马尔迪成像
质谱成像
显微镜
自体荧光
化学
图像配准
人工智能
质谱法
模式识别(心理学)
基质辅助激光解吸/电离
计算机科学
病理
光学
图像(数学)
色谱法
吸附
物理
解吸
荧光
有机化学
医学
作者
Nathan Heath Patterson,Michael Tuck,Raf Van de Plas,Richard M. Caprioli
出处
期刊:Analytical Chemistry
[American Chemical Society]
日期:2018-10-01
卷期号:90 (21): 12395-12403
被引量:110
标识
DOI:10.1021/acs.analchem.8b02884
摘要
The correlation of imaging mass spectrometry (IMS) with histopathology can help relate novel molecular findings obtained through IMS to the well-characterized and validated histopathology knowledge base. The quality of correlation between these two modalities is limited by the quality of the spatial mapping that is obtained by registration of the two image types. In this work, we develop novel workflows for MALDI IMS-to-microscopy data registration and analysis using nondestructive IMS-compatible wide field autofluorescence (AF) microscopy combined with computational image registration. First, a substantially automated procedure for high-accuracy registration between IMS and microscopy data of the same section is described that explicitly links the MALDI laser ablation pattern imaged by microscopy to its corresponding IMS pixel. Subsequent examination of the registered data allows for high-confidence colocalization of image features between the two modalities, down to single-cell scales within tissue. Building on this IMS-microscopy spatial mapping, we furthermore demonstrate the automated spatial correlation between IMS measurements from serial sections. This AF-registration-driven inter-section analysis, using a combination of nonlinear AF-to-AF and IMS-to-AF image registrations, can be applied to tissue sections that are prepared and imaged with different sample preparations (e.g., lipids vs proteins) and/or that are measured using different spatial resolutions. Importantly, all registrations, whether within a single section or across serial sections, are entirely independent of the IMS intensity signal content and thus unbiased by it.
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