Deciphering tumour tissue organization by 3D electron microscopy and machine learning.
Deciphering tumour tissue organization by 3D electron microscopy and machine learning.
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DOI：
10.1038/s42003-021-02919-z
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发表时间：
2021-12-13
影响因子：
5.9
通讯作者：
Grosset CF
中科院分区：
文献类型：
--
作者：
de Senneville BD;Khoubai FZ;Bevilacqua M;Labedade A;Flosseau K;Chardot C;Branchereau S;Ripoche J;Cairo S;Gontier E;Grosset CF
尽管最近在肿瘤成分的表征方面取得了进展，但这种病理组织的三维(3D)组织和决定其内部结构的参数仍然难以捉摸。在这里，我们分析了来自肝母细胞瘤的患者来源的异种组织的空间组织，这是最常见的儿童肝脏肿瘤，使用结合了3D成像、手动和基于机器学习的半自动分割、数学和信息图的集成工作流程的连续块面扫描电子显微镜。通过数字化重建完整的肝母细胞瘤标本，包括毛细血管、胆小管样结构、数百个肿瘤细胞及其主要细胞器(如细胞质、细胞核、线粒体)，我们报告了关于肿瘤组织组织的独特的三维超微结构数据。我们发现肝母细胞瘤细胞的大小与其核、细胞质和线粒体质量的大小有关。我们还发现在3D环境中，毛细血管与肿瘤细胞的平面排列和大小之间存在解剖学上的联系。最后，一组肿瘤细胞沿着与胆小管样结构相对应的热点方向极化。总而言之，这项先导性研究允许确定塑造肿瘤内部和空间组织的生物结构参数，从而为未来在新兴的肿瘤切开术领域的研究铺平了道路。De Senneville等人。演示结合3D成像、手动和基于机器学习的半自动分割、数学和信息图的集成工作流程，以研究患者来源的肝母细胞瘤异种移植组织的空间组织。他们的方法可能有助于对这种儿童肝脏肿瘤和其他类型的肿瘤组织的研究。
Despite recent progress in the characterization of tumour components, the tri-dimensional (3D) organization of this pathological tissue and the parameters determining its internal architecture remain elusive. Here, we analysed the spatial organization of patient-derived xenograft tissues generated from hepatoblastoma, the most frequent childhood liver tumour, by serial block-face scanning electron microscopy using an integrated workflow combining 3D imaging, manual and machine learning-based semi-automatic segmentations, mathematics and infographics. By digitally reconstituting an entire hepatoblastoma sample with a blood capillary, a bile canaliculus-like structure, hundreds of tumour cells and their main organelles (e.g. cytoplasm, nucleus, mitochondria), we report unique 3D ultrastructural data about the organization of tumour tissue. We found that the size of hepatoblastoma cells correlates with the size of their nucleus, cytoplasm and mitochondrial mass. We also found anatomical connections between the blood capillary and the planar alignment and size of tumour cells in their 3D milieu. Finally, a set of tumour cells polarized in the direction of a hot spot corresponding to a bile canaliculus-like structure. In conclusion, this pilot study allowed the identification of bioarchitectural parameters that shape the internal and spatial organization of tumours, thus paving the way for future investigations in the emerging onconanotomy field. de Senneville et al. demonstrate an integrated workflow combining 3D imaging, manual and machine learning-based semi-automatic segmentation, mathematics and infographics to study the spatial organization of patient-derived hepatoblastoma xenograft tissues. Their approach potentially assists investigations of this childhood liver tumour and other types of tumour tissues.
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影响因子：
--
作者：
Cartier F;Indersie E;Lesjean S;Charpentier J;Hooks KB;Ghousein A;Desplat A;Dugot-Senant N;Trézéguet V;Sagliocco F;Hagedorn M;Grosset CF
通讯作者：
Grosset CF
影响因子：
5.7
作者：
Huo, Yuankai;Xu, Zhoubing;Landman, Bennett A.
通讯作者：
Landman, Bennett A.
影响因子：
3.5
作者：
Berger DR;Seung HS;Lichtman JW
通讯作者：
Lichtman JW
影响因子：
2.3
作者：
Chan, Yee-Hung M.;Marshall, Wallace F.
通讯作者：
Marshall, Wallace F.
使用完全卷积网络改善大脑结构分割不平衡的权重。
DOI：
10.3390/healthcare9080938
发表时间：
2021-07-26
期刊：
Healthcare (Basel, Switzerland)
影响因子：
--
作者：
Sugino T;Kawase T;Onogi S;Kin T;Saito N;Nakajima Y
通讯作者：
Nakajima Y