3-D MULTI-PARAMETRIC CONTRAST-ENHANCED ULTRASOUND FOR THE PREDICTION OF PROSTATE CANCER

被引:20
作者
Wildeboer, Rogier R. [1 ]
van Sloun, Ruud J. G. [1 ]
Huang, Pintong [2 ]
Wijkstra, Hessel [1 ,3 ]
Mischi, Massimo [1 ]
机构
[1] Eindhoven Univ Technol, Dept Elect Engn, Lab Biomed Diagnost, Eindhoven, Netherlands
[2] Zhejiang Univ, Affiliated Hosp 2, Dept Ultrasonog, Hangzhou, Zhejiang, Peoples R China
[3] Univ Amsterdam, Amsterdam Univ Med Ctr, Dept Urol, Amsterdam, Netherlands
基金
中国国家自然科学基金; 欧洲研究理事会;
关键词
Prostate cancer; Systematic biopsy; Dynamic contrast-enhanced ultrasound; Contrast ultrasound dispersion imaging; 3-D; Machine learning; AGENT DISPERSION; TRANSRECTAL ULTRASONOGRAPHY; SPATIOTEMPORAL ANALYSIS; ANGIOGENESIS; LOCALIZATION; DIFFUSION; BIOPSIES; GUIDELINES; DIAGNOSIS; DOPPLER;
D O I
10.1016/j.ultrasmedbio.2019.05.017
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Trans-rectal ultrasound-guided 12-core systematic biopsy (SBx) is the standard diagnostic pathway for prostate cancer (PCa) because of a lack of sufficiently accurate imaging. Quantification of 3-D dynamic contrast-enhanced ultrasound (US) might open the way for a targeted procedure in which biopsies are directed at lesions suspicious on imaging. This work describes the expansion of contrast US dispersion imaging algorithms to 3-D and compares its performance against malignant and benign disease. Furthermore, we examined the feasibility of a multi-parametric approach to predict SBx-core outcomes using machine learning. An area under the receiver operating characteristic (ROC) curve of 0.76 and 0.81 was obtained for all PCa and significant PCa, respectively, an improvement over previous US methods. We found that prostatitis, in particular, was a source of false-positive readings. (C) 2019 World Federation for Ultrasound in Medicine & Biology. All rights reserved.
引用
收藏
页码:2713 / 2724
页数:12
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