Kim D, Charlton J D, Coggins J M, Mohler J L
Department of Biomedical Engineering, University of North Carolina at Chapel Hill.
Anal Quant Cytol Histol. 1994 Dec;16(6):400-14.
Nuclear shape analysis has predicted outcome better than histologic grading in patients with clinically localized prostatic carcinoma. However, the requirement for manual nuclear contour tracing makes the method tedious and slow. Currently available image analysis systems for nuclear shape analysis using light-absorption microscopy provide nuclear boundaries of insufficient clarity for automatic segmentation. We improved image resolution using confocal laser scanning microscopy, automatically detected nuclear boundaries by a multiscale segmentation algorithm and discriminated artifacts in a semiautomated way. A manual quantitative morphometry system and our semiautomated system distinguished eight cases of prostatic carcinoma from seven cases of benign prostatic hyperplasia by nuclear roundness factor, ellipticity, nuclear area and perimeter. The ease of semiautomated nuclear shape analysis should allow evaluation of large numbers of patients with known outcomes after treatment for clinically localized prostatic carcinoma to determine whether nuclear shape analysis can be extended from research to clinical usage.
在临床局限性前列腺癌患者中，核形态分析对预后的预测比组织学分级更好。然而，手动追踪核轮廓的要求使得该方法既繁琐又缓慢。目前用于核形态分析的基于光吸收显微镜的图像分析系统所提供的核边界清晰度不足，无法进行自动分割。我们使用共聚焦激光扫描显微镜提高了图像分辨率，通过多尺度分割算法自动检测核边界，并以半自动方式辨别伪像。一个手动定量形态测量系统和我们的半自动系统通过核圆度因子、椭圆率、核面积和周长，将8例前列腺癌与7例良性前列腺增生区分开来。半自动核形态分析的简便性应能让我们评估大量临床局限性前列腺癌患者治疗后的已知预后情况，以确定核形态分析是否能从研究扩展到临床应用。
