title: Diagnostic cytologic sample profiles in patients with bladder cancer using TICAS system.
abstract: Computer analysis of digitized cell images was applied to consecutively encountered, well preserved urothelial cells in the urinary sediment of 12 patients with bladder cancer. It was shown that the composition of the cell sample, and notably the proportion cells classified in the ATY II and POS (malignant) categories, were of diagnostic significance. This work indicated that a computer-generated diagnosis based on the cells in a urinary sample could probably be achieved with a relatively small number of urothelial cells. The study also suggested that computer-generated cytologic profiles of patients with non-papillary carcinoma in situ can be distinguished from other forms of urothelial cancer. The atypicality indices computed for all cells from each patient provided important information but were per se insufficient for diagnostic purposes. This preliminary study, based on a small group of patients, suggests that high resolution scanning offers a promising approach to automation of cytology of the urinary sediment.
mesh_terms: D002277:Carcinoma / Q000175:diagnosis*; D002278:Carcinoma in Situ / Q000175:diagnosis*; D002291:Carcinoma, Papillary / Q000175:diagnosis*; D003201:Computers; D003581:Cytodiagnosis / Q000379:methods*; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D006801:Humans; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis*; D014556:Urine / Q000166:cytology*