title: Bladder cancer diagnosis by computer image analysis of cells in the sediment of voided urine using a video scanning system.
abstract: A video-based computerized semiautomated image analysis system was applied to the diagnostic evaluation of 119 sediments of voided urine: 103 from patients with a broad variety of neoplastic and nonneoplastic disorders of the lower urinary tract and 16 normal controls. Each specimen was presented to the machine as a single cytocentrifuge preparation, preserved in 2% Carbowax in 50% ethanol and stained-by the Papanicolaou method. Five hundred sequential "objects" were scanned within an area of 9 sq mm on each slide. "Objects" of no diagnostic value, such as dirt, debris, inflammatory cells, cell clusters, poorly preserved cells, etc., were eliminated from the final diagnostic analysis by a computer-based hierarchic triage system. The final specimen classifier was based on the cell images identified by the computer as well-preserved normal (NEG), atypical (ATY I), suspicious (ATY II) and malignant (POS) cells. For specimen classification by computer, the four categories of "abnormal," "inadequate," "acellular" and "negative" were defined. For high-grade tumors, the performance of the specimen classifier was generally comparable to the visual diagnosis. The specimen classifier unexpectedly identified twice as many low-grade papillary urothelial tumors as abnormal than did the visual analysis. Several false "alarms" were recorded by computer in patients with benign prostatic hypertrophy and prostatic carcinoma, some of whom had atypical urothelium. One of the 16 negative controls was misdiagnosed by the computer as abnormal. The possibility that the video system recognizes nuclear abnormalities not perceived by the human eye is being investigated further. The details of the computer analysis are reported, and the value of the system is discussed. The system appears to be promising as a future laboratory instrument, although it requires further extensive testing.
mesh_terms: D000230:Adenocarcinoma / Q000652:urine; D002277:Carcinoma / Q000652:urine; D003581:Cytodiagnosis / Q000379:methods; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D010212:Papilloma / Q000652:urine; D011237:Predictive Value of Tests; D011471:Prostatic Neoplasms / Q000652:urine; D001749:Urinary Bladder Neoplasms / Q000473:pathology / Q000652:urine*; D014741:Video Recording