Pathomics in urology

Curr Opin Urol. 2020 Nov;30(6):823-831. doi: 10.1097/MOU.0000000000000813.


Purpose of review: Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summarize its most relevant applications in urology.

Recent findings: There is a steady rise in the number of studies employing Pathomics, and especially deep learning, in urology. In prostate cancer, several algorithms have been developed for the automatic differentiation between benign and malignant lesions and to differentiate Gleason scores. Furthermore, several applications have been developed for the automatic cancer cell detection in urine and for tumor assessment in renal cancer. Despite the explosion in research, Pathomics is not fully ready yet for widespread clinical application.

Summary: In prostate cancer and other urologic pathologies, Pathomics is avidly being researched with commercial applications on the close horizon. Pathomics is set to improve the accuracy, speed, reliability, cost-effectiveness and generalizability of pathology, especially in uro-oncology.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Artificial Intelligence*
  • Carcinoma, Renal Cell / pathology
  • Deep Learning
  • Diagnosis, Computer-Assisted
  • Female
  • Humans
  • Kidney Neoplasms / pathology
  • Male
  • Neoplasm Grading
  • Pathology*
  • Prostatic Neoplasms / pathology
  • Reproducibility of Results
  • Testicular Neoplasms / pathology
  • Urogenital Neoplasms / pathology*
  • Urologic Neoplasms / pathology
  • Urology*