Bartels P H, Montironi R, Thompson D, Vaught L, Hamilton P W
Optical Sciences Center, University of Arizona, Tucson 85721, USA.
Anal Quant Cytol Histol. 1998 Oct;20(5):381-8.
To delineate the sampling requirements for a histometric assessment of progression in low grade and high grade prostatic intraepithelial neoplasia (PIN) lesions.
Images of whole glands from normal prostates, low grade PIN lesions and high grade PIN lesions were digitized. The images were processed by a machine vision system and automatically segmented, and a number of histometric characteristics descriptive of the disruption of the basal cell layer were extracted. Next, high-resolution images of secretory cell nuclei still facing or no longer facing intact segments of the basal cell layer were recorded and karyometrically analyzed.
For the characterization of an individual lesion a minimum of 20-30 glands should be analyzed to provide an estimate of a progression index. Then, a change in progression, or due to regression, of approximately 16% can be documented. The disruption of the basal cell layer is accompanied by statistically highly significant changes in the chromatin texture and spatial distribution in secretory cell nuclei no longer facing an intact segment of that layer.
Automated histometry by machine vision can provide valuable quantitative data for diagnostic assessment and for monitoring the efficacy of chemopreventive treatment.
明确对低级别和高级别前列腺上皮内瘤变（PIN）病变进展进行组织计量学评估的取样要求。
对来自正常前列腺、低级别PIN病变和高级别PIN病变的整个腺体的图像进行数字化处理。图像由机器视觉系统处理并自动分割，提取了一些描述基底细胞层破坏的组织计量学特征。接下来，记录仍面对或不再面对基底细胞层完整节段的分泌细胞核的高分辨率图像，并进行核形态测量分析。
为了对单个病变进行特征描述，至少应分析20 - 30个腺体，以提供进展指数的估计值。然后，可以记录到约16%的进展变化或因消退导致的变化。基底细胞层的破坏伴随着不再面对该层完整节段的分泌细胞核中染色质纹理和空间分布的统计学上高度显著的变化。
通过机器视觉进行的自动组织计量学可为诊断评估和监测化学预防治疗的疗效提供有价值的定量数据。
