Past-in-the-Future. Peak detection improves targeted mass spectrometry imaging

被引:8
作者
Falcetta, Francesca [1 ]
Morosi, Lavinia [1 ]
Ubezio, Paolo [1 ]
Giordano, Silvia [2 ]
Decio, Alessandra [1 ]
Giavazzi, Raffaella [1 ]
Frapolli, Roberta [1 ]
Prasad, Mridula [3 ,4 ,5 ]
Franceschi, Pietro [4 ]
D'Incalci, Maurizio [1 ]
Davoli, Enrico [2 ]
机构
[1] IRCCS Ist Ric Farmacol Mario Negri, Dept Oncol, Via La Masa 19, I-20156 Milan, Italy
[2] IRCCS Ist Ric Farmacol Mario Negri, Dept Environm Hlth Sci, Mass Spectrometry Lab, Via La Masa 19, I-20156 Milan, Italy
[3] Radboud Univ Nijmegen, IMM Analyt Chem, Heyendaalseweg, NL-6525 AJ Nijmegen, Netherlands
[4] Fdn Edmund Mach, Biostat & Data Management Grp, I-38010 San Michele All Adige, Italy
[5] Univ Torino, Dept Mol Biotechnol & Hlth Sci, Nanotechnol Med Chem, I-10126 Turin, Italy
关键词
Mass spectrometry images; Preprocessing; Tumour drug distribution; Imaging data analysis; Quantitative imaging; DRUG DISTRIBUTION; BREAST-CANCER; SOFTWARE; GROWTH; MODEL; VISUALIZATION; HETEROGENEITY; QUANTITATION; INHIBITION; PACLITAXEL;
D O I
10.1016/j.aca.2018.06.067
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Mass spectrometry imaging is a valuable tool for visualizing the localization of drugs in tissues, a critical issue especially in cancer pharmacology where treatment failure may depend on poor drug distribution within the tumours. Proper preprocessing procedures are mandatory to obtain quantitative data of drug distribution in tumours, even at low intensity, through reliable ion peak identification and integration. We propose a simple preprocessing and quantification pipeline. This pipeline was designed starting from classical peak integration methods, developed when "microcomputers" became available for chromatography, now applied to MSI. This pre-processing approach is based on a novel method using the fixed mass difference between the analyte and its 5 d derivatives to set up a mass range gate. We demonstrate the use of this pipeline for the evaluating the distribution of the anticancer drug paclitaxel in tumour sections. The procedure takes advantage of a simple peak analysis and allows to quantify the drug concentration in each pixel with a limit of detection below 0.1 pmol mm(-2) or 10 mu g g(-1). Quantitative images of paclitaxel distribution in different tumour models were obtained and average paclitaxel concentrations were compared with HPLC measures in the same specimens, showing <20% difference. The scripts are developed in Python and available through GitHub, at github.com/FrancescaFalcetta/Imaging_of_drugs_distribution_and_quantifications.git. (C 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 10
页数:10
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