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头颈部癌症的三维多模态成像数据整合和高级特征识别。

Integration of 3D multimodal imaging data of a head and neck cancer and advanced feature recognition.

机构信息

Fraunhofer Institute for Image Computing MEVIS, Lübeck, Germany.

Institute of Physical Chemistry, Friedrich Schiller University, Jena, Germany; ENT Department, University Hospital Jena, Germany.

出版信息

Biochim Biophys Acta Proteins Proteom. 2017 Jul;1865(7):946-956. doi: 10.1016/j.bbapap.2016.08.018. Epub 2016 Sep 1.

Abstract

In the last years, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) became an imaging technique which has the potential to characterize complex tumor tissue. The combination with other modalities and with standard histology techniques was achieved by the use of image registration methods and enhances analysis possibilities. We analyzed an oral squamous cell carcinoma with up to 162 consecutive sections with MALDI MSI, hematoxylin and eosin (H&E) staining and immunohistochemistry (IHC) against CD31. Spatial segmentation maps of the MALDI MSI data were generated by similarity-based clustering of spectra. Next, the maps were overlaid with the H&E microscopy images and the results were interpreted by an experienced pathologist. Image registration was used to fuse both modalities and to build a three-dimensional (3D) model. To visualize structures below resolution of MALDI MSI, IHC was carried out for CD31 and results were embedded additionally. The integration of 3D MALDI MSI data with H&E and IHC images allows a correlation between histological and molecular information leading to a better understanding of the functional heterogeneity of tumors. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

摘要

在过去的几年中,基质辅助激光解吸/电离质谱成像(MALDI MSI)已成为一种具有描绘复杂肿瘤组织潜力的成像技术。通过使用图像配准方法并增强分析可能性,与其他模态和标准组织学技术相结合。我们用 MALDI MSI、苏木精和伊红(H&E)染色和针对 CD31 的免疫组织化学(IHC)对多达 162 个连续切片的口腔鳞状细胞癌进行了分析。通过对光谱进行基于相似性的聚类生成 MALDI MSI 数据的空间分割图。接下来,将地图与 H&E 显微镜图像叠加,并由经验丰富的病理学家对结果进行解释。图像配准用于融合两种模态并构建三维(3D)模型。为了可视化 MALDI MSI 分辨率以下的结构,还进行了针对 CD31 的 IHC,并将结果嵌入其中。将 3D MALDI MSI 数据与 H&E 和 IHC 图像集成可以在组织学和分子信息之间建立相关性,从而更好地理解肿瘤的功能异质性。本文是由 Corinna Henkel 博士和 Peter Hoffmann 教授编辑的题为“MALDI 成像”的特刊的一部分。

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