Literature DB >> 29530251

MassImager: A software for interactive and in-depth analysis of mass spectrometry imaging data.

Jiuming He1, Luojiao Huang1, Runtao Tian2, Tiegang Li1, Chenglong Sun1, Xiaowei Song1, Yiwei Lv1, Zhigang Luo1, Xin Li1, Zeper Abliz3.   

Abstract

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.
Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Artificial intelligent pathological diagnosis; Data processing software; In-situ biomarker discovery; Interactive visualization; Mass spectrometry imaging

Mesh:

Year:  2018        PMID: 29530251     DOI: 10.1016/j.aca.2018.02.030

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  4 in total

1.  Spatially resolved metabolomics to discover tumor-associated metabolic alterations.

Authors:  Chenglong Sun; Tiegang Li; Xiaowei Song; Luojiao Huang; Qingce Zang; Jing Xu; Nan Bi; Guanggen Jiao; Yanzeng Hao; Yanhua Chen; Ruiping Zhang; Zhigang Luo; Xin Li; Luhua Wang; Zhonghua Wang; Yongmei Song; Jiuming He; Zeper Abliz
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-17       Impact factor: 11.205

2.  Molecular Pathological Diagnosis of Thyroid Tumors Using Spatially Resolved Metabolomics.

Authors:  Luojiao Huang; Xinxin Mao; Chenglong Sun; Tiegang Li; Xiaowei Song; Jiangshuo Li; Shanshan Gao; Ruiping Zhang; Jie Chen; Jiuming He; Zeper Abliz
Journal:  Molecules       Date:  2022-02-18       Impact factor: 4.411

Review 3.  The application of mass spectrometry imaging in traditional Chinese medicine: a review.

Authors:  Lieyan Huang; Lixing Nie; Zhong Dai; Jing Dong; Xiaofei Jia; Xuexin Yang; Lingwen Yao; Shuang-Cheng Ma
Journal:  Chin Med       Date:  2022-03-05       Impact factor: 5.455

4.  A temporo-spatial pharmacometabolomics method to characterize pharmacokinetics and pharmacodynamics in the brain microregions by using ambient mass spectrometry imaging.

Authors:  Dan Liu; Jianpeng Huang; Shanshan Gao; Hongtao Jin; Jiuming He
Journal:  Acta Pharm Sin B       Date:  2022-03-31       Impact factor: 14.903

  4 in total

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