1. Probe electrospray ionization mass spectrometry-based rapid diagnosis of liver tumors.
- Author
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Hakoda H, Kiritani S, Kokudo T, Yoshimura K, Iwano T, Tanimoto M, Ishizawa T, Arita J, Akamatsu N, Kaneko J, Takeda S, and Hasegawa K
- Subjects
- Humans, Spectrometry, Mass, Electrospray Ionization methods, Machine Learning, Liver Neoplasms diagnosis, Carcinoma, Hepatocellular diagnosis
- Abstract
Background and Aim: Prompt differential diagnosis of liver tumors is clinically important and sometimes difficult. A new diagnostic device that combines probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning may help provide the differential diagnosis of liver tumors., Methods: We evaluated the diagnostic accuracy of this new PESI-MS device using tissues obtained and stored from previous surgically resected specimens. The following cancer tissues (with collection dates): hepatocellular carcinoma (HCC, 2016-2019), intrahepatic cholangiocellular carcinoma (ICC, 2014-2019), and colorectal liver metastasis (CRLM, 2014-2019) from patients who underwent hepatic resection were considered for use in this study. Non-cancerous liver tissues (NL) taken from CRLM cases were also incorporated into the analysis. Each mass spectrum provided by PESI-MS was tested using support vector machine, a type of machine learning, to evaluate the discriminatory ability of the device., Results: In this study, we used samples from 91 of 139 patients with HCC, all 24 ICC samples, and 103 of 202 CRLM samples; 80 NL from CRLM cases were also used. Each mass spectrum was obtained by PESI-MS in a few minutes and was evaluated by machine learning. The sensitivity, specificity, and diagnostic accuracy of the PESI-MS device for discriminating HCC, ICC, and CRLM from among a mix of all three tumors and from NL were 98.9%, 98.1%, and 98.3%; 87.5%, 93.1%, and 92.6%; and 99.0%, 97.9%, and 98.3%, respectively., Conclusion: This study demonstrated that PESI-MS and machine learning could discriminate liver tumors accurately and rapidly., (© 2022 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)
- Published
- 2022
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