During the past decade, the field of mass spectrometry imaging (MSI) has greatly evolved, to a point where it has now been fully integrated by most vendors as an optional or dedicated platform that can be purchased with their instruments. However, the technology is not mature and multiple research groups in both academia and industry are still very actively studying the fundamentals of imaging techniques, adapting the technology to new ionization sources, and developing new applications. As a result, there are an important variety of data file formats used to store mass spectrometry imaging data and concurrent to the development of MSi collaborative efforts have been undertaken to introduce common imaging data file formats. However, few free software packages to read and analyze files of these different formats are readily available. We introduce here MSiReader, a free open source application to read and analyze high resolution MSI data from the most common MSi data formats. The application is built on the Matlab platform (Mathworks, Natick, MA) and includes a large selection of data analysis tools and features. People who are unfamiliar with the Matlab language will have little difficult navigating the user friendly interface, and users with Matlab programming experience can adapt and customize MSiReader for their own needs.
A major update to the mass spectrometry imaging (MSI) software MSiReader is presented, offering a multitude of newly added features critical to MSI analyses. MSiReader is a free, open-source, and vendor-neutral software written in the MATLAB platform and is capable of analyzing most common MSI data formats. A standalone version of the software, which does not require a MATLAB license, is also distributed. The newly incorporated data analysis features expand the utility of MSiReader beyond simple visualization of molecular distributions. The MSiQuantification tool allows researchers to calculate absolute concentrations from quantification MSI experiments exclusively through MSiReader software, significantly reducing data analysis time. An image overlay feature allows the incorporation of complementary imaging modalities to be displayed with the MSI data. A polarity filter has also been incorporated into the data loading step, allowing the facile analysis of polarity switching experiments without the need for data parsing prior to loading the data file into MSiReader. A quality assurance feature to generate a mass measurement accuracy (MMA) heatmap for an analyte of interest has also been added to allow for the investigation of MMA across the imaging experiment. Most importantly, as new features have been added performance has not degraded, in fact it has been dramatically improved. These new tools and the improvements to the performance in MSiReader v1.0 enable the MSI community to evaluate their data in greater depth and in less time. Graphical Abstract ᅟ.
Mass spectrometry imaging (MSI) allows for the direct monitoring of the abundance and spatial distribution of chemical compounds over the surface of a tissue sample. This technology has opened the field of mass spectrometry to numerous innovative applications over the past 15 years. First used with SIMS and MALDI MS that operate under vacuum, interest has grown for mass spectrometry ionization sources that allow for effective imaging but where the analysis can be performed at ambient pressure with minimal or no sample preparation. We introduce here a versatile source for MALDESI imaging analysis coupled to a hybrid LTQ-FT-ICR mass spectrometer. The imaging source offers single shot or multi-shot capability per pixel with full control over the laser repetition rate and mass spectrometer scanning cycle. Scanning rates can be as fast as 1 pixel/second and a spatial resolution of 45 μm was achieved with oversampling.
In the past 15 years, ambient ionization techniques have witnessed a significant incursion into the field of mass spectrometry imaging, demonstrating their ability to provide complementary information to matrix‐assisted laser desorption ionization. Matrix‐assisted laser desorption electrospray ionization is one such technique that has evolved since its first demonstrations with ultraviolet lasers coupled to Fourier transform‐ion cyclotron resonance mass spectrometers to extensive use with infrared lasers coupled to orbitrap‐based mass spectrometers. Concurrently, there have been transformative developments of this imaging platform due to the high level of control the principal group has retained over the laser technology, data acquisition software (RastirX), instrument communication, and image processing software (MSiReader). This review will discuss the developments of MALDESI since its first laboratory demonstration in 2005 to the most recent advances in 2021.
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