Distinguishing of histopathological staging features of H-E stained human cSCC by Microscopical multispectral Imaging

Abstract

Abstract Background: Cutaneous squamous cell carcinoma (cSCC) is the second most common malignant skin tumor. Early and precise diagnosis of tumor staging are crucial for long-term outcomes. While pathological diagnosis has traditionally served as the gold standard, the assessment of differentiation levels heavily depends on subjective judgments. How do we improve the diagnosis accuracy and objectivity of pathologists༟Method: We used Multispectral imaging (MSI) to enhance tumor classification. The hematoxylin and eosin (H&E) stained cSCC slides were from Shanghai Ruijin Hospital. Scale-Invariant Feature Transform is applied to multispectral images for image stitching, while adaptive threshold segmentation method and random forest segmentation method are used for image segmentation, respectively.Results: Synthetic pseudo-color images effectively highlight tissue differences. Quantitative analysis confirms significant variation in nuclear area between normal and cSCC tissues (P < 0.001), supported by an AUC of 1 in ROC analysis. The AUC within cSCC tissues is 0.57. Further study shows higher nuclear atypia in poorly differentiated cSCC tissues compared to well differentiated cSCC (P < 0.001), also with an AUC of 1. Lastly, well differentiated cSCC tissues show more and larger keratin pearls.Conclusion: These results have shown that combined MSI with imaging processing techniques will improve H&E stained human cSCC diagnosis accuracy, and it will be well utilized to distinguish histopathological staging features.