Imaging secondary ion mass spectrometry (SIMS) is a promising approach for chemically imaging the composition at the surface (top 5 nm) of a sample.  High-resolution secondary ion mass spectrometry (SIMS) performed on a Cameca NanoSIMS 50 has recently been combined with metabolic labeling to permit imaging the distributions of isotope-labeled lipids in the plasma membranes of intact cells with about 100 nm lateral resolution.  However, approaches that permit quantitatively assessing the presence of component-enriched domains on the sample surface are required to definitively test a multitude of hypotheses concerning plasma membrane organization.  Here we describe a computational statistics approach for evaluating whether local elevations in component-specific SIMS signals are statistically significant.  Though this approach was developed for the detection of lipid domains within biological membranes, it may also be applied to NanoSIMS images from a variety of samples to assess the presence of statistically significant elevations in component enrichment.

Statistical approaches for the detection of compositionally distinct domains in high-resolution secondary ion mass spectrometry images

244th National Meeting (2012)

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