Aganovic Damir, Kulovac Benjamin, Radović Svjetlana, Bilalović Nurija, Bajramović Senad, Kešmer Amel
Department of Urology, University Clinical Center Sarajevo, Sarajevo, Bosnia and Herzegovina.
Department of Pathology, Faculty of Medicine, University of Sarajevo, Sarajevo, Bosnia and Herzegovina.
Acta Inform Med. 2019 Jun;27(2):89-95. doi: 10.5455/aim.2019.27.89-95.
Cancer of the prostate (PCa) is the second most common cancer-related cause of death among men and the most common non-cutaneous malignancy in Western countries. Numerous papers have been published on the topic of various aspects of this disease; however, rather little has been written on the diagnostic and prognostic value of the prostate cancer obtained from needle biopsy.
To examine the utility of Pixel Prostate software in determining the volume and topographic distribution cancer of the prostate (PCa), and to analyze it with other variables that are characteristic for PCa.
retrospectively, 75 patients data and postoperative prostate specimens were analyzed, after determining topographic distribution and cancer volume (PCa), using PixelProstate software.
Mean VPCa was 6.99 cm (0.14-29.7; median 4.51), and mean percentage cancer volume relative to prostate volume (%VPCa) was 16% (0.1-67.2%; median 13%). 71% of the patients had T2 stage, while the rest had T3 stage. Apex involvement was present in 65% of the patients, while central zone involvement and extraprostatic extension were present in 23.5% and 22.7% of the patients, respectively. Preoperative Gleason score undergrading was present in 27 (36%) patients, while bilateral PCa finding was increased from 51% to 87%, postoperatively. The most discriminant variable according to the prediction of %VPCa>10% had preoperative bilateral needle biopsy findings, with AUC of 0.75 (<.001), with sensitivity and specificity of 84% and 70%, respectively; (+LR 2,8; PPV of 74%; NPV of 82%). %VPCa showed good correlation with prostate specific antigen (PSA) and PSA-density.
A possibility of precise spatial orientation and volume characterization of the PCa by PixelProstate software was shown. Simultaneously, with time, a clinician, experienced by PP software feedback, gets better insight for the planning of future prostate biopsy, as an important factor in clinical decision making.
前列腺癌（PCa）是男性中第二大常见的癌症相关死因，也是西方国家最常见的非皮肤恶性肿瘤。关于这种疾病各个方面的主题已经发表了大量论文；然而，关于经针吸活检获得的前列腺癌的诊断和预后价值的论述相对较少。
研究Pixel Prostate软件在确定前列腺癌（PCa）体积和地形分布方面的效用，并将其与PCa的其他特征变量进行分析。
回顾性分析75例患者的数据和术后前列腺标本，使用PixelProstate软件确定地形分布和癌体积（PCa）。
平均癌体积（VPCa）为6.99立方厘米（0.14 - 29.7；中位数4.51），癌体积相对于前列腺体积的平均百分比（%VPCa）为16%（0.1 - 67.2%；中位数13%）。71%的患者为T2期，其余为T3期。65%的患者有尖部受累，23.5%和22.7%的患者分别有中央区受累和前列腺外扩展。27例（36%）患者术前Gleason评分低估，术后双侧PCa发现率从51%增加到87%。根据%VPCa>10%的预测，最具判别力的变量是术前双侧针吸活检结果，曲线下面积（AUC）为0.75（<0.001），敏感性和特异性分别为84%和70%；（阳性似然比2.8；阳性预测值74%；阴性预测值82%）。%VPCa与前列腺特异性抗原（PSA）和PSA密度显示出良好的相关性。
展示了使用PixelProstate软件对PCa进行精确空间定位和体积表征的可能性。同时，随着时间的推移，通过PP软件反馈积累经验的临床医生，在规划未来前列腺活检方面能有更好的洞察力，这是临床决策中的一个重要因素。
