Internal Standard Ion Selection And Application

internal-standard-ion-selection-and-application

Summary

Select and apply user-defined internal standard lipid ions to normalize isotope-corrected ion-image intensities, enabling conversion of raw mass spectrometry imaging signals to quantified values. This skill is essential for converting relative ion intensities into absolute or semi-quantitative lipid abundance estimates across tissue or sample regions.

When to use

After isotope correction has been applied to MSI ion images, when you have sprayed or identified a reference lipid standard of known amount (pmol/mm²) and need to normalize target lipid intensities against this standard to remove matrix effects and enable cross-pixel and cross-sample comparisons. Use this skill when the goal is to move from raw or isotope-corrected intensity matrices to quantified image data suitable for statistical analysis or biomarker discovery.

When NOT to use

• Input ion images have not yet undergone isotope correction (use isotope correction skill first)
• No internal standard lipid has been identified, sprayed, or quantified in the sample
• The internal standard intensity is uniformly zero or near-detection limit across most pixels (normalization will produce unreliable or NaN-dominated output)

Inputs

• HDF5 MSI export file with image_type='isotope' (isotope-corrected ion images)
• User-defined internal standard specification (feature ID or name from database)
• Target lipid feature ID or name to be quantified
• featureData table with feature_id column for standard and target lookup

Outputs

• HDF5 MSI export file with image_type='quant' containing normalized quantified intensity matrix
• Updated featureData metadata reflecting single quantified target lipid
• Quantified ion image displayable in LipidQMap with Q (quantitative) view toggle

How to apply

Identify the internal standard lipid species in the sample database by matching either the sample identifier or feature name; retrieve its isotope-corrected intensity row from the HDF5 spectraData/intensity matrix. For each target lipid of interest, retrieve its corresponding intensity row. Perform element-wise division of the target lipid intensity vector 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. Export the normalized matrix to a new HDF5 file with root attribute image_type set to 'quant' and updated featureData metadata following Cardinal::HDF5 conventions. Verify that the quantified image shows spatial patterns consistent with the isotope-corrected view but with reduced pixel-to-pixel noise and improved comparability across regions.

Related tools

• LipidQMap (Primary GUI application for selecting internal standards from database, toggling between raw/isotope-corrected/quantified views, and exporting quantified images) — https://github.com/swinnenteam/LipidQMap
• Cardinal (Defines HDF5 container conventions for MSI exports; quantified output must follow Cardinal::HDF5 standard) — https://cardinalmsi.org
• h5py or h5netcdf (HDF5 reader/writer library for programmatic access to isotope-corrected intensity matrix and metadata; required for scripted quantification workflows)

Examples

In LipidQMap: (1) Import imzML file with isotope correction enabled. (2) Click on target lipid in Species table. (3) In Settings, confirm the database row 'IS' column points to a standard with 'Is standard'=TRUE and 'Standard amount (pmol/mm2)' populated. (4) Click Settings → select internal standard from dropdown. (5) Press 'Q' to toggle to Quantitative view. (6) Click 'Save images' and select 'Save Quantitative images'.

Evaluation signals

• Output HDF5 file root attribute image_type equals 'quant' (not 'isotope' or 'raw')
• Output quantified intensity matrix shape matches input (n_features × n_pixels) with float32 dtype
• Pixels with zero or negative internal standard intensity are masked as NaN or zero (no inf or invalid values)
• Quantified image view (Q toggle in LipidQMap) displays smooth spatial patterns without extreme outliers caused by low-intensity standard pixels
• featureData metadata in output HDF5 reflects single target lipid (not all original features) with quantitation method documented in file attributes

Limitations

• Internal standard must be present in the sample at detectable intensity across representative tissue regions; sparse or highly variable standard signal will produce unreliable quantitation
• Quantitation is relative to the chosen internal standard and does not yield absolute abundance without independent standard calibration
• Division-by-zero handling (masking as NaN) reduces effective pixel count in quantified image; high frequency of masked pixels indicates poor internal standard coverage
• Database column 'IS' (internal standard ID reference) must be correctly populated for each target lipid, or standard lookup will fail

Evidence

• [intro] LipidQMap performs quantitation based on user-defined internal standards: "Performs quantitation based on user defined internal standards."
• [other] Isotope-corrected intensity matrix from HDF5 spectraData/intensity: "Extract the isotope-corrected intensity matrix from spectraData/intensity (shape: n_features × n_pixels, float32)."
• [other] Feature lookup by matching feature_id against user definition: "Locate the internal standard feature in featureData by matching feature_id against the user definition and retrieve its intensity row."
• [other] Element-wise division with NaN/zero masking for zero-intensity pixels: "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] Output HDF5 follows Cardinal::HDF5 conventions with image_type='quant': "Write the quantified intensity matrix to a new HDF5 file following Cardinal::HDF5 conventions, updating root attribute image_type to 'quant'"
• [readme] Toggle view in LipidQMap between raw, isotope-corrected, and quantified images: "Can toggle view between raw, isotope corrected and quantified images."
• [readme] Database column 'IS' specifies internal standard for quantitation: "IS: ID of the standard species that should be used for the quantitation."