Method Article

Correlative Optical Spectroscopy and Mass Spectrometry Imaging Methodology to Visualise Drug Distribution in a Soft Tissue Section

DOI:

10.3791/67383

⸱

June 20th, 2025

 ,  ,  ,  ,  ,  ,  , 
1Chemical & Biological Sciences Department, National Physical Laboratory, 2Department of Life Sciences, University of Bath, 3Haleon CH SARL, 4School of Chemistry & Chemical Engineering, University of Surrey

In This Article

Summary

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This study presents a method for correlative imaging of drugs in soft tissues using nonlinear optical spectroscopy and mass spectrometry imaging. Combining high-resolution skin imaging with sensitive drug detection offers a valuable approach to study drug distribution in the skin, critical for the development of superior topical products.

Abstract

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A new correlative imaging methodology combining sub-micron spatial resolution with sensitive drug detection by optical spectroscopy and mass spectrometry imaging has been developed to visualise chemical distribution upon drug application in soft tissue. In this example, the method has been tested on excised skin tissue after in vitro topical application of a commercial nonsteroidal anti-inflammatory drug product for 16 hours. Non-destructive optical spectroscopic methods, including stimulated Raman scattering, second harmonic generation, and two-photon fluorescence microscopies, were first employed to map the skin structure and morphology. Subsequently, the same skin tissue samples were analysed via time-of-flight secondary ion mass spectrometry (ToF-SIMS), which enabled enhanced sensitivity for the detection of diclofenac across the outermost skin layers - epidermis and dermis. Image registration methods were devised to integrate the optical and mass spectrometric data. This approach combines label-free, high-resolution visualisation of tissue structure with sensitive chemical detection, and represents a valuable tool for investigating drug distribution in skin and potentially, in other soft biological tissues.

Introduction

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Understanding the rate, extent, and drivers of the distribution of active pharmaceutical ingredients within soft biological tissues following their topical or systemic application is crucial to elucidate the mechanisms underlying tissue-specific drug uptake, metabolism, and clearance, (i.e., a deeper understanding of drug pharmacokinetics). Here, we present a novel correlative imaging method integrating nonlinear optical spectroscopies and mass spectroscopy imaging for label-free visualisation of the tissue structure and the distribution of topical drugs within the same tissue sample1.

Raman spectroscopy (RS) has emerged as a valuable tool for mapping drug distribution within cells and tissues with high spatial resolution and molecular specificity2. RS relies on the inelastic scattering of light3 by a sample of interest permitting a detailed chemical characterisation via the characteristic vibrational modes of molecules therein, without the need for external labels. However, the long acquisition times to produce high-resolution images can potentially compromise the integrity of sensitive biological samples. Additionally, when probing deeper tissue layers, scattering and absorption of light by the tissue can attenuate the Raman signal, further limiting its sensitivity. Stimulated Raman Scattering (SRS) microscopy represents a significant advancement over conventional RS, leveraging pulsed laser excitation and detection of the stimulated Raman signal4. SRS microscopy allows 2-D and 3-D rapid image acquisition with high spatial resolution and - when performed in tandem with second harmonic generation (SHG) and two photon excited fluorescence (TPEF) microscopies - can provide a comprehensive image of connective tissues, collagen, and elastin1,5,6,7,8,9. SHG microscopy is a nonlinear optical technique that relies on the interaction of light with non-centrosymmetric structures in a sample, generating a signal at half the wavelength of the incident light. It is particularly useful for imaging ordered structures like collagen in biological tissues. TPEF is another nonlinear microscopy technique where two lower-energy photons simultaneously excite a fluorophore, causing it to emit fluorescence. TPEF allows deep tissue imaging with reduced photodamage, as the excitation light is in the near-infrared range, which penetrates deeper into biological samples.

Mass spectrometry imaging (MSI) is a powerful analytical technique that combines the capabilities of mass spectrometry with spatial information, allowing label-free identification of a wide range of molecules10,11,12. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) operates by bombarding the sample surface with high-energy primary ions, causing the ejection of secondary ions from the surface. These secondary ions are then accelerated toward a time-of-flight analyser, where their mass-to-charge ratios are determined. This analysis allows for the identification of molecular fragments and isotopic variations with high sensitivity and resolution. Valuable applications of ToF-SIMS have been demonstrated in biological and pharmaceutical research for the study of chemicals and biomolecules in cells13, tissues14,15, and organs15.

Both SRS and ToF-SIMS have been used independently to study the distribution of drugs in different skin models. However, it is most valuable to use these techniques in combination to benefit from their complementarity. In this study, we describe a workflow to combine the optical microscopies (SRS, TPEF and SHG) with ToF-SIMS to obtain images of the skin morphology with sub-micron spatial resolution (provided by the optical methods) overlayed with the drug signal detected with superior sensitivity (provided by the ToF-SIMS). The approach has been used to address the challenging example of visualising the distribution of diclofenac in excised skin tissues treated with a commercial topical formulation (Voltaren gel). The criteria for success included high chemical sensitivity to detect diclofenac at its therapeutic concentration, and sufficient spatial resolution to resolve the skin structure. Although diclofenac content in different skin layers can be quantified after topical treatment through laborious and technically demanding methods such as tape stripping followed by quantification16, or via open flow microperfusion17, these approaches cannot elucidate excipient-dependent diclofenac partitioning, penetration, retention, and depth distribution in the individual skin layers, which are essential factors aiding the product development phase.

Prior to the measurement methodology described below, Voltaren Forte gel (containing 2.32 % diclofenac diethylammonium) or a corresponding placebo gel (supplied by Haleon CH SARL) was applied on the skin surface for different periods (4, 12, 16, or 24 h). After removal of any residual formulation, SRS and ToF-SIMS measurements on the same skin samples were performed; full details of the methodology are described in the original manuscript1.

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Protocol

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Ethical statement: Human skin samples were obtained from Tissue Solutions Ltd, Glasgow, UK, by Charles River Laboratories (CRL) in Edinburgh, UK. All anonymous samples were acquired in compliance with the legal and ethical standards of the collection country, with ethical approval and informed consent from the donors or their closest relatives.

1. Skin sectioning

A cryostat was used to produce sections of the skin tissues.

  1. Transport the treated skin disks out of the -20 °C freezer and cut a small piece (~1.0 cm x 1.0 cm) from the center of the disk.
  2. Mount the sample on the chuck in the cryostat over a frozen water droplet. Do not use optimal cutting temperature (OCT) compound or other embedding media.
  3. Set the blade and sample temperature at - 20 °C and - 16 °C, respectively.
  4. Section 30 µm-thick section onto a glass coverslip (#1.5, Fisher Scientific).
  5. Perform SRS and ToF-SIMS immediately or alternatively, the sample may be vacuum-packed for storage at -80 °C.
  6. Desiccate for 20 min prior to use.

2. SRS imaging

SRS, SHG and TPEF microscopy was performed using a coherent Raman microscope. Two picosecond laser pulses were generated by a 1031.2 nm Stokes beam, overlapped spatially and temporally with a tunable pump beam. The Stokes beam, modulated at 20 MHz, facilitated the detection of stimulated Raman loss signals via transmission. A silicon-based detector, coupled with a lock-in amplifier, was utilised for signal detection. Another channel was employed to collect second harmonic and emitted fluorescence signals, employing a photomultiplier tube for detection.

  1. Install suitable objective and condensers lenses for multiphoton tissue imaging, in this case a water immersion 40x magnification lens (1.1 NA) in conjunction with a short working distance air condenser lens (0.9 NA).
  2. Place the mounted tissue section onto the SRS microscope sample stage so the tissue is on the same face of the microscope slide as the condenser lens. Focus the objective lens on the tissue section, and then optimize the condenser height.
  3. Set the laser power to appropriate values to obtain good signal-to-noise ratio without damaging the tissue. In this example, approximately 10 mW for the pump beam and 30 mW for the Stokes beam were applied at the sample. Refer to Tsikritsis et al for practical considerations for SRS measurements4.
  4. Acquire a mosaic image of the whole section with 512 x 512 pixels resolution corresponding to 290 µm x 290 µm at X1 zoom with an imaging speed of 400 Hz and line average of 1 at 2850 cm-1 corresponding to CH2 stretching.
  5. Within the mosaic image of the whole section, choose a region of interest (ROI) with the following considerations: (i) it is positioned at the center, avoiding the outermost 20 % of the sample perimeter where there could be un-dosed skin which was clamped in the Franz cell apparatus; (ii) it is sufficiently flat to be examined within the same optical depth level; (iii) it has distinct structural features that would assist its visual identification when the sample is transferred to ToF-SIMS.
  6. Apply consistent gain settings across the study for SRS and SHG/fluorescence detectors, and acquire images in (i) the C-H stretching region (at 2945 cm-1, 2850 cm-1 and 2650 cm-1 corresponding to CH3, CH2 and off-resonance control, respectively); (ii) the fingerprint region (at 1666 cm-1 and 1723 cm-1 corresponding to Amide I and off-resonance control, respectively); (iii) the wavenumber corresponding to the on- and off-resonance related to the applied drug; in this example, at 1586 cm-1 and 1530 cm-1 corresponding to C=C and off-resonance, respectively.

After SRS imaging, immediately transfer the sample to the ToF-SIMS setup for analysis.

3. ToF-SIMS imaging

Time-of-flight secondary ion mass spectrometry imaging was performed using a 30 keV Bi3+ primary ion beam with a current of 0.2 pA.

  1. Choose appropriate acquisition settings; in this example, negative ion polarity was used, with a 100 ms duty cycle time, a mass range of m/z 0-900, and a beam diameter of 5 µm. A 20 eV electron flood gun at 5 µA was used for charge compensation.
  2. Acquire an overall image by the stage macro raster mode to map the entire tissue section with a field of view depending on the tissue dimensions (in our case we used 2.5 to 3.0 mm x 8.5 to 9.0 mm). This overall image is formed from a mosaic of smaller images. In this example, each had a field of view of 0.5 mm x 0.5 mm (256 x 256 pixels) with 1 ion beam shot per pixel, resulting in an ion dose of 8.18 x 108 ions/cm2.
  3. Utilize the same method to capture images of the ROI by selecting an appropriate field of view; in this instance, it was 1.0 mm x 0.5 mm, with 4 shots per pixel per frame and 10 frames per patch, corresponding to an ion dose of 1.31 x 1011 ions/cm2.
  4. To ensure quality control, analyze tissue homogenate samples immediately before and after examining each skin section. Use a field of view of 0.5 mm x 0.5 mm (256 x 256 pixels) with 1 shot per pixel and 1 frame per scan, conducting a total of 15 scans. This setup corresponds to an ion dose density of 3.27 x 1010 ion/cm2.
  5. After acquisition, the resulting mass spectra can be calibrated using H−, C−, C2−, and C3− ions.
  6. Data acquisition and extraction were performed using Surface Lab 7.1 software.

4. Image registration and data analysis using MATLAB

  1. Reduce SIMS and SRS images to 3 dimensions each using non-negative matrix factorisation to be visualised as red, green, and blue color channels.
  2. Choose matching features between these two non-matrix factorization images by selecting the Matlab control point selection tool "cpselect" (Matlab, Mathworks, 2019b and Image Processing Toolbox).
  3. Use the "cp2tform" and "imtransform" functions to perform registration, applying an affine transformation with the SIMS data as the fixed images and the optical spectroscopy data as the moving images.
  4. Where multiple peaks are detected in the ToF-SIMS data for the drug of interest, sum together the intensities of these peaks to create a combined drug ion intensity.
  5. Extract the average total ion count of the two homogenate datasets (before and after) for each corresponding skin tissue sample. Using this corresponding value, normalise the intensities in the ToF-SIMS data of the drug ion in each skin image.
  6. After registration, create an overlay of the optical spectroscopy and SIMS data by assigning the respective images to the RGB channels: red (SRS image for CH2), green (SHG image for collagen), and blue (SIMS image for diclofenac, including signals from various ions at m/z 214.04, 216.04, 250.02, 252.02, 294.01, and 296.01).

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Results

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Figure 1 presents the results of feature-based image registration, displaying the registered overlay images of SRS, SHG, and SIMS for two skin samples-one treated with a placebo (Figure 1a) and the others with Voltaren gel for 4 hours (Figure 1b) and 16 hours (Figure 1c). In this image, the summed drug intensity signal (from ToF-SIMS measurements) is depicted in blue, li...

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Discussion

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This method allows correlative imaging with nonlinear optical spectroscopy and mass spectrometry imaging to detect drug distribution in soft tissue with sub-micron spatial resolution and high sensitivity. Importantly, imaging is achieved without the use of potentially interfering labels that would be required for fluorescence-based microscopies. Further validation of the workflow involved the conventional hematoxylin and eosin (H&E) staining of a tissue section to elucidate the skin structure and permitted registrati...

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Disclosures

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MBB is an employee of Haleon CH SARL, the funding institution of the study.

Acknowledgements

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This study was funded by Haleon CH SARL. Contributions of NAB and RHG were partially supported by the Food and Drug Administration (FDA) of the U.S. Department of Health and Human Services (HHS) through a financial assistance award (1-U01-FD006533). This work was funded by the UK Department of Business, Energy, and Industrial Strategy through the projects NMS/ID74 and NMS/ST18 of the UK National Measurement System. The contents of this article are those of the authors and do not necessarily represent the official views of, nor an endorsement by, FDA/HHS or the U.S. Government. NAB is grateful for the support from the Community for Analytical Measurement Science for the 2020 CAMS Fellowship Award funded by the Analytical Chemistry Trust Fund.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
Coherent Raman microscope Leica Microsystemshttps://www.leica-microsystems.com/products/confocal-microscopes/p/leica-tcs-sp8-cars/
Human skin samples Tissue Solutions Ltd, Glasgow
Leica CM 1850 Cryostat Leica Biosystemshttps://www.leicabiosystems.com/en-fr/histology-equipment/cryostats/leica-cm1850/Discontinued
PicoEmerald-S laser systemAPE Berlinhttps://www.ape-berlin.de/en/cars-srs/
ToF SIMS 5IONToF GmbHhttps://spectral.se/products/tof-sims-5

References

$$\rightleftharpoonup{xx}$$ $$\longleftharp{xx}$$, $$\longrightharp{xx}$$,
  1. Belsey, N. A., et al. Visualisation of drug distribution in skin using correlative optical spectroscopy and mass spectrometry imaging. J Control Release. 364, 79-89 (2023).
  2. Pudlas, M., et al. Raman spectroscopy: A noninvasive analysis tool for the discrimination of human skin cells. Tissue Eng Part C Methods. 17 (10), 1027-1040 (2011).
  3. Raman, C. V., Krishnan, K. S. A new type of secondary radiation. Nature. 121 (3048), 501-502 (1928).
  4. Tsikritsis, D., Legge, E. J., Belsey, N. A. Practical considerations for quantitative and reproducible measurements with stimulated Raman scattering microscopy. Analyst. 147 (21), 4642-4656 (2022).
  5. Sarri, B., et al. Stimulated Raman histology: One to one comparison with standard hematoxylin and eosin staining. Biomed Opt Express. 10 (10), 5378-5384 (2019).
  6. Lee, M., et al. Recent advances in the use of stimulated Raman scattering in histopathology. Analyst. 146 (3), 789-802 (2021).
  7. Mansfield, J., Moger, J., Green, E., Moger, C., Winlove, C. P. Chemically specific imaging and in-situ chemical analysis of articular cartilage with stimulated Raman scattering. J Biophotonics. 6 (10), 803-814 (2013).
  8. Shi, L., Fung, A. A., Zhou, A. Advances in stimulated Raman scattering imaging for tissues and animals. Quant Imaging Med Surg. 11 (3), 1078-1101 (2021).
  9. Brzozowski, K., et al. Stimulated Raman scattering microscopy in chemistry and life science - development, innovation, perspectives. Biotechnol Adv. 60, 108003(2022).
  10. Buchberger, A. R., Delaney, K., Johnson, J., Li, L. Mass spectrometry imaging: A review of emerging advancements and future insights. Anal Chem. 90 (1), 240-265 (2018).
  11. Seeley, E. H., Caprioli, R. M. Molecular imaging of proteins in tissues by mass spectrometry. Proc Natl Acad Sci U S A. 105 (47), 18126-18131 (2008).
  12. Vanbellingen, Q. P., et al. Time-of-flight secondary ion mass spectrometry imaging of biological samples with delayed extraction for high mass and high spatial resolutions. Rapid Commun Mass Spectrom. 29 (13), 1187-1195 (2015).
  13. Singh, A. V., et al. ToF-SIMS 3D imaging unveils important insights on the cellular microenvironment during biomineralization of gold nanostructures. Sci Rep. 10 (1), 261(2020).
  14. Yoon, S., Lee, T. G. Biological tissue sample preparation for time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging. Nano Converg. 5 (1), 24(2018).
  15. Shi, X., et al. A ToF-SIMS methodology for analyzing inter-tissue lipid distribution variations and intra-tissue multilevel mass spectrometry imaging within a single rat. Microchem J. 200, 110235(2024).
  16. Louw, E. -V., et al. Comparative study on the topical and transdermal delivery of diclofenac incorporated in nano-emulsions, nano-emulgels, and a colloidal suspension. Drug Deliv Transl Res. 13 (5), 1372-1389 (2023).
  17. Hummer, J., et al. Optimization of topical formulations using a combination of in vitro methods to quantify the transdermal passive diffusion of drugs. Int J Pharm. 620, 121737(2022).
  18. Sjövall, P., et al. Imaging the distribution of skin lipids and topically applied compounds in human skin using mass spectrometry. Sci Rep. 8 (1), 16683(2018).
  19. Delvaux, X., Noël, C., Poumay, Y., Houssiau, L. Probing the human epidermis by combining tof-sims and multivariate analysis. Biointerphases. 18 (1), 011002(2023).
  20. Kolenc, O. I., Quinn, K. P. Evaluating cell metabolism through autofluorescence imaging of nad (p) h and fad. Antioxid Redox Signal. 30 (6), 875-889 (2019).
  21. Hanson, K. M., Clegg, R. M. Observation and quantification of ultraviolet-induced reactive oxygen species in ex vivo human skin. Photochem Photobiol. 76 (1), 57-63 (2002).
  22. Wang, J., et al. Non-invasive skin imaging assessment of human stress during head-down bed rest using a portable handheld two-photon microscope. Front Physiol. 13, 899830(2022).
  23. Brunetti, A., et al. Correlative morphologic and functional imaging for diagnosis, staging and follow up in aids: An overview. Q J Nucl Med. 39 (3), 201-211 (1995).
  24. Van Zyl, T., Van Rensburg, L. J., Naidoo, K., Merven, M., Opperman, J. F. Correlative imaging and histopathology of a complicated sinonasal teratocarcinosarcoma. SA J Radiol. 27 (1), 2548(2023).
  25. Huber, K., et al. Novel approach of MALDI drug imaging, immunohistochemistry, and digital image analysis for drug distribution studies in tissues. Anal Chem. 86 (21), 10568-10575 (2014).

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Tags

Correlative ImagingSkin TissueStimulated Raman ScatteringTwo Photon FluorescenceTime Of Flight SIMSImage RegistrationDrug Penetration

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