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Intraoperative Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry

A mass spectrometric approach was developed for intraoperative identification of cancerous tissue, in near–real-time. Diagnosing the Masses One of the best options for curing cancer is surgery. Yet, surgeons can leave cancerous tissue behind by not seeing the “tumor margins”—or edges of the tumor—clearly. If a surgeon isn’t sure whether tissue is normal or cancerous, the tissue is sent to a pathologist for testing. During this time (20 to 30 min), the patient remains under anesthesia, and, quite often, additional samples are required. To ensure that all malignant tissue is removed in the operating room, Balog and colleagues developed a mass spectrometry–based approach that identifies cancer during surgery. After analyzing ex vivo samples of cancerous, healthy, and benign/inflammatory tissue with rapid evaporative ionization mass spectrometry (REIMS), the authors created a database of the nearly 3000 tissue-specific mass spectra. These spectra were unique for each cancer type, with lipids such as phosphatidylcholine and phosphotidylinositol showing different ratios. Using these ratios, Balog et al. were even able to identify the origin of metastatic tumors ex vivo. To adapt this technology for use in vivo, during surgery, the authors created the “intelligent knife” (iKnife), which samples surgical smoke for mass spectrometric analysis. More than 800 spectra were acquired with the iKnife from 81 patients. These spectra, when matched against the previously created database, confirmed the results of normal histology, with low rates of false-positive and false-negative readouts. This first-in-human demonstration shows that the iKnife technology is ready for widespread use in the operating room to improve the accuracy of surgical intervention in cancer. 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.