UR BIA, INRAE, 44316, Nantes, France.
BIBS Facility, INRAE, 44316, Nantes, France.
BMC Bioinformatics. 2021 Feb 8;22(1):56. doi: 10.1186/s12859-020-03954-z.
Mass spectrometry imaging (MSI) is a family of acquisition techniques producing images of the distribution of molecules in a sample, without any prior tagging of the molecules. This makes it a very interesting technique for exploratory research. However, the images are difficult to analyze because the enclosed data has high dimensionality, and their content does not necessarily reflect the shape of the object of interest. Conversely, magnetic resonance imaging (MRI) scans reflect the anatomy of the tissue. MRI also provides complementary information to MSI, such as the content and distribution of water.
We propose a new workflow to merge the information from 2D MALDI-MSI and MRI images. Our workflow can be applied to large MSI datasets in a limited amount of time. Moreover, the workflow is fully automated and based on deterministic methods which ensures the reproducibility of the results. Our methods were evaluated and compared with state-of-the-art methods. Results show that the images are combined precisely and in a time-efficient manner.
Our workflow reveals molecules which co-localize with water in biological images. It can be applied on any MSI and MRI datasets which satisfy a few conditions: same regions of the shape enclosed in the images and similar intensity distributions.
质谱成像（MSI）是一组采集技术，可生成样本中分子分布的图像，而无需对分子进行任何预先标记。这使其成为探索性研究非常有趣的技术。然而，由于封闭数据具有高维性，并且其内容不一定反映感兴趣对象的形状，因此图像难以分析。相反，磁共振成像（MRI）扫描反映了组织的解剖结构。MRI 还提供了与 MSI 互补的信息，例如水的含量和分布。
我们提出了一种新的工作流程，用于合并 2D MALDI-MSI 和 MRI 图像的信息。我们的工作流程可以在有限的时间内应用于大型 MSI 数据集。此外，该工作流程是完全自动化的，并且基于确定性方法，可确保结果的可重复性。我们的方法进行了评估，并与最先进的方法进行了比较。结果表明，图像以精确且高效的方式进行了组合。
我们的工作流程揭示了与生物图像中水共定位的分子。它可以应用于任何满足以下几个条件的 MSI 和 MRI 数据集：图像中封闭的形状的相同区域和相似的强度分布。
