title: Morphometric diagnosis of bladder tumor.
abstract: This paper reports the morphometric analysis results of 100 cases of bladder tumor cells with a Q-900 computer-assisted image analysis system. According to the nuclear area, axis ratio and area ratio of tumor nuclei, bladder transitional cell tumors were divided into 4 grades. This system is called the morphometric grading system (M grading). The results show that the higher the M grading, the lower the survival rate and the higher the recurrence rate. As the M grade increases the tumors could be accompanied by muscular invasion. When recurring, the tumor has a poor prognosis if M grading increases. We conclude that the morphometric grading system is able to yield a quantitative pathologic diagnosis and can predict the biological behavior of bladder tumors. Recently, new techniques for diagnosing and predicting the biological behavior of bladder tumors have been developed. One such technique is morphometric analysis of bladder transitional cell carcinoma with computer-assisted image instruments [1]. Because this morphometric method is easily applicable to pathological section routinely stained with HE and the results are reproducible and more objective, the studies about morphometric analysis of bladder tumor have increased in recent times. This paper reports the preliminary morphometric analysis results of bladder tumor cells examined by a Q-900 image analysis instrument for 100 cases.
authors.affiliation: Department of Urology, First Affiliated Hospital, People's Republic of China.
authors.forename: Q B
authors.initials: QB
authors.lastname: Yang
authors.forename: Y Z
authors.initials: YZ
authors.lastname: Xia
authors.forename: Z Y
authors.initials: ZY
authors.lastname: Wang
authors.forename: G J
authors.initials: GJ
authors.lastname: Wang
authors.forename: S Z
authors.initials: SZ
authors.lastname: Ding
authors.forename: D Z
authors.initials: DZ
authors.lastname: Shi
authors.forename: W D
authors.initials: WD
authors.lastname: Liu
mesh_terms: D005500:Follow-Up Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000473:pathology