Zeng J, Bauer J J, Yao X, Zhang W, McLeod D G, Sesterhenn I A, Connelly R R, Moul J W, Mun S K
Department of Radiology, Georgetown University Medical Center, Washington, DC 20007, USA.
Stud Health Technol Inform. 2000;70:392-8.
Transrectal Ultrasonography (TRUS) based systematic needle biopsy of the prostate has been widely used clinically in the diagnosis of prostate carcinoma. Current protocols for prostate biopsy, such as the Sextant Protocol, however, have been proven to be insufficient in cancer detection since these protocols were built without having accurate information on 3D distribution of prostate cancers. In this research, our goal is to optimize prostate biopsy protocols by statistically investigating spatial distributions of prostate cancers. Based on the low-resolution nature of ultrasound imaging and the current clinical conventions, we propose to divide each individual prostate gland into different zones that are can be recognized and accessed by the urologists with ultrasound images during biopsy. By calculating cancer appearance inside each of these zones using a large number of prostate samples, we get the overall distributions of prostate cancers based on which an optimal biopsy protocol can be developed.
基于经直肠超声检查（TRUS）的前列腺系统穿刺活检已在临床上广泛用于前列腺癌的诊断。然而，目前的前列腺活检方案，如六分区活检法，已被证明在癌症检测方面存在不足，因为这些方案在制定时并未掌握前列腺癌三维分布的准确信息。在本研究中，我们的目标是通过对前列腺癌的空间分布进行统计研究来优化前列腺活检方案。基于超声成像的低分辨率特性和当前的临床惯例，我们建议将每个个体的前列腺划分为不同区域，泌尿外科医生在活检过程中借助超声图像能够识别并触及这些区域。通过使用大量前列腺样本计算每个区域内癌症的出现情况，我们得出前列腺癌的总体分布情况，并据此制定最佳活检方案。
