two excitation lasers, their signal detection schemes and spectral properties are quite different. The goal of this protocol is to perform both hyperspectral SRS and CARS imaging on a single platform and compare the two microscopy techniques for imaging different biological samples. The spectral focusing method is employed to acquire spectral information using femtosecond lasers. By using standard chemical samples, the sensitivity, spatial resolution, and spectral resolution of SRS and CARS in the same excitation conditions (i.e., power at the sample, pixel dwell time, objective lens, pulse energy) are compared. The imaging contrasts of CARS and SRS for biological samples are juxtaposed and compared. The direct comparison of CARS and SRS performances would allow for optimal selection of the modality for chemical imaging.
The Raman scattering phenomenon was first observed in 1928 by C. V. Raman1. When an incident photon is interacting with a sample, an inelastic scattering event can spontaneously occur, in which the energy change of the photon matches a vibrational transition of the analyzed chemical species. This process does not require the use of a chemical tag, making it a versatile, label-free tool for chemical analysis while minimizing sample perturbation. Despite its advantages, spontaneous Raman scattering suffers from a low scattering cross-section (typically 1011 lower than the infrared [IR] absorption cross-section), which necessitates long acquisition times for analysis2. Thus, the quest for increasing the sensitivity of the Raman scattering process is essential in pushing Raman technologies for real-time imaging.
One effective way to greatly enhance the sensitivity of Raman scattering is through coherent Raman scattering (CRS) processes, for which two laser pulses are typically used to excite molecular vibrational transitions3,4. When the photon energy difference between the two lasers matches the vibrational modes of sample molecules, strong Raman signals will be generated. The two most commonly used CRS processes for imaging are coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS)5. Over the past two decades, technological developments have advanced CARS and SRS microscopy techniques to become powerful tools for label-free quantification and elucidation of chemical changes in biological samples.
Chemical imaging by CARS microscopy can be dated to 1982 when laser scanning was first applied to acquire CARS images, demonstrated by Duncan et al6. The modernization of CARS microscopy was greatly accelerated after the wide applications of laser scanning multiphoton fluorescence microscopy7. Early work from the Xie group using high repetition rate lasers has transitioned CARS to be a high-speed, label-free, chemical imaging platform for the characterization of molecules in biological samples8,9,10. One of the major issues for CARS imaging is the presence of a nonresonant background, which reduces the image contrast and distorts the Raman spectrum. Many efforts have been made to either reduce the nonresonant background11,12,13,14,15 or to extract resonant Raman signals from the CARS spectra16,17. Another advancement that has greatly advanced the field is hyperspectral CARS imaging, which allows for spectral mapping at each image pixel with improved chemical selectivity18,19,20,21.
Stimulated Raman scattering (SRS) is a younger imaging technology than CARS, although it was discovered earlier22. In 2007, SRS microscopy was reported using a low repetition rate laser source23. Soon, several groups demonstrated high-speed SRS imaging using high repetition rate lasers24,25,26. One of the major advantages of SRS microscopy over CARS is the absence of the nonresonant background27, although other backgrounds such as cross-phase modulation (XPM), transient absorption (TA), two-photon absorption (TPA), and photothermal (PT) effect, may occur with SRS28. In addition, the SRS signal and sample concentration have linear relationships, unlike CARS, which has a quadratic signal-concentration dependence29. This simplifies chemical quantification and spectral unmixing. Multicolor and hyperspectral SRS has evolved in different forms30,31,32,33,34,35,36, with spectral focusing being one of the most popular approaches for chemical imaging37,38.
Both CARS and SRS require the focusing of the pump and Stokes laser beams onto the sample to match the vibrational transition of the molecules for signal excitation. CARS and SRS microscopes also share a lot in common. However, the physics underlying these two processes, and signal detections involved in these microscopy technologies have disparities3,39. CARS is a parametric process that does not have net photon-molecule energy coupling3. SRS, however, is a nonparametric process, and contributes to energy transfer between photons and molecular systems27. In CARS, a new signal at anti-Stokes frequency is generated, while SRS manifests as the energy transfer between the pump and Stokes laser beams.
CARS signal satisfies Eq (1)28.
(1)
Meanwhile, SRS signal can be written as Eq (2)28.
(2)
Here, Ip, Is, ICARS, and ΔISRS are the intensities of the pump beam, Stokes beam, CARS signal, and SRS signals, respectively. χ(3) is the third-order nonlinear optical susceptibility of the sample, and is a complex value composed of real and imaginary parts.
These equations express the spectral profiles and signal-concentration dependence of CARS and SRS. Differences in physics result in disparate detection schemes for these two microscopy technologies. Signal detection in CARS usually involves spectral separation of newly generated photons and detection using a photomultiplier tube (PMT) or charge-coupled device (CCD); for SRS, the energy exchange between the pump and Stokes beams is usually measured by high-speed intensity modulation using an optical modulator and demodulation using a photodiode (PD) paired with a lock-in amplifier.
Although many technological developments and applications have been published in recent years in both CARS and SRS fields, no systematic comparisons of the two CRS techniques have been performed on the same platform, especially for hyperspectral CARS and SRS microscopy. Direct comparisons in sensitivity, spatial resolution, spectral resolution, and chemical separation capabilities would allow biologists to select the best modality for chemical quantification. In this protocol, detailed steps to construct a multimodal imaging platform with both hyperspectral CARS and SRS modalities based on a femtosecond laser system and spectral focusing are provided. The two techniques have been compared in the forward direction for spectral resolution, detection sensitivity, spatial resolution, and imaging contrasts of cells.
1. Instrumental setup for hyperspectral CRS imaging
NOTE: The generation of CRS signal requires the use of high-power (i.e., class 3B or class 4) lasers. Safety protocols must be addressed and proper personal protective equipment (PPE) must be worn at all times when working at such high peak powers. Consult proper documentation before experimentation. This protocol focuses on designing the beam path, chirping the femtosecond pulses, and optimizing imaging conditions. A general optical layout of this hyperspectral CRS microscope is shown in Figure 1. The configuration shown here is one of many existing configurations for CRS microscopy. The CRS microscopy system used in this protocol is built upon a dual-output femtosecond laser source and a laser scanning microscope.
2. Image analysis and data processing
3. Preparation of samples for hyperspectral CRS imaging
Comparisons of the spectral resolution
Figure 2 compares the spectral resolution of hyperspectral SRS (Figure 2A) and CARS (Figure 2B) microscopy using a DMSO sample. For the SRS spectrum, two Lorentzian functions (see protocol step 2.3) were applied to fit the spectrum, and a resolution of 14.6 cm-1 was obtained using the 2,913 cm-1 peak. For CARS, a two-peak-fitting function with a Gaussian background (see protocol step 2.3) was utilized for fitting, which gave the spectral resolution of 17.1 cm-1. These results show that, in the same measurement condition, SRS has a better spectral resolution than CARS. The reduced spectral resolution in CARS is mainly contributed by the involvement of the nonresonant background. In addition, it was found that the symmetric (2,913 cm-1) and asymmetric (2,995 cm-1) peak ratios were very different for SRS and CARS. This is due to the different signal correlations with the third-order nonlinear optical susceptibility, as described in equations (1) and (2). With the quadratic dependence of CARS, the intensity difference between the two peaks is amplified. The symmetric line shapes of the SRS peaks and the asymmetric line shapes of the CARS peaks can be observed in the spectrum. The asymmetry in the CARS signal is mainly due to the presence of the nonresonant background interference. The CARS spectral peaks appear slightly red-shifted (1-2 cm-1) to the SRS peaks. This also arises from the nonresonant background interference with resonant peaks.
Comparisons of the detection sensitivity
Figure 3 compares the detection sensitivity of hyperspectral SRS and CARS microscopy. The SNR of the DMSO SRS signals (2,913 cm-1) as the function of DMSO concentration in D2O at high concentrations are plotted first (1%-50%, Figure 3A). The results show a linear relationship, satisfying equation (2). Figure 3B plots the DMSO spectra at 0.1% and 0.01% concentrations, in which the 2,913 cm-1 peak can be resolved in the former but not in the latter, indicating the detection limit is between 0.1% and 0.01% DMSO. Using the limit of blank criteria, we estimated that the SRS detection limit is 0.021% DMSO. Figure 3C plots the CARS SNR as the function of DMSO concentration (1%-50%), showing a quadratic dependence in agreement with equation (1). The phase-retrieved CARS spectra are shown in Figure 3D for the 0.1% and 0.01% DMSO. To achieve these spectra, a spectral phase-retrieval method based on Kramers-Kronig relations was used and additional background removal was performed16. Similar to the SRS spectra, the DMSO 2,913 cm-1 peak can be clearly resolved for the 0.1% DMSO but not the 0.01%, indicating a detection limit between these two concentrations. Using the limit of blank criteria, we estimated that the SRS detection limit is 0.015% DMSO. The 0.02% DMSO corresponds to 2.8 mM. Therefore, the detection limit of the hyperspectral CRS microscope used here is ~2.1-2.8 mM DMSO.
Comparisons of the spatial resolution
Figure 4 compares the resolution of a small cellular feature detected in SRS (Figure 4A) and CARS (Figure 4B) images. The intensity profiles from the same line are displayed and fit using a Gaussian function to determine FWHM values for resolution comparison. The SRS signal gave a resolution of 398.6 nm (Figure 4C), while the CARS signal gave a resolution of 330.3 nm (Figure 4D). The resolution of CARS was ~1.2x better than that of the SRS. The reason for the resolution difference also lies in equations (1) and (2). Both pump and Stokes beams have a Gaussian point spread function at the focus. The signal of CARS is then proportional to the multiplication of three Gaussian functions, which roughly reduces the width by a factor of √3. Similarly, for SRS, the width is reduced by a factor of √2. Therefore, the resolution of CARS was √3/√2 = 1.2 times better than that of the SRS.
Comparisons of the images of cells
Figure 5 compares SRS and CARS images from MIA PaCa-2 cells at different optical delay positions. Figure 5A shows the SRS images at the optical delay that gave the strongest signal. In this image, lipid droplets (LDs), endoplasmic reticulum (ER), and nucleus (NU) can be detected, with LDs having the strongest signals shown as bright dots. Figure 5B shows the CARS channel image at the same optical delay, having much-reduced contrasts for LDs. The major reasons for this contrast difference are the presence of the nonresonant background and the red-shift of the same Raman peak in CARS spectra. At this optical delay, the generated signal has a large contribution from the nonresonant background of water. To enhance the lipid contrast in CARS, the optical delay was tuned to a red-shifted value. The red-shift improved the lipid contrasts by concentrating more energy to the 2,850 cm-1 for both SRS (Figure 5C) and CARS (Figure 5D), although the overall signal level was reduced. For CARS, a similar contrast of LDs as SRS was achieved by a ~98 cm-1 red-shift in spectral focusing (Figure 5D), though a background higher than that in the SRS image was still observed. At this optical delay, the SRS image shows much less protein and nucleic acid contents but strong lipid contents in LDs, ER, and cell membranes (Figure 5C).
CARS is a parametric process while SRS is nonparametric. Such a difference also contributes to contrast differences in the two modalities. The parametric CARS signals are determined by the interference of CARS signals from different layers close to the laser focus, which might show negative contrasts as indicated by arrows in Figure 5B and Figure 5D (also in Figure 4B). Such signal-interference-induced negative contrasts are absent in the SRS images. The negative contrast in CARS might provide information about the axial position of the target of interest.
The SRS signals have a linear relationship with the molecular concentration, while the CARS signals satisfy a near-quadratic concentration-dependence. Therefore, the CH2-rich LDs show a much stronger signal than the ER and the cell membranes in the CARS image than in the SRS image (Figure 5E,F). The SRS spectra can be extracted from hyperspectral images. Figure 5G shows the typical SRS spectra from LDs, ER, cytosol (CY), and NU. Both the intensity and spectral shape are different for different cellular compartments. LD shows a much stronger signal at 2,850 cm-1 than other organelles. As for CARS, similar spectra, though different in shapes, can be obtained. The raw CARS spectra show a small red-shift compared to the corresponding SRS spectra. Spectral phase-retrieval can be further used to extract the Raman responses using the CARS spectra.
Figure 1: A schematic of the hyperspectral CARS/SRS microscope. Abbreviations: CARS = coherent anti-Stokes Raman scattering; SRS = stimulated Raman scattering; PBS = polarization beam splitter; PD = photodiode; PMT = photomultiplier tube; AOM = acousto-optic modulator. Please click here to view a larger version of this figure.
Figure 2: DMSO spectra. (A) SRS and (B) CARS spectra of DMSO. Dots are experimental data; curves are spectral fitting results. Abbreviations: CARS = coherent anti-Stokes Raman scattering; SRS = stimulated Raman scattering; DMSO = dimethyl sulfoxide; w = spectral resolution. Please click here to view a larger version of this figure.
Figure 3: Signal-to-noise ratios and spectra of DMSO. (A) Signal-to-noise ratio of the DMSO symmetric peak at 2,913 cm-1 as a function of concentration in D2O measured by SRS. The dots are experimental data; the line is the linear fitting result. (B) The SRS spectra of 0.1% and 0.01% DMSO in D2O. (C) Signal-to-noise ratio of the DMSO symmetric peak at 2,913 cm-1 as a function of concentration in D2O measured by CARS. The dots are experimental data; the curve is the second-degree polynomial fitting result. (D) The CARS spectra of 0.1% and 0.01% DMSO in D2O. Abbreviations: CARS = coherent anti-Stokes Raman scattering; SRS = stimulated Raman scattering; DMSO = dimethyl sulfoxide; SNR = signal-to-noise ratio; D2O = deuterium oxide. Please click here to view a larger version of this figure.
Figure 4: SRS and CARS images and intensity profiles of an MIA PaCa-2 cell. (A) An SRS image of an MIA PaCa-2 cell. (B) A CARS image of an MIA PaCa-2 cell at the same field-of-view as panel A. (C) Intensity profile of SRS along the yellow line in panel A. (D) Intensity profile of CARS along the yellow line in panel B. Dots are experimental data; curves are Gaussian function fitting results. Scale bars = 5 µm. Abbreviations: CARS = coherent anti-Stokes Raman scattering; SRS = stimulated Raman scattering; w = resolution. Please click here to view a larger version of this figure.
Figure 5: Images and intensity profile of MIA PaCa-2 cells. (A) An SRS image of MIA PaCa-2 cells at the optimized time delay for SRS intensity. (B) A CARS image at the same delay as in panel A. (C) An SRS image at the 98 cm-1 red-shifted delays as in panel A. (D) A CARS image at the same optical delay as in panel C. (E,F) The SRS and CARS intensity profiles plotted along the dotted lines in panels A and D. (G) Typical SRS spectra from the lipid droplets, endoplasmic reticulum, cytosol, and nucleus. (H) Typical CARS spectra of the four cellular compositions. The green and red dotted lines are delay positions for panels A/B and C/D, respectively. Scale bars = 10 µm. Abbreviations: CARS = coherent anti-Stokes Raman scattering; SRS = stimulated Raman scattering; LD = lipid droplets; ER = endoplasmic reticulum; CY = cytosol; NU = nucleus. Please click here to view a larger version of this figure.
Supplemental File: Lab-written software based on LabVIEW having a simultaneous multichannel display for real-time viewing and saving images. Please click here to download this File.
The protocol presented here describes the construction of a multimodal CRS microscope and the direct comparison between CARS and SRS imaging. For the microscope construction, the critical steps are spatial and temporal beam overlapping and beam size optimization. It is recommended to use a standard sample such as DMSO before the biological imaging for optimizing SNR and calibrating Raman shifts. Direct comparison between CARS and SRS images reveals that CARS has a better spatial resolution, while SRS gives better spectral resolution and less convoluted chemical contrasts. Both CARS and SRS have similar detection limits.
CARS and SRS imaging use high-energy pulse lasers for excitation. This allows the platform to integrate other nonlinear optical imaging modalities such as multiphoton excitation fluorescence, harmonic generation, and transient absorption for additional chemical contrasts28,39.
CARS and SRS have been extensively used to study lipid composition with high chemical selectivity. However, the technologies are not limited to quantifying lipids. SRS has been applied to map drug distribution42, protein synthesis43, and DNA44. CARS and SRS have also been applied to image pharmaceutical ingredients and excipients in tablets45,46,47,48. Hyperspectral CARS and SRS have found applications in cancer diagnosis49, cardiovascular disease evaluation50, and neural imaging51. They can also be applied for COVID-19 studies52. Broadband CARS, which can cover spectral windows as broad as 3,000 cm-1, can elucidate rich chemical structures in biological samples53. However, due to the slow readout rate of the CCD, the pixel dwell time is on the level of milliseconds, much slower than the microsecond pixel dwell time for SRS microscopy34. Hyperspectral SRS microscopy currently has a typical bandwidth of 200-300 cm-1, limited by the laser bandwidth and the lack of lock-in-integrated array detectors34. Fourier transform SRS microscopy is an alternative way to potentially broaden the SRS spectral coverage35.
Although CARS and SRS provide rich chemical information without the need for labeling, the chemical selectivity lies in chemical bonds, making it difficult to distinguish specific proteins. Raman tags have shown the potential to enhance the chemical selectivity of CARS and SRS54,55. However, coherent Raman imaging still has much lower sensitivity compared to fluorescence detection. Surface enhancement was used for spontaneous Raman scattering spectroscopy to improve the signal levels56. It was also applied to CARS and SRS for signal amplification57,58,59. Although the enhancement factor is not as high as spontaneous Raman scattering, surface-enhanced CARS and SRS microscopy still show the potential to detect single molecules59,60. Nevertheless, the use of metal particles or surfaces deprives the advantage of the label-free approach. Improving the sensitivity of coherent Raman microscopy without using metal surfaces would greatly expand the application of the technology in biological science.
The authors have nothing to disclose.
This research was supported by the Purdue University Department of Chemistry startup fund.
2D galvo scanner set | Thorlabs | GVS002 | |
Acousto-optic modulator | Isomet | M1205-P80L-0.5 | |
AOM driver | Isomet | 532B-2 | |
Data acquisition card | National Instruments | PCle 6363 | Custom ordered filter (980 sp) |
Delay stage | Zaber | X-LSM050A | |
Deuterium oxide | Millipore Sigma | 151882-100G | |
Dichroic mirror for beam combination | Thorlabs | DMLP1000 | |
Dichroic mirror for signal separation | Semrock | FF776-Di01-25×36 | |
DMSO | MiliporeSigma | 200-664-3 | |
MIA PaCa 2 Cells | ATCC | CRL-1420 | |
Femtosecond laser system | Spectral Physics | InSightX3+ | |
Filter for CARS | Chroma | AT655/30m | |
Filter for SRS | Chroma | ET980sp | |
Function generator | Rigol | DG1022Z | |
Glass rods | Lattice Electro Optics | SF-57 | |
Half-wave plate | Newport | 10RP02-51; 10RP02-46 | |
LabVIEW 2020 | National Instruments | This is the image acquisition software | |
Lock-in amplifier | Zurich Instrument | HF2LI | |
Microscope housing | Olympus | BX51W1 | |
Objective lens | Olympus | UPLSAPO60XW | |
Origin Pro 2019b | OriginLab Corporation | This is the spectral fitting software | |
Oscilloscope | Tektronix | TBS2204B | |
Photodiode | Hamamatsu | S3994-01 | |
PMT detector | Hamamatsu | H7422P-40 | |
PMT voltage amplifier | Advanced Research Instrument Corp. | PMT4V3 | |
Polarizing beamsplitter cube | Thorlabs | PBS255 | |
Terminal block | National Instruments | BNC-2110 |