Deep learning approach for accurate prostate cancer identification and stratification using combined immunostaining of cytokeratin, p63, and racemase.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Published Date:

Abstract

BACKGROUND: Prostate cancer (PCa) is the most frequently diagnosed cancer in men worldwide, affecting around 1.4 million individuals. Current PCa diagnosis relies on histological analysis of prostate biopsy samples, an activity that is both time-consuming and prone to observer bias. Previous studies have demonstrated that immunostaining of cytokeratin, p63, and racemase can significantly improve the sensitivity and the specificity of PCa detection compared to traditional H&E staining.

Authors

  • Massimo Salvi
  • Claudia Manini
    Department of Pathology, San Giovanni Bosco Hospital, 10154 Turin, Italy; Department of Sciences of Public Health and Pediatrics, University of Turin, 10124 Turin, Italy.
  • Jose I López
    Biomarkers in Cancer Group, Biocruces-Bizkaia Health Research Institute, 48903 Barakaldo, Spain.
  • Dario Fenoglio
    Biolab, PoliToBIOMed Lab, Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.
  • Filippo Molinari
    Department of Electronics and Telecommunications, Politecnico di Torino, Italy.