UNASSIGNED: Micro-CT scans were conducted on 12 FFPEs obtained from 8 NSCLC patients with histologically confirmed mediastinal LN metastases. Simultaneously, whole-slide images from these FFPEs underwent scanning, and 47 regions of interest (ROIs) (17 metastatic foci, 11 normal lymphoid tissues, 10 adipose tissues, and 9 anthracofibrosis) were marked on scanned images. Quantitative structural variables obtained via micro-CT analysis from tumoral and non-tumoral ROIs, were analyzed.
UNASSIGNED: Significant distinctions were observed in linear density, connectivity, connectivity density, and closed porosity between tumoral and non-tumoral ROIs, as indicated by kappa coefficients of 1, 0.90, 1, and 1, respectively. Receiver operating characteristic analysis substantiated the differentiation between tumoral and non-tumoral ROIs based on thickness, linear density, connectivity, connectivity density, and the percentage of closed porosity.
UNASSIGNED: Quantitative micro-CT parameters demonstrate the ability to distinguish between tumoral and non-tumoral regions of LNs in FFPEs. The discriminatory characteristics of these quantitative micro-CT parameters imply their potential usefulness in developing an artificial intelligence algorithm specifically designed for the 3D identification of LN metastases while preserving the FFPE tissue.
■对从8例经组织学证实的纵隔LN转移的NSCLC患者获得的12例FFPE进行了Micro-CT扫描。同时,来自这些FFPE的整个幻灯片图像进行了扫描,和47个感兴趣区域(ROI)(17个转移灶,11个正常淋巴组织,10脂肪组织,和9个炭疽纤维化)在扫描图像上标记。通过显微CT分析从肿瘤和非肿瘤ROI获得的定量结构变量,进行了分析。
■在线性密度中观察到显着差异,连通性,连接密度,肿瘤和非肿瘤ROI之间的闭孔,如Kappa系数分别为1、0.90、1和1所示。接收器工作特征分析证实了基于厚度的肿瘤和非肿瘤ROI之间的区别,线密度,连通性,连接密度,和闭孔百分比。
■定量微CT参数表明能够区分FFPE中LN的肿瘤区域和非肿瘤区域。这些定量微CT参数的辨别特征暗示了它们在开发专门设计用于LN转移的3D识别同时保留FFPE组织的人工智能算法中的潜在有用性。