ABSTRACT
Mass spectrometry imaging (MSI) is a technique that can map analyte spatial distribution directly onto a tissue section. This enables the spatial correlation of molecular entities with a tissue morphology to be investigated. Analyte annotation in MSI is intrinsically linked to the mass accuracy of the data. Mass accuracy and analyte identification are determined by such factors as the experimental set up and the data processing workflow. We present an MSI data processing workflow that uses a label-free approach to compensate for mass shifts. The algorithms developed were designed to perform efficiently even for datasets much larger than computer's memory. Herein, we present the application of the developed processing workflow to a dataset with more than 13.000 pixels and â¼50.000 mass channels. We assessed the overall mass accuracy in the range m/z 400 to 1200 using silver and gold sputtered nanolayers. With our novel processing workflow we were able to obtain mass errors as low as 5â¯ppm using a TOF instrument.