{"doi":"10.1007/s00216-025-06138-x","title":"Demonstrating voxel-by-voxel (V × V) single-point calibration in liver tissue by IR-MALDESI quantitative MSI","abstract":"Quantitative mass spectrometry imaging (qMSI) provides information regarding the colocalization, relative abundance, and concentration of a target analyte in a tissue without homogenization. Ionization sources, including IR-MALDESI, commonly utilize an on-tissue spatial calibration curve approach; however, this approach has several limitations including tedious sample preparation, and this approach does not account for local matrix effects. To compensate for these two limitations, we developed voxel-by-voxel (V × V) quantification to provide an internal standard calibration point for every voxel which requires a simple sample preparation and accounts for local matrix effects. In this work, we evaluate the performance of V × V quantification against the spatial calibration curve to assess the quantitative capacity of this newly developed method. Quantification of glutathione (GSH) on a per-voxel basis involves homogenously spraying a known amount of stable isotope-labeled glutathione (SIL-GSH) on a microscope slide. Next, we mount liver sections on top of the coated slides and image them using IR-MALDESI MSI. Statistical analysis demonstrated high precision for V × V quantification over a wide concentration range; however, the method's accuracy is currently limited due to the sprayer's configuration. Results support the feasibility of V × V quantification as evidenced by concentration heatmaps. Additionally, V × V quantification allows for parallel reaction monitoring (PRM) imaging which provides high specificity. Combined with relativity, straightforward sample preparation, and promising initial statistics, the V × V method offers significant advantages over spatial calibration curves.","journal":"Analytical and Bioanalytical Chemistry","year":2025,"id":536772,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9478,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":928956,"name":"Russell R. Kibbe","orcid":"0000-0002-6606-5689","position":1,"is_corresponding":false},{"id":1422609,"name":"Logan J. Opperman","orcid":null,"position":2,"is_corresponding":false},{"id":448808,"name":"David C. Muddiman","orcid":"0000-0003-2216-499X","position":3,"is_corresponding":false},{"id":1422608,"name":"Emily R. Bruce","orcid":null,"position":0,"is_corresponding":true}],"reference_count":25,"raw_metadata":null,"created_at":"2026-07-19T02:52:09.056872Z","pmid":"41021018","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}