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Draft:Surface-enhanced Spatially Offset Raman Spectroscopy

Surface-enhanced Spatially Offset Raman Scattering (SESORS) is a non-invasive, highly sensitive technique that combines the sensitivity of surface-enhanced Raman scattering (SERS) with the depth resolution of spatially offset Raman spectroscopy (SORS) to detect Raman photons from subsurface layers.

Components edit

 
Figure 1: A) Schematic Diagram of Rayleigh scattering, anti-Stokes Raman scattering and Stokes Raman scattering (Adapted from [1]) B) Conventional configuration of Spontaneous Raman Spectroscopy (Adapted from [2])

In conventional Raman scattering spectroscopy, a sample is illuminated by a laser. When molecules in the sample interact with photons from the incident laser, the resulting scattering can exhibit three modes: photons scatter back with the same energy (Rayleigh scattering), higher energy (anti-Stokes scattering), or lower energy (Stokes scattering) compared to the incident photons (Figure 1A) [1]. More specifically, Rayleigh scattering occurs when a molecule returns to its ground state without any change in energy, emitting a photon of the same frequency as the incident one. Stokes scattering involves the molecule transitioning to a higher vibrational energy level by absorbing energy from the incident photon and scattering photons with lower energy than the incident photon. On the other hand, anti-Stokes scattering arises when the molecule of higher energy state loses energy to the incident photon and scattering photons with higher energy than the incident photon. Conventional Raman spectroscopy typically involves directing a laser beam of a specific wavelength onto a sample through a pinhole (Figure 1B) [3]. The scattered light, which includes both Rayleigh and Raman scattering, is then filtered by a beam splitter to remove the intense Rayleigh component and enhance the weaker Raman signals. The Raman photons are subsequently passed through a spectrometer to disperse the light into its constituent wavelengths, thereby generating a Raman spectrum. However, because of the backscattering configuration used in conventional Raman spectroscopy, researchers can only observe photons originating from or near the surface of the sample.

 
Figure 2: A) Schematic Diagram of SORS B) Configuration of SORS C) SORS Variants (Adapted from [4])

To address this limitation, SORS utilizes the phenomenon where scattered Raman photons disperse laterally away from the illumination source and eventually reach the sample’s surface at different distances (Δs) (Figure 2A) from the source [4]. By collecting Raman signals at various offset distances, the technique can probe deeper layers of the sample, reduce surface interference and enhance the detection of subsurface or buried materials. The optical configuration of SORS closely resembles that of conventional Raman spectroscopy (Figure 2B). However, there are some important changes. Firstly, SORS incorporates an optical fiber bundle arranged in a specific pattern to deliver laser light to the sample surface. Then, another set of fiber bundles is positioned at various offset distances (Δs) to gather the scattered photons. Secondly, SORS employs a spectrally narrow illumination source with a bandwidth less than 1 cm-1 to narrow the Raman peak as much as possible. Thirdly, detectors in SORS are positioned at offset distances away from the illumination source to capture Raman signals originating from various depths within the sample. Due to its reliance on photon scattering for signal detection, highly absorbent samples are not well-suited for SORS. There are variants of SORS: 1) Point-like SORS 2) Ring-collection SORS 3) Ring-collection SORS 4) Ring-illumination SORS 5) Defocusing SORS (Figure 2C). Point-like SORS uses a small spot of laser light to illuminate the sample. Then, Raman photons are collected at various offset distances away from the illumination spot. Ring-collection SORS collects Raman photons in a ring-shaped configuration around the illumination spot. Such a technique is good for mapping the sample. Ring-illumination SORS shapes the laser to a ring pattern during illumination, which enhances the depth resolution of the techniques. Defocusing SORS uses intentionally defocused lasers to create a larger and more diffusive spot of light. The wider distribution of light can allow it to penetrate deeper into the sample before it is significantly attenuated.

 
Figure 3: A) Schematic Diagram of SERS B) Electromagnetic and Chemical Enhancement in SERS (Adapted from [5]​)

To further enhance the penetration depth and resolution of SORS, surface enhancement is introduced. Surface enhancement involves illuminating a sample adsorbed on nanostructures with a laser (Figure 3A) [5]. When the incident light interacts with the surface of nanostructures, it induces collective oscillation of electrons. These oscillations create strong, localized electromagnetic fields near the nanostructure surface, leading to significant enhancement of the Raman scattering signal of nearby molecules (Figure 3B). The electromagnetic enhancement is strongest when the excitation wavelength matches the surface plasmon resonance of the nanoparticles. Additionally, electrons are transferred between the molecule and the nanostructures, ultimately enhancing the Raman scattering signal (Figure 3C). Together, the electromagnetic and chemical enhancements amplify the signal of Raman scattering. Surface-enhanced Raman spectroscopy uses the configuration as the conventional Raman spectroscopy. However, the sample needs to be adsorbed onto nanostructures such as gold nanoparticles, silver nanoparticles to achieve surface enhancement.

To put everything together, SESORS uses the optical set-up of SORS, where there are fiber bundles to deliver the illumination source and collect scattered Raman photons at various offset distances. The illumination source must be spectrally narrow with a bandwidth less than 1 cm-1 to narrow the Raman peak. The sample is also attached to gold or silver nanoparticles to generate surface plasmon effects to amplify Raman signals at deeper depths into the sample.

Depth edit

 
Figure 4: A) SESORS Configuration B) Raman Spectra of Pork Muscle (Adapted from [6])​

Stone (2010) uses SESORS to study a pork muscle with a thickness of 15 and 25 mm. Silver nanoparticles loaded with NIR dye tag were injected into the 15 and 25 mm tissues at 3.0 x 109 and 5.9 x 109 nanoparticles, respectively. A 200 mW of 830 nm laser light was used to illuminate the sample. All Raman spectra were collected for 10 seconds. The Raman photons were collected on the opposite side of the sample. After background subtraction, both Raman spectra of 15 and 25 mm tissues exhibit sharp Raman peaks. Since the 25 mm tissue received twice the dose of nanoparticles than the 15 mm tissue, the Raman signals were increased by 100 times (Figure 4A-B) [6]. However, silver nanoparticles can be toxic to cellular processes, making it not an ideal target for in vivo study.

Stone (2011) uses SESORS to study a large porcine tissue block of 20 x 50 x 50 mm. Gold nanoparticles loaded with various Raman reporters including d8DIPY, BPE for multiplexing experiments were injected into porcine tissues of 20 x 50 x 50 and 50 x 50 x 50 mm at 1.8 x 109 and 3 x 1010 nanoparticles, respectively. A 219 mW of 830 nm laser light was used to illuminate the sample. A 22 active fibers made of silica with a core diameter of 220 μm was used to deliver the illumination source. Another bundle of fibers with length ~2 m used to collect Raman photons from the opposite side of the sample [7]. Raman spectra were collected for 50 seconds. SESORS analysis of 50x50x50 mm tissue demonstrated a higher signal intensity at 1070 cm-1 due to higher concentration of nanoparticles [6]. However, the 1250-1600 cm-1 region showed significant signal loss. This can be attributed to absorption of water and myoglobin under a more powerful laser with a longer acquisition time. On top of that, Raman reporters were used in this study instead of NIR dye tag because they were designed to contain high Raman cross-sections, which generate stronger Raman signals per molecule. At the same time, the Raman reporters were in resonance with the excitation wavelength used in the study, leading to an even higher Raman signal. As such, this study was able to capture Raman photons at a greater depth than the previous study.

Dey (2022) uses SESORS to study breast cancer through a 71 mm of heterogeneous tissue [8]. Gold nanoparticles loaded with Raman reporters such as BPT were injected subcutaneously into a mouse bearing breast cancer tumor at 1.5 x 109 nanoparticles twice. A 350 mW of 830 nm laser light was used to illuminate the sample in a point-like configuration. A bundle of fibers was shaped into a ring configuration to collect Raman photons at an offset distance of 5 mm away from the illumination source. SESORS analysis with an initial dose of 1.5 x 109 nanoparticles were able to detect the Raman signature peak of BPT at 1079 cm-1 in tumors located near the skin surface, which is relevant to human skin cancer or head and neck cancer. However, to visualize deeply seated tumors, a booster dose of 1.5 x 109 nanoparticles was injected to the mice. Inductively coupled plasma mass spectrometry (ICP-MS) was used to confirm a net accumulation of 1012 nanoparticles in the deeply seated tumor after two separate doses. As such, the 1079 cm-1 of the BPT Raman reporter was still observable through 71 mm heterogeneous tissue.

Resolution edit

Linear Offset Induced Image Drag edit

 
Figure 5: While SESORS assumes detected light comes from excited molecules beneath the excitation point, off-target objects underneath the collection point may also be excited and imaged. (Adapted from [9])

The Faulds group identified an image reconstruction artifact when performing SESORS measurements they deemed as “Linear Offset Induced Image Drag” (LOIID) [9]. When the collection measurement is taken some distance δx away from the excitation, LOIID causes the reconstructed image to be offset in the negative x direction with a magnitude proportional to δx. As seen in Figure 5, LOIID is caused by the unexpected excitation of objects between the excitation and collection points or beneath the collection point. During image reconstruction, the assumption that the detected signal originates from directly beneath the collection point causes the image to be shifted in the negative x direction compared to the ground truth. SESORS imaging requires obtaining several individual measurements across a two dimensional plane and Berry et al. notes that LOIID can affect images when the “offset” distance between the collection and detection points is larger than the step size between measurements as is the case in high-resolution SESORS images. Therefore, they note that contrary to expectation, a high-resolution image is at an increased risk of spatial distortion compared to low-resolution images. In their experiment in which they buried powder behind 15 mm of porcine tissue, they saw a 1 pixel offset which corresponded to a distance between 1.25 and 2.5 mm. The authors proposed measuring a circular pattern radially from the excitation point to reduce image distortion.

Oversampling edit

The Haigis group investigated the effects of oversampling in SESORS measurements [10]. Oversampling refers to the practice of repeatedly measuring a specific location within a sample, ensuring comprehensive coverage across multiple measurements. In this paper, the authors measured a 5 mm x 5 mm x 2 mm PTFE prism underneath a mouse skull and skin layer and varied the degree of oversampling. They saw dramatic improvement from oversampling each location two to five times, but saw limited resolution enhancement from five to ten times.

Nanoparticle Usage edit

 
Figure 6: Transmission electron microscopy (TEM) image of the synthesized gold nanostar and electromagnetic field simulation shows significantly enhanced electromagnetic field at GNS tips. (Adapted from [11])

While the pool of unique nanoparticle geometries and compositions is vast, SESORS tends to primarily use only two different types: gold nanospheres and gold nanostars. Silver is typically avoided due to its cytotoxicity making it undesirable for in-vivo imaging [12]. Gold nanospheres, typically 2-100 nm in diameter [13], offer a SERS enhancement factor of 106 [14]. They benefit from a simple synthesis method which enables uniformity amongst batches and homogeneity within batches. Additionally, their uniform surface aids in inducing uniform enhancement across its surface. Gold nanospheres are the most common nanostructure currently employed in SESORS measurements [7] [15] [16] [17] [18].

Gold nanostars represent another nanoparticle type that has gained increasing traction in the SESORS technique. Gold nanostars have multiple branches that protrude from an inner gold core. These protrusions have sharp tips which locally enhance the electromagnetic field and increase the SERS signal as much as 109 [14]. Their unique shape allows them to be highly tunable and support different plasmon resonances. Gold nanostars have a relatively complex synthesis method which can cause nonuniform star formation and properties especially between batches. Gold nanostar use has gradually become more popular for SESORS in recent years [19].

Renal clearance and liver accumulation of nanoparticles is still an unsolved problem which will need to be addressed for nanoparticle imaging to become an established technique [20].

Functionalization of Gold Nanoparticles edit

Nanoparticle functionalization refers to the technique of binding molecular elements to the surface of nanoparticles. While many different functionalization moieties have been utilized in research, Raman reporter conjugation and bioreceptor conjugation are most common in SESORS studies.

Raman reporters are examples of resonant dyes whose electronic state energy matches the wavelength used to image. This dramatically increases the occurrence of Raman scattered light which can similarly be enhanced in what is called Surface Enhanced Resonance Raman (SERRS). Raman reporters have characteristic SERS spectra and by conjugating these reporters to nanoparticles and measuring for said spectra, real-time in-vivo tracking of nanoparticles becomes possible. Common reporters in SESORS are typically resonant in the near infrared to increase the excitation light source penetration into the tissue [10].

Bioreceptors have also been conjugated to nanoparticles for use in SESORS. These bioreceptors are typically specific for an antigen on an antigen presenting tumor cell allowing specific localization of nanoparticles into tumor tissue. An antibody bioreceptor is typically chosen for SERS if a bioreceptor is to be used, but aptamers (single stranded nucleic acids that fold into tertiary conformations) have also been used for breast cancer specificity [16]. Two recent papers chose not to functionalize their nanoparticles with bioreceptors and instead relied on the Enhanced Permeability and Retention (EPR) effect. The EPR principle relies on relatively high metabolism of tumor tissue which takes in more material (including nanoparticles) from the bloodstream to rapidly grow and, as a result, it creates a highly concentrated area of nanoparticles able to be detected via SESORS [20].

Applications edit

Applications of the SESORS technique include glucose monitoring, neurochemical monitoring, breast cancer detection, glioblastoma detection, and glioblastoma imaging [10] [16] [17] [18] [21].

Neurochemical Monitoring edit

The Sharma group has utilized the SESORS technique as a way to monitor the concentrations of several different neurotransmitters [18]. Using gold nanospheres, the group demonstrated detection capabilities up to 18 mm in a gel behind a rat skull fragment. They measured with a 1 mm offset in-vivo by injecting 100 μM of serotonin and gold nanoparticles directly into the brain and were successfully able to recover the serotonin peaks.

The group followed the typical SESORS data processing methods and initially took a measurement with no offset to obtain a SERS spectra of the surface of the sample. Following this, they took a measurement with a set offset and subtracted the first measurement from this to eliminate surface contributions. They compared this subtracted spectra to that of a reference neurochemical to find their limit of detection.

Glioblastoma Detection edit

The Vo-Dinh group used the SESORS method to detect glioblastomas in-vitro [21]. In their paper, they functionalized gold nanostars with the Raman reporter Cy7.5. They incorporated these particles into a gel layer which was buried beneath 4 mm of empty gel. The entire gel phantom was placed beneath a fragment of a monkey skull to simulate in-vivo measuring barriers. They used the previously mentioned Inverse-SORS set-up to reduce spectral distortions and conducted measurements using a 5 mm offset and a 785 nm wavelength laser. Using this technique, they were able to recover the Cy7.5 peaks.

 
Figure 7: Results from [10]. (A-C) MRI measurements of glioblastoma. (D-G) SESORRS measurements of the same area. (H-K) Region of interest of SESORRS measurements. (L-O) Spectra from SESORRS measurement. (P-R) Histology of brain following sacrifice.

Glioblastoma Imaging edit

A recent study by the Haigis group modified the Vo-Dinh method to image, rather than solely detect, glioblastomas in-vivo [10]. The group functionalized gold nanostars with the Raman reporter IR780p and injected them into the tail vein of a mouse induced with glioblastoma. Similar to the Vo-Dinh group, they relied on the EPR effect to obtain a selectively high concentration of nanoparticles in the tumor region. Using a 785 nm wavelength laser, the researchers scanned across the head of the mouse with a spatial offset of 1.5 mm. Their SESORS measurements were confirmed by MRI and histology and they were also able to see a second region of interest (ROI) that was only visible 3.5 mm deep.

Limitations edit

The SESORS technique has several limitations. Most notably, it requires the researcher to scan over the imaging area one measurement at a time. This process is complex and time-consuming, and due to the lateral distance dependence of SESORS imaging, the researcher would be unable to measure multiple spots at once to speed up the process. Additionally, the Vo-Dinh group noted that scaled subtraction is not a perfect solution to recover depth measurements as a highly scattering top layer can prevent penetration to the bottom layer [21]. Particles may not be distributed uniformly in the subject which would lead to variation in signals for molecular location studies such as those done by the Sharma group [18]. Finally as mentioned previously, the cytotoxicity and renal clearing of gold nanoparticles is often debated which would prevent its adaptation into human trials.

References edit

  1. ^ a b Jones, R. R., Hooper, D. C., Zhang, L., Wolverson, D., & Valev, V. K. (2019). Raman Techniques: Fundamentals and Frontiers. Nanoscale research letters, 14(1), 231. https://doi.org/10.1186/s11671-019-3039-2
  2. ^ Bonales, L. J., Elorrieta, J. M., Lobato, Á., & Cobos, J. (2016). Raman Spectroscopy, a Useful Tool to Study Nuclear Materials. In Applications of Molecular Spectroscopy to Current Research in the Chemical and Biological Sciences.
  3. ^ Laura J. Bonales, Jone M. Elorrieta, Álvaro Lobato and Joaquin Cobos (October 5th 2016). Raman Spectroscopy, a Useful Tool to Study Nuclear Materials, Applications of Molecular Spectroscopy to Current Research in the Chemical and Biological Sciences, Mark T. Stauffer, IntechOpen, DOI: 10.5772/64436.
  4. ^ a b Mosca, S., Conti, C., Stone, N. et al. Spatially offset Raman spectroscopy. Nat Rev Methods Primers 1, 21 (2021). https://doi.org/10.1038/s43586-021-00019-0
  5. ^ a b Han, X.X., Rodriguez, R.S., Haynes, C.L. et al. Surface-enhanced Raman spectroscopy. Nat Rev Methods Primers 1, 87 (2021). https://doi.org/10.1038/s43586-021-00083-6
  6. ^ a b c Stone, N., Faulds, K., Graham, D., & Matousek, P. (2010). Prospects of deep Raman spectroscopy for noninvasive detection of conjugated surface enhanced resonance Raman scattering nanoparticles buried within 25 mm of mammalian tissue. Analytical chemistry, 82(10), 3969-3973.
  7. ^ a b Stone, N., Kerssens, M., Lloyd, G. R., Faulds, K., Graham, D., & Matousek, P. (2011). Surface enhanced spatially offset Raman spectroscopic (SESORS) imaging–the next dimension. Chemical Science, 2(4), 776-780.
  8. ^ Dey, P., Vaideanu, A., Mosca, S., Salimi, M., Gardner, B., Palombo, F., Uchegbu, I., Baumberg, J., Schatzlein, A., Matousek, P., & Stone, N. (2022). Surface enhanced deep Raman detection of cancer tumour through 71 mm of heterogeneous tissue. Nanotheranostics, 6(3), 337–349. https://doi.org/10.7150/ntno.71510
  9. ^ a b Berry, M. E., McCabe, S. M., Sloan-Dennison, S., Laing, S., Shand, N. C., Graham, D., & Faulds, K. (2022). Tomographic Imaging and Localization of Nanoparticles in Tissue Using Surface-Enhanced Spatially Offset Raman Spectroscopy. ACS Applied Materials & Interfaces, 14(28), 31613-31624.
  10. ^ a b c d e Nicolson, F., Andreiuk, B., Lee, E., O’Donnell, B., Whitley, A., Riepl, N., ... & Haigis, K. M. (2024). In vivo imaging using surface enhanced spatially offset raman spectroscopy (SESORS): balancing sampling frequency to improve overall image acquisition. npj Imaging, 2(1), 7.
  11. ^ Yuan, H., Khoury, C. G., Hwang, H., Wilson, C. M., Grant, G. A., & Vo-Dinh, T. (2012). Gold Nanostars: Surfactant-Free Synthesis, 3D Modelling, and Two-Photon Photoluminescence Imaging. Nanotechnology, 23(7), 075102.
  12. ^ de Lima, R., Seabra, A. B., & Durán, N. (2012). Silver nanoparticles: a brief review of cytotoxicity and genotoxicity of chemically and biogenically synthesized nanoparticles. Journal of Applied Toxicology, 32(11), 867-879.
  13. ^ Cai, W., Gao, T., Hong, H., & Sun, J. (2008). Applications of gold nanoparticles in cancer nanotechnology. Nanotechnology, science and applications, 17-32.
  14. ^ a b Golmohammadi, S., & Etemadi, M. (2019). Analysis of plasmonic gold nanostar arrays with the optimum sers enhancement factor on the human skin tissue. Journal of Applied Spectroscopy, 86(5), 925-933.
  15. ^ Ma, K., Yuen, J. M., Shah, N. C., Walsh Jr, J. T., Glucksberg, M. R., & Van Duyne, R. P. (2011). In vivo, transcutaneous glucose sensing using surface-enhanced spatially offset Raman spectroscopy: multiple rats, improved hypoglycemic accuracy, low incident power, and continuous monitoring for greater than 17 days. Analytical chemistry, 83(23), 9146-9152.
  16. ^ a b c Kapara, A. (2019). Imaging of breast cancer using SERS and SESORS.
  17. ^ a b Moody, A. S., Baghernejad, P. C., Webb, K. R., & Sharma, B. (2017). Surface enhanced spatially offset Raman spectroscopy detection of neurochemicals through the skull. Analytical chemistry, 89(11), 5688-5692.
  18. ^ a b c d Payne, T. D. (2019). Neurological Disease Detection Using Surface Enhanced Spatially Offset Raman Spectroscopy (SESORS).
  19. ^ Andreiuk, B., Nicolson, F., Clark, L. M., Panikkanvalappil, S. R., Rashidian, M., Harmsen, S., & Kircher, M. F. (2022). Design and synthesis of gold nanostars-based SERS nanotags for bioimaging applications. Nanotheranostics, 6(1), 10.
  20. ^ a b Haute, D. V., & Berlin, J. M. (2017). Challenges in realizing selectivity for nanoparticle biodistribution and clearance: lessons from gold nanoparticles. Therapeutic delivery, 8(9), 763-774.
  21. ^ a b c Odion, R. A., Strobbia, P., Crawford, B. M., & Vo‐Dinh, T. (2018). Inverse surface‐enhanced spatially offset Raman spectroscopy (SESORS) through a monkey skull. Journal of Raman Spectroscopy, 49(9), 1452-1460.
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