Urine cytology: Updates and challenges in reporting systems, ancillary studies, and artificial intelligence

• Published in: Human Pathology Reports
• Main Authors: Juan Xing, Jordan P. Reynolds, Xiaoying Liu, Liron Pantanowitz
• Format: Article
• Language: English
• Published: Elsevier 2024-03-01
• Subjects: Ancillary studies; Artificial intelligence; Cytochemistry; Digital cytology; Fluorescence in situ hybridization; Immunocytochemistry
• Online Access: http://www.sciencedirect.com/science/article/pii/S2772736X24000057
• ISSN: 2772-736X

Several urine cytology classifications have been published in the literature. However, global acceptance in the field of urine cytology was only gained in 2016 after The Paris System for reporting urinary cytology was published. Despite this Paris System and its shifted focus toward the detection of high-grade urothelial carcinoma, the perceived weakness of low sensitivity and indeterminate diagnoses when screening with urine cytology remains unresolved. To overcome these shortcomings, investigators have studied a variety of emerging ancillary tests to augment urine cytology (UroVysion, ImmunoCyt/uCyte+, BTA-stat/TRAK, NMP22, SCD-A7, URO17, CellDetect, UroMark, UroSEEK). Furthermore, with the advent of digital cytology, the creation of artificial intelligence tools has created innovative opportunities to aid with urine cytology. This review article discusses the lessons learned in the evolution of reporting systems, explores the merit and challenges of ancillary tests, and calls attention to potential utility of applying artificial intelligence in urine cytology.