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Intraoperative Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry

质谱法 体内 色谱法 化学 线性判别分析 离体 病理 生物医学工程 医学 计算机科学 生物 人工智能 生物技术
作者
Júlia Balog,László Sasi-Szabó,James Kinross,Matthew R. Lewis,Laura J. Muirhead,Kirill Veselkov,Reza Mirnezami,Balázs Dezsö,László Damjanovich,Ara Darzi,Jeremy K. Nicholson,Zoltán Takáts
出处
期刊:Science Translational Medicine [American Association for the Advancement of Science]
卷期号:5 (194): 194ra93-194ra93 被引量:595
标识
DOI:10.1126/scitranslmed.3005623
摘要

Rapid evaporative ionization mass spectrometry (REIMS) is an emerging technique that allows near-real-time characterization of human tissue in vivo by analysis of the aerosol ("smoke") released during electrosurgical dissection. The coupling of REIMS technology with electrosurgery for tissue diagnostics is known as the intelligent knife (iKnife). This study aimed to validate the technique by applying it to the analysis of fresh human tissue samples ex vivo and to demonstrate the translation to real-time use in vivo in a surgical environment. A variety of tissue samples from 302 patients were analyzed in the laboratory, resulting in 1624 cancerous and 1309 noncancerous database entries. The technology was then transferred to the operating theater, where the device was coupled to existing electrosurgical equipment to collect data during a total of 81 resections. Mass spectrometric data were analyzed using multivariate statistical methods, including principal components analysis (PCA) and linear discriminant analysis (LDA), and a spectral identification algorithm using a similar approach was implemented. The REIMS approach differentiated accurately between distinct histological and histopathological tissue types, with malignant tissues yielding chemical characteristics specific to their histopathological subtypes. Tissue identification via intraoperative REIMS matched the postoperative histological diagnosis in 100% (all 81) of the cases studied. The mass spectra reflected lipidomic profiles that varied between distinct histological tumor types and also between primary and metastatic tumors. Thus, in addition to real-time diagnostic information, the spectra provided additional information on divergent tumor biochemistry that may have mechanistic importance in cancer.
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