{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Woolman M"],"funding":["Natural Sciences and Engineering Research Council of Canada"],"pagination":["8723-8735"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8163395"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["11(33)"],"pubmed_abstract":["Integration between a hand-held mass spectrometry desorption probe based on picosecond infrared laser technology (PIRL-MS) and an optical surgical tracking system demonstrates <i>in situ</i> tissue pathology from point-sampled mass spectrometry data. Spatially encoded pathology classifications are displayed at the site of laser sampling as color-coded pixels in an augmented reality video feed of the surgical field of view. This is enabled by two-way communication between surgical navigation and mass spectrometry data analysis platforms through a custom-built interface. Performance of the system was evaluated using murine models of human cancers sampled <i>in situ</i> in the presence of body fluids with a technical pixel error of 1.0 ± 0.2 mm, suggesting a 84% or 92% (excluding one outlier)"],"journal":["Chemical science"],"pubmed_title":["<i>In situ</i> tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality."],"pmcid":["PMC8163395"],"funding_grant_id":["RGPIN-2018-04611"],"pubmed_authors":["Katz L","Qiu J","Chan H","Woolman M","Wu M","Fricke I","Wouters BG","Dara D","Daud F","Ventura M","Das S","Ferry I","Weersink R","Kuzan-Fischer CM","Ginsberg HJ","Bernards N","Irish J","Zaidi M","Jaffray DA","Zarrine-Afsar A","Rutka JT"],"additional_accession":[]},"is_claimable":false,"name":"<i>In situ</i> tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality.","description":"Integration between a hand-held mass spectrometry desorption probe based on picosecond infrared laser technology (PIRL-MS) and an optical surgical tracking system demonstrates <i>in situ</i> tissue pathology from point-sampled mass spectrometry data. Spatially encoded pathology classifications are displayed at the site of laser sampling as color-coded pixels in an augmented reality video feed of the surgical field of view. This is enabled by two-way communication between surgical navigation and mass spectrometry data analysis platforms through a custom-built interface. Performance of the system was evaluated using murine models of human cancers sampled <i>in situ</i> in the presence of body fluids with a technical pixel error of 1.0 ± 0.2 mm, suggesting a 84% or 92% (excluding one outlier)","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Jul","modification":"2025-05-18T12:40:47.563Z","creation":"2025-05-18T12:40:47.563Z"},"accession":"S-EPMC8163395","cross_references":{"pubmed":["34123126"],"doi":["10.1039/d0sc02241a"]}}