The use of artificial intelligence in bladder cancer: a histopathologic perspective

Abstract

Artificial Intelligence has shown promising results in the context of cancer diagnostics, especially due to the advancements in Digital and Computational Pathology. With regards to Bladder Cancer, AI Systems have shown to be capable of solving complex problems such as cancer detection, tumor grading, detection of lymph node metastasis or even the prediction of lymph node or mutation status (e.g. FGFR3) based solely on Hematoxylin & Eosin morphology. Furthermore, AI systems can aid pathologists by autonomously generating synoptic reports from Whole Slide Images. Against this backdrop, this review aims to provide a high level, yet comprehensive overview on the latest advancements of AI in bladder cancer, from a histopathological perspective, while discussing the current challenges in this field. In line with this scope, while highly interesting, applications of AI in the context of cystoscopy, cytology, immunohistochemistry, radiology and bioinformatics will not be discussed.