Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research

Abstract

Mass spectrometry imaging (MSI) enables the visualization of molecular distributions on complex surfaces. It has been extensively used in the field of biomedical research to investigate healthy and diseased tissues. Most of the MSI studies are conducted in a 2D fashion where only a single slice of the full sample volume is investigated. However, biological processes occur within a tissue volume and would ideally be investigated as a whole to gain a more comprehensive understanding of the spatial and molecular complexity of biological samples such as tissues and cells. Mass spectrometry imaging has therefore been expanded to the 3D realm whereby molecular distributions within a 3D sample can be visualized. The benefit of investigating volumetric data has led to a quick rise in the application of single-sample 3D-MSI investigations. Several experimental and data analysis aspects need to be considered to perform successful 3D-MSI studies. In this review, we discuss these aspects as well as ongoing developments that enable 3D-MSI to be routinely applied to multi-sample studies.

Keywords: 3D imaging; Data analysis; Experimental set-up; Mass spectrometry imaging.

Fig. 1.

Schematic representation of the different approaches in 3D mass spectrometry imaging (MSI). a Secondary ion mass spectrometry (SIMS) continuously alternates imaging and sputtering cycles. b Matrix-assisted laser desorption/ionization (MALDI) or desorption electrospray ionization (DESI) rely on the sectioning of the sample into a stack of consecutive sections which are then analyzed individually and their data reassembled afterward.

Fig. 2.

Applications of 3D mass spectrometry imaging (MSI). a 3D SIMS-MSI was used to study the permeation of ascorbic acid through ex vivo skin samples after the application of PBS or a hydrogel. The results showed a deeper permeation when a hydrogel is used. This article was published in [40] (copyright Elsevier). b Quantitative 3D MALDI-MSI of the anti-cancer drug paclitaxel in a malignant pleural mesothelioma tumor. Images indicate the drug is mostly located at the edge of the tumor. Figure adapted from [41] (licensed under CC BY 4.0: http://creativecommons.org/licenses/by/4.0/). c The application of advanced data analysis methods to a 3D DESI-MSI dataset of a human colorectal cancer sample revealed several metabolically different tumor subgroups highlighting the heterogeneity of tumors in three dimensions. Figure adapted from [19] (published by The Royal Society of Chemistry).

Fig. 3.

Experimental considerations in 3D-MSI. a When no randomization has been performed, the fluctuation of the overall signal intensity across every single section, represented by its total ion count (TIC), can be caused by other factors such as date of experiment, the slide, or the position of the section on the slide. b Assuming proper randomization and that close by sections should have similar molecular signals, we have recently proposed a z-direction based regression of molecular signals. Outliers are detected whose molecular signals are not in line with previous and successive sections. This article was published in [63] (copyright Elsevier).

Fig. 4.

Alignment strategies in tissue-section-based 3D-MSI. a Alignment based on embedded fiducial markers requires a previous embedding of the sample into a medium but delivers good results. Adapted with permission from [60] (copyright American Chemical Society). b An alignment based on optical images requires the optical images to be linked to the MSI data before data analysis, e.g., during the experiment. c Alignment based on only the MS images requires visible and well-defined structures in the images. The coarseness of these structures should match the spatial resolution of the MS images. Figure adapted from [48] (licensed under CC BY 4.0: http://creativecommons.org/licenses/by/4.0/).

Fig. 5.

Integration of 3D-MSI with other modalities. a A 3D MALDI-MSI dataset consisting of 162 consecutive sections of an oral squamous cell carcinoma was combined with the corresponding 3D stack of histological images. Both volumes were placed in the same space allowing the co-visualization of both modalities at the same depth. This article was published in [70] (copyright Elsevier). b A 3D MALDI-MSI dataset of glioblastoma in a mouse brain was also combined with MRI. The visualization on the left shows a molecule that highlights the tumor area and on the right, the same ion is overlaid with the MRI image. Adapted with permission from [71] (copyright American Chemical Society).