Gavriil Vassilios, Ferraro Angelo, Cefalas Alkiviadis-Constantinos, Kollia Zoe, Pepe Francesco, Malapelle Umberto, De Luca Caterina, Troncone Giancarlo, Sarantopoulou Evangelia
National Hellenic Research Foundation, Theoretical and Physical Chemistry Institute, 48 Vassileos Constantinou Avenue, 11635 Athens, Greece.
Dipartimento di Sanità Pubblica, Università Degli Studi di Napoli "Federico II", via Pansini 5, 801301 Napoli, Italy.
Cancers (Basel). 2023 Feb 14;15(4):1220. doi: 10.3390/cancers15041220.
Early ascertainment of metastatic tumour phases is crucial to improve cancer survival, formulate an accurate prognostic report of disease advancement, and, most importantly, quantify the metastatic progression and malignancy state of primary cancer cells with a universal numerical indexing system. This work proposes an early improvement to metastatic cancer detection with 97.7 nm spatial resolution by indexing the metastatic cancer phases from the analysis of atomic force microscopy images of human colorectal cancer histological sections. The procedure applies variograms of residuals of Gaussian filtering and theta statistics of colorectal cancer tissue image settings. This methodology elucidates the early metastatic progression at the nanoscale level by setting metastatic indexes and critical thresholds based on relatively large histological sections and categorising the malignancy state of a few suspicious cells not identified with optical image analysis. In addition, we sought to detect early tiny morphological differentiations indicating potential cell transition from epithelial cell phenotypes of low metastatic potential to those of high metastatic potential. This metastatic differentiation, which is also identified in higher moments of variograms, sets different hierarchical levels for metastatic progression dynamics.
早期确定转移性肿瘤阶段对于提高癌症生存率、制定准确的疾病进展预后报告至关重要，最重要的是，要用通用的数字索引系统量化原发性癌细胞的转移进展和恶性状态。这项工作通过对人大肠癌组织切片的原子力显微镜图像进行分析，对转移性癌症阶段进行索引，提出了一种早期改进的转移性癌症检测方法，其空间分辨率为97.7纳米。该程序应用高斯滤波残差的变差函数和结直肠癌组织图像设置的θ统计量。这种方法通过基于相对较大的组织切片设置转移指数和临界阈值，并对光学图像分析未识别的一些可疑细胞的恶性状态进行分类，在纳米尺度上阐明了早期转移进展。此外，我们试图检测早期微小的形态学差异，这些差异表明潜在的细胞从低转移潜能的上皮细胞表型向高转移潜能的上皮细胞表型转变。这种转移分化在变差函数的高阶矩中也能识别，为转移进展动力学设定了不同的层次水平。
