A comparative study of the inter-observer variability on Gleason grading against Deep Learning-based approaches for prostate cancer.
Journal:
Computers in biology and medicine
Published Date:
Apr 6, 2023
Abstract
BACKGROUND: Among all the cancers known today, prostate cancer is one of the most commonly diagnosed in men. With modern advances in medicine, its mortality has been considerably reduced. However, it is still a leading type of cancer in terms of deaths. The diagnosis of prostate cancer is mainly conducted by biopsy test. From this test, Whole Slide Images are obtained, from which pathologists diagnose the cancer according to the Gleason scale. Within this scale from 1 to 5, grade 3 and above is considered malignant tissue. Several studies have shown an inter-observer discrepancy between pathologists in assigning the value of the Gleason scale. Due to the recent advances in artificial intelligence, its application to the computational pathology field with the aim of supporting and providing a second opinion to the professional is of great interest.