Hanske Julian, Risse Yannic, Roghmann Florian, Pucheril Daniel, Berg Sebastian, Tully Karl H, von Landenberg Nicolas, Wald Jan, Noldus Joachim, Brock Marko
Department of Urology, Marien Hospital Herne, Ruhr-University Bochum, Herne, Germany.
Department of Urology, Kettering Medical Center, Kettering Physician Network, Dayton, Ohio, USA.
Prostate. 2022 Feb;82(2):227-234. doi: 10.1002/pros.24264. Epub 2021 Nov 3.
Magnetic resonance imaging (MRI)-targeted prostate biopsy is a routinely used diagnostic tool for prostate cancer (PCa) detection. However, a clear superiority of the optimal approach for software-based MRI processing during biopsy procedures is still unanswered. To investigate the impact of robotic approach and software-based image processing (rigid vs. elastic) during MRI/transrectal ultrasound (TRUS) fusion prostate biopsy (FBx) on overall and clinically significant (cs) PCa detection.
The study relied on the instructional retrospective biopsy data collected data between September 2013 and August 2017. Overall, 241 men with at least one suspicious lesion (PI-RADS ≥ 3) on multiparametric MRI underwent FBx. The study protocol contains a systematic 12-core sextant biopsy plus 2 cores per targeted lesion. One experienced urologist performed 1048 targeted biopsy cores; 467 (45%) cores were obtained using rigid processing, while the remaining 581 (55%) cores relied on elastic image processing. CsPCa was defined as International Society of Urological Pathology (ISUP) grade ≥ 2. The effect of rigid versus elastic FBx on overall and csPCa detection rates was determined. Propensity score weighting and multivariable regression models were used to account for potential biases inherent to the retrospective study design.
In multivariable regression analyses, age, prostate-specific antigen (PSA), and PIRADS ≥ 3 lesion were related to higher odds of finding csPCa. Elastic software-based image processing was independently associated with a higher overall PCa (odds ratio [OR] = 3.6 [2.2-6.1], p < 0.001) and csPCa (OR = 4.8 [2.6-8.8], p < 0.001) detection, respectively.
Contrary to existing literature, our results suggest that the robotic-driven software registration with elastic fusion might have a substantial effect on PCa detection.
磁共振成像（MRI）靶向前列腺活检是用于检测前列腺癌（PCa）的常用诊断工具。然而，活检过程中基于软件的MRI处理的最佳方法的明显优势仍未得到解答。为了研究MRI/经直肠超声（TRUS）融合前列腺活检（FBx）期间机器人方法和基于软件的图像处理（刚性与弹性）对总体和临床显著性（cs）PCa检测的影响。
该研究依赖于2013年9月至2017年8月期间收集的指导性回顾性活检数据。总体而言，241名在多参数MRI上至少有一个可疑病变（PI-RADS≥3）的男性接受了FBx。研究方案包括系统性的12针六分仪活检以及每个靶向病变额外2针活检。一名经验丰富的泌尿科医生进行了1048次靶向活检针穿刺；467针（45%）采用刚性处理获得，而其余581针（55%）依赖弹性图像处理。CsPCa定义为国际泌尿病理学会（ISUP）分级≥2级。确定了刚性与弹性FBx对总体和csPCa检出率的影响。倾向评分加权和多变量回归模型用于解释回顾性研究设计固有的潜在偏差。
在多变量回归分析中，年龄、前列腺特异性抗原（PSA）和PIRADS≥3级病变与发现csPCa的较高几率相关。基于弹性软件的图像处理分别与较高的总体PCa（优势比[OR]=3.6[2.2-6.1]，p<0.001）和csPCa（OR=4.8[2.6-8.8]，p<0.001）检测独立相关。
与现有文献相反，我们的结果表明，机器人驱动的弹性融合软件配准可能对PCa检测有重大影响。
