Belsey, NA;
Tsikritsis, D;
Dondi, C;
Vorng, JL;
Dexter, A;
Shaw, M;
(2025)
Combining vibrational and fluorescence microscopies with mass spectrometry imaging for visualization of drug delivery.
In: Evans, Conor L and Chan, Kin Foong, (eds.)
Progress in Biomedical Optics and Imaging - Proceedings of SPIE.
(pp. p. 6).
SPIE: San Francisco, California, United States.
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Abstract
Recent advances in label-free chemical imaging approaches have yielded new methods for measuring drug distribution in biological tissues. Techniques include vibrational spectroscopies in addition to a range of powerful mass spectrometry imaging methods. These techniques offer complementary information, with different strengths and limitations. By combining datasets from several of these techniques using image registration, powerful visualization of cells and tissues can be achieved, enabling high chemical specificity and sensitivity with sub-micron spatial resolution. Here we present several correlative imaging examples that combine vibrational spectroscopic with mass spectrometric imaging, in addition to single and multiphoton fluorescence. This multimodal approach offers optimal visualization of biological structure, in addition to the measured drug distribution.
| Type: | Proceedings paper |
|---|---|
| Title: | Combining vibrational and fluorescence microscopies with mass spectrometry imaging for visualization of drug delivery |
| Event: | Visualizing and Quantifying Drug Distribution in Tissue IX (BiOS 2025) |
| Dates: | 25 Jan 2025 - 31 Jan 2025 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1117/12.3043629 |
| Publisher version: | https://doi.org/10.1117/12.3043629 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10208491 |
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