OBJECTIVE: To delineate the sampling requirements for a histometric assessment of progression in low grade and high grade prostatic intraepithelial neoplasia (PIN) lesions. STUDY DESIGN: 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. RESULTS: 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. CONCLUSION: Automated histometry by machine vision can provide valuable quantitative data for diagnostic assessment and for monitoring the efficacy of chemopreventive treatment.
Statistical histometry of the basal cell secretory cell bilayer in prostatic intraepithelial neoplasia / Bartels, P. H.; Montironi, Rodolfo; Thompson, D.; Vaught, L.; Hamilton, P. W.. - In: ANALYTICAL AND QUANTITATIVE CYTOLOGY AND HISTOLOGY. - ISSN 0884-6812. - 20(5):(1998), pp. 381-388.
Statistical histometry of the basal cell secretory cell bilayer in prostatic intraepithelial neoplasia.
MONTIRONI, RODOLFO;
1998-01-01
Abstract
OBJECTIVE: To delineate the sampling requirements for a histometric assessment of progression in low grade and high grade prostatic intraepithelial neoplasia (PIN) lesions. STUDY DESIGN: 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. RESULTS: 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. CONCLUSION: Automated histometry by machine vision can provide valuable quantitative data for diagnostic assessment and for monitoring the efficacy of chemopreventive treatment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.