title: The use of hierarchic classification in the image analysis of a complex cell population. Experience with the sediment of voided urine.
abstract: Microscopic analysis of cells in the sediment of voided urine is the principal noninvasive method of diagnosing and detecting cancer of the lower urinary tract, mainly the bladder. The sediments contain several populations of cells of unequal diagnostic value. By applying a system of hierarchic classification to the computer analysis of digitized cell images, we were able to eliminate from diagnostic consideration cells that are difficult to classify, such as degenerated cells, multinucleated cells, cell clusters, renal tubular cells and cells infected by the human polyomavirus. When this method of triage was applied to the images of sequentially encountered epithelial cells and clusters, the cell images accepted for final analysis by the computer were sufficient in number and quality to automatically construct cytologic profiles of documented diagnostic value in 15 patients with bladder cancer. The method proved to be applicable to smears and quantitative cytocentrifuge preparations processed by methods developed in our laboratory. This work clearly documents the feasibility of automated analysis of cells in voided urine for the purpose of diagnosing bladder cancer. It also confirms prior observations suggesting that a relatively small sample of sequential images of epithelial cells (200 to 300) is sufficient to establish a diagnostic profile of clinical value on patients with high-grade cancer of the urinary bladder.
mesh_terms: D003201:Computers; D003581:Cytodiagnosis / Q000379:methods*; D006801:Humans; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000473:pathology / Q000652:urine; D014556:Urine / Q000166:cytology*