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Digital histology by phase imaging specific biomarkers for human tumoral tissues discrimination

Abstract: Histology is the diagnosis gold standard. Conventional biopsy presents artifacts, delays, or human bias. Digital histology includes automation and improved diagnosis. It digitalizes microscopic images of histological samples and analyzes similar parameters. The present approach proposes the novel use of phase contrast in clinical digital histology to improve diagnosis. The use of label-free fresh tissue slices prevents processing artifacts and reduces processing time. Phase contrast parameters are implemented and calculated: the external scale, the fractal dimension, the anisotropy factor, the scattering coefficient, and the refractive index variance. Images of healthy and tumoral samples of liver, colon, and kidney are employed. A total of 252 images with 10×, 20×, and 40× magnifications are measured. Discrimination significance between healthy and tumoral tissues is assessed statistically with ANOVA (p-value < 0.005). The analysis is made for each tissue type and for different magnifications. It shows a dependence on tissue type and image magnification. The p-value of the most significant parameters is below 10-5. Liver and colon tissues present a great overlap in significant phase contrast parameters. The 10× fractal dimension is significant for all tissue types under analysis. These results are promising for the use of phase contrast in digital histology clinical praxis.

 Autoría: Ganoza-Quintana J.L., Fanjul-Vélez F., Arce-Diego J.L.,

 Fuente: Applied Sciences, 2021, 11(13), 6142

 Editorial: MDPI

 Fecha de publicación: 01/07/2021

 Nº de páginas: 14

 Tipo de publicación: Artículo de Revista

 DOI: 10.3390/app11136142

 ISSN: 2076-3417

 Proyecto español: PGC2018-101464-B-I00