Isotope Corrected Image Quantitation

isotope-corrected-image-quantitation

Summary

Convert isotope-corrected mass spectrometry ion-image intensities into quantified lipid abundance values by normalizing against user-defined internal standards. This skill enables absolute quantitation of spatial lipid distributions in MSI data by dividing target lipid intensity matrices by internal standard intensity, handling division-by-zero artifacts.

When to use

Apply this skill after isotopic correction has been performed on MSI ion images and you need to convert normalized intensities into absolute quantitative values. Trigger when: (1) you have isotope-corrected intensity matrices stored in HDF5 format (image_type='isotope'), (2) you have selected a lipid species as the quantitation target, (3) you have identified and located an appropriate internal standard lipid with known quantity (pmol/mm²), and (4) you want to toggle between raw, isotope-corrected, and quantified image views for validation.

When NOT to use

• Input intensity matrix has not undergone isotopic correction (image_type ≠ 'isotope'); apply isotope correction first.
• No suitable internal standard has been defined or located in the dataset; quantitation requires a known-quantity standard.
• Internal standard intensity is uniformly zero or below detection threshold across all pixels; normalization will produce NaN/zero matrices.

Inputs

• HDF5 MSI export file with image_type='isotope' attribute
• Isotope-corrected intensity matrix (n_features × n_pixels, float32)
• Feature metadata table (featureData) with feature_id and m/z
• User-defined internal standard identifier (sample ID or feature name)
• Target lipid feature identifier (sample ID or feature name)

Outputs

• Quantified intensity matrix (single feature × n_pixels, float32)
• HDF5 MSI export file with image_type='quant' attribute
• Updated featureData metadata reflecting quantified target
• Quantified ion image (toggleable view in LipidQMap GUI)

How to apply

Load the HDF5 MSI export file containing isotope-corrected intensities (verified by root attribute image_type='isotope') using an HDF5 reader (h5py or equivalent). Extract the isotope-corrected intensity matrix from spectraData/intensity (shape: n_features × n_pixels, float32) and retrieve both the target lipid feature row and the internal standard feature row by matching featureData/feature_id against user-defined identifiers. Divide the target lipid intensity vector element-wise by the internal standard intensity vector to produce normalized quantitation. Handle division-by-zero pixels (where standard intensity ≤ 0) by masking them as NaN or zero to avoid spurious values. Write the resulting quantified intensity matrix to a new HDF5 file following Cardinal::HDF5 conventions, updating the root attribute image_type to 'quant' and featureData metadata to reflect the single quantified target. Validate by toggling the image view between raw, isotope-corrected, and quantified modes to confirm spatial patterns are preserved and intensity scales are reasonable.

Related tools

• LipidQMap (Graphical interface for importing imzML files, performing isotopic correction, selecting internal standards, and toggling between raw, isotope-corrected, and quantified image views; exports HDF5 containers following Cardinal::HDF5 conventions) — https://github.com/swinnenteam/LipidQMap
• Cardinal (Defines HDF5 container conventions and metadata structure for MSI data storage; LipidQMap writes exports following Cardinal::HDF5 standard) — https://cardinalmsi.org
• h5py (HDF5 reader/writer library for loading and writing isotope-corrected and quantified intensity matrices and metadata in Python)

Evaluation signals

• Output HDF5 root attribute image_type equals 'quant' (not 'isotope')
• Quantified intensity matrix has shape (1, n_pixels) or single-feature subset, with values normalized relative to internal standard baseline
• No NaN or infinite values appear in quantified pixels where both target and standard intensity are > 0
• Spatial patterns in quantified image preserve the spatial distribution visible in isotope-corrected image, only with intensity rescaled
• Division-by-zero pixels (standard intensity ≤ 0) are consistently masked as NaN or zero across all quantified features

Limitations

• Quantitation accuracy depends critically on internal standard quality and homogeneous spatial distribution; non-uniform standard distribution will introduce spatial bias.
• Division-by-zero handling (masking as NaN or zero) is a lossy operation; downstream analyses must account for masked pixels.
• The skill assumes the user has correctly identified and defined the internal standard; mislabeled or missing standards will produce invalid quantitation.
• LipidQMap currently available only for Windows 10+ and Mac (Apple silicon M1+); quantitation workflow unavailable on Linux or Intel Mac.

Evidence

• [other] LipidQMap performs quantitation based on user-defined internal standards, enabling conversion of ion-image intensities to quantified values.: "LipidQMap performs quantitation based on user-defined internal standards, enabling conversion of ion-image intensities to quantified values."
• [other] Extract the isotope-corrected intensity matrix from spectraData/intensity (shape: n_features × n_pixels, float32). Read the user-provided internal standard definition (sample identifier and/or feature name). Divide the target lipid intensity vector element-wise by the internal standard intensity vector (normalized quantitation); handle division-by-zero pixels (standard intensity ≤ 0) by masking them as NaN or zero.: "Divide the target lipid intensity vector element-wise by the internal standard intensity vector (normalized quantitation); handle division-by-zero pixels (standard intensity ≤ 0) by masking them as"
• [other] The software allows toggling between raw, isotope-corrected, and quantified image views.: "The software allows toggling between raw, isotope-corrected, and quantified image views."
• [intro] Can toggle view between raw, isotope corrected and quantified images.: "Can toggle view between raw, isotope corrected and quantified images."
• [methods] LipidQMap writes MSI exports as HDF5 containers that follow the Cardinal::HDF5 conventions.: "LipidQMap writes MSI exports as HDF5 containers that follow the Cardinal::HDF5 conventions."