期刊
ANALYTICA CHIMICA ACTA
卷 1015, 期 -, 页码 50-57出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2018.02.030
关键词
Mass spectrometry imaging; Data processing software; Interactive visualization; In-situ biomarker discovery; Artificial intelligent pathological diagnosis
资金
- National Natural Science Foundation of China [81373370, 81773678]
- Fundamental Research Funds for the Central Universities [3332015177]
- PUMC Youth Fund
- National Instrumentation Program [2016YFF0100304]
- CAMS Innovation Fund for Medical Sciences of Peking Union Medical College [2016-I2M-1-009]
Mass spectrometry imaging (MSI) has become a powerful tool to probe molecule events in biological tissue. However, it is a widely held viewpoint that one of the biggest challenges is an easy-to-use data processing software for discovering the underlying biological information from complicated and huge MSI dataset. Here, a user-friendly and full-featured MSI software including three subsystems, Solution, Visualization and Intelligence, named MassImager, is developed focusing on interactive visualization, in-situ biomarker discovery and artificial intelligent pathological diagnosis. Simplified data preprocessing and high-throughput MSI data exchange, serialization jointly guarantee the quick reconstruction of ion image and rapid analysis of dozens of gigabytes datasets. It also offers diverse self-defined operations for visual processing, including multiple ion visualization, multiple channel superposition, image normalization, visual resolution enhancement and image filter. Regions-of-interest analysis can be performed precisely through the interactive visualization between the ion images and mass spectra, also the overlaid optical image guide, to directly find out the region-specific biomarkers. Moreover, automatic pattern recognition can be achieved immediately upon the supervised or unsupervised multivariate statistical modeling. Clear discrimination between cancer tissue and adjacent tissue within a MSI dataset can be seen in the generated pattern image, which shows great potential in visually in-situ biomarker discovery and artificial intelligent pathological diagnosis of cancer. All the features are integrated together in MassImager to provide a deep MSI processing solution at the in-situ metabolomics level for biomarker discovery and future clinical pathological diagnosis. (C) 2018 The Authors. Published by Elsevier B.V.
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