Tian Jun, Qian Bo, Zhang Sanmei, Guo Rui, Zhang Hui, Jeannon J-P, Jin Rongxiu, Feng Xiang, Zhan Yangni, Liu Jie, He Pengfei, Guo Jue, Li Le, Jia Yue, Huang Fuhui, Wang Binquan
Department of Otolaryngology, Head & Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Department of General Surgery, The General Hospital of Taiyuan Iron & Steel Company, Taiyuan, China.
Sci Rep. 2020 Nov 3;10(1):18962. doi: 10.1038/s41598-020-76081-7.
Three-dimensional (3D) image reconstruction of tumors based on serial histological sectioning is one of the most powerful methods for accurate high-resolution visualization of tumor structures. However, 3D histological reconstruction of whole tumor has not yet been achieved. We established a high-resolution 3D model of molecular marked whole laryngeal cancer by optimizing the currently available techniques. A series of 5,388 HE stained or immunohistochemically stained whole light microscopic images (200 ×) were acquired (15.61 TB).The data set of block-face images (96.2 GB) was also captured. Direct volume rendering of serial 6.25 × light microscopy images did not demonstrate the major characteristics of the laryngeal cancer as expected. Based on fusion of two datasets, the accurate boundary of laryngeal tumor bulk was visualized in an anatomically realistic context. In the regions of interest, micro tumor structure, budding, cell proliferation and tumor lymph vessels were well represented in 3D after segmentation, which highlighted the advantages of 3D reconstruction of light microscopy images. In conclusion, generating 3D digital histopathological images of a whole solid tumor based on current technology is feasible. However, data mining strategy should be developed for complete utilization of the large amount of data generated.
基于连续组织切片的肿瘤三维(3D)图像重建是精确高分辨率可视化肿瘤结构的最有效方法之一。然而,完整肿瘤的三维组织学重建尚未实现。我们通过优化现有技术,建立了分子标记的全喉癌高分辨率三维模型。获取了一系列5388张苏木精-伊红(HE)染色或免疫组化染色的全光学显微镜图像(200×)(15.61TB)。还采集了块面图像数据集(96.2GB)。对连续的6.25×光学显微镜图像进行直接体绘制,并未如预期那样显示出喉癌的主要特征。基于两个数据集的融合,在符合解剖学实际的背景下可视化了喉肿瘤块的精确边界。在感兴趣区域,分割后的微观肿瘤结构、芽生、细胞增殖和肿瘤淋巴管在三维中得到了很好的呈现,这突出了光学显微镜图像三维重建的优势。总之,基于当前技术生成完整实体肿瘤的三维数字组织病理学图像是可行的。然而,应开发数据挖掘策略以充分利用所生成的大量数据。