Evaluating limits of detection for single-cell elemental bioimaging by LA-ICP-TOFMS

Elemental bioimaging using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is widely used for studying metal exposure and the biological roles of metals in health and disease. Quantitative metal distributions can be assessed at spatial resolutions reaching the single-cell level. Current quantification relies on in-house matrix-matched standards, gelatine being the most common, as no certified biological reference materials exist. Based on the calibration, elemental maps are reconstructed deploying pixel-based quantitative values along with detection limits (LODs), critical for quality assurance. Image analysis allows to extract single-cell data for downstream quantification obtaining absolute elemental amounts (given as femtogram (fg) of metal per cell). Following image pre-processing and cell segmentation, extracted pixel sums are calibrated to reveal metal accumulation at single-cell level. While pixel-based analytical figures of merit are useful for assessing the instrumental performance, these metrics fall short when evaluating quantitative single-cell metal data. In this work, we propose a novel LOD strategy for single-cell LA-ICP-TOFMS imaging that utilizes gelatine micro-droplet calibrations and bootstrapped signal distributions from gelatine blanks. As micro-droplets do not exhibit homogenous elemental distributions, bootstrapping was employed to generate representative distributions from integrated signals over subsets of pixels. Depending on these distributions, isotope- and cell size-specific LODs are estimated. The different cell sizes are accounted for by the number of integrated pixels at a given spatial resolution. The proposed concept can be expanded to any quantitative imaging considering regions of interest (ROIs).