Percentage carcinoma as a measure of prostatic tumor size in radical prostatectomy tissues.
Tumor size is a well-established prognosticator for many malignant neoplasms and is a fundamental component of the tumor-node-metastasis staging system. Prostatic tumor size, assessed in radical prostatectomy specimens by means of a variety of techniques, has been shown to be an important prognosticator. Little is known of the comparative capacity of these various methodologic approaches to predict actual tumor volume. We compared two methods for their ability to predict computer-assisted and morphometrically calculated tumor volume in 100 completely-embedded radical prostatectomy specimens. The two methods, visual inspection and grid morphometric analysis, were applied to estimate the percentage surface area of prostatic tissue sections involved by carcinoma. Statistical analysis entailed correlation coefficient calculation and linear regression analysis, including analysis of variance and model creation. Visual inspection and grid morphometric percentage tumor estimates were significantly related to tumor volume, with similar correlation coefficients of r = 0.79 and 0.81, respectively. Model construction revealed a significant relationship of both percentage estimates with tumor volume, with a model F statistic of 192 for the grid ratio and 161 for the visual inspection data. Incorporation of gland size into the model by using the number of blocks of prostatic tissue as a multiplier diminished the variance, and raised the F value to 989 for the grid ratio and 636 for visual inspection. The final model using either estimate of percentage tumor yielded this equation: tumor volume = factor x percentage carcinoma x number of blocks. We conclude that percentage carcinoma estimates by both visual inspection and grid morphometric analysis are highly significant predictors of tumor volume in radical prostatectomy specimens.
Humphrey
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Lauren V. Ackerman Laboratory of Surgical Pathology, Department of Pathology, Washington University Medical Center, St. Louis, Missouri, USA.
Vollmer
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D000368:Aged; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D010340:Pathology, Surgical / Q000379:methods; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000473:pathology*; D012984:Software