Artificial Intelligence-Assisted Urine Cytology for Noninvasive Detection of Muscle-Invasive Urothelial Carcinoma: A Multi-Center Diagnostic Study with Prospective Validation.

ABSTRACT: Accurate preoperative diagnosis of muscle invasion (MI) is critical for urothelial carcinoma (UC) management. The aim is to evaluate whether artificial intelligence (AI) model based on urine cytology can accurately detect MIUC and compare its performance with radiologist assessments. UC patients underwent liquid-based urine cytology from four centers are included for model development/validation. Performance of the precision urine cytology AI solution for MI (PUCAS-M) is validated across multicenter cohorts and compared to radiologists' assessments (including CT/MR, MR accounted for 40.7%). Clinical utility is assessed for initial diagnosis, recurrence detection, and neoadjuvant therapy. PUCAS-M achieves an area under the receiver operation curve (AUROC) of 0.857 (95% CI: 0.820-0.895) in t

SUBMITTER: Shen R 

PROVIDER: S-EPMC12533399 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature