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Three-dimensional computer-assisted analysis of sector biopsy of the prostate.

机译:前列腺扇形活检的三维计算机辅助分析。

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OBJECTIVES: To assess the relationship between tumor volume, gland volume, number of sectors submitted to biopsy, and prostatic biopsy detection rate. METHODS: Using a three-dimensional mathematical model of the prostate, we assessed detection rates achieved with 4-, 6-, 8-, 10-, and 12-sector biopsies for glands ranging from 20 to 100 cc and peripheral zone tumors ranging from 0.3 to 1.4 cc. RESULTS: Quadrant and sextant biopsy approaches only yielded from 6.2% to 13.4% and 8.6% to 18.3%, respectively, of lesions in a 40-cc gland. Conversely, 10- and 12-sector approaches yielded, respectively, from 19.8% to 48.8% and 25.4% to 62% of lesions for the same gland size. When assessed according to the density of sampling, one biopsy core used for every 1 .5 to 3.5 cc of prostatic tissue detected 42.5% of 0.5-cc lesions. For the same lesion size, the density of sampling per biopsy core was then decreased to intervals extending from 3.6 to 7.5 cc, 7.6 to 12.5 cc, and 12.6 to 25 cc. These sampling density intervals yielded, respectively, 25.0%, 15.8%, and 9.8% detection rates. CONCLUSIONS: On the basis of our results, a gland volume-based biopsy algorithm is likely to result in improved detection of clinically significant prostate cancer.
机译:目的:评估肿瘤体积,腺体体积,要进行活检的扇区数和前列腺活检检出率之间的关系。方法:使用三维数学模型对前列腺进行评估,我们评估了4、6、8、10和12扇区活检组织对20到100 cc腺体和周围区域肿瘤的检出率。 0.3至1.4 cc结果:在40 cc腺体中,象限和六分活检方法分别仅占病变的6.2%至13.4%和8.6%至18.3%。相反,在相同腺体的情况下,10扇区和12扇区的方法分别占病变的19.8%至48.8%和25.4%至62%。根据采样密度进行评估时,每1 .5至3.5 cc前列腺组织使用一个活检核心,可检测到42.5%的0.5 cc病变。对于相同的病变大小,然后将每个活检核心的采样密度降低到从3.6到7.5 cc,7.6到12.5 cc和12.6到25 cc的间隔。这些采样密度间隔分别产生25.0%,15.8%和9.8%的检测率。结论:基于我们的研究结果,基于腺体体积的活检算法可能会改善对临床上重要的前列腺癌的检测。

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