Qualitative Detection of Serum Paraproteins Using Mass Chromatogram: Ease of Interpretation Validated by Multiple Analysts
Year: 2025
Type: article
Abstract: Aim and background: Liquid chromatography (LC) mass spectrometry (MS) methods are often developed and validated by scientists, while pathologists/biochemists report the test results of the patient samples.An understanding of the technique is crucial for confident reporting by pathologists/biochemists.The present study aims to evaluate the ease of interpretation of data from total ion chromatogram (TIC) to detect serum paraproteins in a clinical setting.Methodology: The dataset (n = 37) used for the study included monoclonal (n = 15), biclonal (n = 3), free light chain (κ, λ) (n = 7), and negative samples (n = 12) as identified by LC triple quadrupole (TQ) MS and immunofixation electrophoresis test results.Multiple analysts (n = 18) from different backgrounds, namely pathologists, microbiologists, biochemists, cytogeneticists, data scientists, and a professor, were given basic training to identify serum paraproteins from a total ion mass chromatogram.Following initial training, the same dataset was reordered and repurposed as a validation dataset.Results: Of the various isotypes of immunoglobulins, 72% of analysts accurately identified monoclonal proteins, while 81% correctly identified free light chains.Additionally, 87% of analysts successfully identified biclonal proteins, either fully or partially, with partial identification indicating the detection of any one clone.Around 89% of analysts correctly identified the negative samples.Conclusion: Serum proteins can be identified using TIC.Multiple analysts with different technical backgrounds have validated the ease of interpreting the data through TIC.Clinical significance: A strong understanding of the MS technology and the interpretation of TIC by clinical professionals could significantly improve the diagnostic utility of MS for detecting serum paraproteins in a clinical setting.
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4410566283