Fusion of MALDI Spectrometric Imaging and Raman Spectroscopic Data for the Analysis of Biological Samples

Ryabchykov, Oleg; Popp, Juergen; Bocklitz, Thomas

doi:10.3389/fchem.2018.00257

Cited by 39 publications

(36 citation statements)

References 42 publications

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“…MSI and fluorescence microscopy can be merged in order to discover molecular partners of fluorescent proteins, such as the study led in Jones et al [ 30 ]. On another note, MSI and Raman spectroscopy images can be analyzed jointly to identify specific regions in the sample [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

Esmraldi: efficient methods for the fusion of mass spectrometry and magnetic resonance images

et al. 2021

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Background Mass spectrometry imaging (MSI) is a family of acquisition techniques producing images of the distribution of molecules in a sample, without any prior tagging of the molecules. This makes it a very interesting technique for exploratory research. However, the images are difficult to analyze because the enclosed data has high dimensionality, and their content does not necessarily reflect the shape of the object of interest. Conversely, magnetic resonance imaging (MRI) scans reflect the anatomy of the tissue. MRI also provides complementary information to MSI, such as the content and distribution of water. Results We propose a new workflow to merge the information from 2D MALDI–MSI and MRI images. Our workflow can be applied to large MSI datasets in a limited amount of time. Moreover, the workflow is fully automated and based on deterministic methods which ensures the reproducibility of the results. Our methods were evaluated and compared with state-of-the-art methods. Results show that the images are combined precisely and in a time-efficient manner. Conclusion Our workflow reveals molecules which co-localize with water in biological images. It can be applied on any MSI and MRI datasets which satisfy a few conditions: same regions of the shape enclosed in the images and similar intensity distributions.

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Section: Discussionmentioning

confidence: 99%

Esmraldi: efficient methods for the fusion of mass spectrometry and magnetic resonance images

et al. 2021

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“…Raman spectroscopy has also been correlated with mechanical measurement techniques (Unal and Akkus, 2015). Among the advanced techniques, a vibrant and promising field is the implementation of heterospectral imaging approaches, which directly interrelate the hyperspectral data of several modalities at the pixel level for a more comprehensive biomolecular analysis (Lasch and Noda, 2017, 2019; Bergholt et al, 2018; Ryabchykov et al, 2018). For instance, Lasch and Noda (2017) and Lasch and Noda (2019) introduced multimodal FT-IR, Raman, and MALDI-TOF imaging for tissue characterization.…”

Section: Advanced Raman Methodsmentioning

confidence: 99%

Raman Spectroscopy: Guiding Light for the Extracellular Matrix

Bergholt

Serio

Albro

2019

Front. Bioeng. Biotechnol.

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The extracellular matrix (ECM) consists of a complex mesh of proteins, glycoproteins, and glycosaminoglycans, and is essential for maintaining the integrity and function of biological tissues. Imaging and biomolecular characterization of the ECM is critical for understanding disease onset and for the development of novel, disease-modifying therapeutics. Recently, there has been a growing interest in the use of Raman spectroscopy to characterize the ECM. Raman spectroscopy is a label-free vibrational technique that offers unique insights into the structure and composition of tissues and cells at the molecular level. This technique can be applied across a broad range of ECM imaging applications, which encompass in vitro, ex vivo, and in vivo analysis. State-of-the-art confocal Raman microscopy imaging now enables label-free assessments of the ECM structure and composition in tissue sections with a remarkably high degree of biomolecular specificity. Further, novel fiber-optic instrumentation has opened up for clinical in vivo ECM diagnostic measurements across a range of tissue systems. A palette of advanced computational methods based on multivariate statistics, spectral unmixing, and machine learning can be applied to Raman data, allowing for the extraction of specific biochemical information of the ECM. Here, we review Raman spectroscopy techniques for ECM characterizations over a variety of exciting applications and tissue systems, including native tissue assessments (bone, cartilage, cardiovascular), regenerative medicine quality assessments, and diagnostics of disease states. We further discuss the challenges in the widespread adoption of Raman spectroscopy in biomedicine. The results of the latest discovery-driven Raman studies are summarized, illustrating the current and potential future applications of Raman spectroscopy in biomedicine.

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“…This data fusion consisted of adjusting the dimensionality and dynamic range of each data set and then merging the two matrixes into one. 8 Similarly, Neumann et al coregistered the MS and IR images using anatomical features of the individual PCA score images and then fused the data by up-sampling the MS image and down-sampling the IR image to adjust discrepancies between the spatial resolution. 4 Another data fusion strategy transformed the coordinate system of one imaging modality into the other in order to calculate the mean VSI spectra for regions which exhibit a certain intensity of a MSI peak or MSI fingerprint.…”

Section: Challenges Of Multimodal Imagingmentioning

confidence: 99%

Perspective on Multimodal Imaging Techniques Coupling Mass Spectrometry and Vibrational Spectroscopy: Picturing the Best of Both Worlds

et al. 2021

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Studies on complex biological phenomena often combine two or more imaging techniques to collect high-quality comprehensive data directly in situ , preserving the biological context. Mass spectrometry imaging (MSI) and vibrational spectroscopy imaging (VSI) complement each other in terms of spatial resolution and molecular information. In the past decade, several combinations of such multimodal strategies arose in research fields as diverse as microbiology, cancer, and forensics, overcoming many challenges toward the unification of these techniques. Here we focus on presenting the advantages and challenges of multimodal imaging from the point of view of studying biological samples as well as giving a perspective on the upcoming trends regarding this topic. The latest efforts in the field are discussed, highlighting the purpose of the technique for clinical applications.

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Fusion of MALDI Spectrometric Imaging and Raman Spectroscopic Data for the Analysis of Biological Samples

Cited by 39 publications

References 42 publications

Esmraldi: efficient methods for the fusion of mass spectrometry and magnetic resonance images

Esmraldi: efficient methods for the fusion of mass spectrometry and magnetic resonance images

Raman Spectroscopy: Guiding Light for the Extracellular Matrix

Perspective on Multimodal Imaging Techniques Coupling Mass Spectrometry and Vibrational Spectroscopy: Picturing the Best of Both Worlds

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