Correlation of Stiffness of Prostate Cancer Measured by Shear Wave Elastography with Grade Group: A Preliminary Study

前列腺癌 相关性 弹性成像 剪切(地质) 刚度 医学 材料科学 物理 癌症 内科学 数学 复合材料 放射科 超声波 几何学
作者
Wenbin Dai,Jun Xu,Bo Yu,Lin Chen,Yue Chen,Jia Zhan
出处
期刊:Ultrasound in Medicine and Biology [Elsevier]
卷期号:47 (2): 288-295 被引量:10
标识
DOI:10.1016/j.ultrasmedbio.2020.10.018
摘要

The aim of study was to explore the correlation between shear wave elastography (SWE) and grade group (GG) of prostate cancer (PCa). This retrospective study involved prostate-specific antigen elevated patients with elevated prostate-specific antigen levels who underwent SWE before transrectal ultrasound-guided needle biopsy. A total of 49 PCa lesions were reviewed after radical prostatectomy; 3-7 regions of interest were placed within the cancerous area on axial view compared with the tumor foci outlined on the slides by pathologist. The maximum SWE value was measured, quantitative SWE parameters (Emax, Emean, Emin and standard deviation [SD]) were recorded and correlated with GG and then parameters were compared between indolent (≤2) and aggressive (≥3) GGs. The diagnostic value of each parameter was compared with the receiver operating characteristic curve. Forty-nine PCa foci were divided into two groups on the basis of their GGs. All SWE parameters exhibited a significant linear trend with GG. The area under the receiver operating characteristic curve (AUC) was 0.816 for Emax; with a cutoff point of 84 kPa, sensitivity and specificity were 81.3% and 82.4% to differentiate low and high GGs in PCa. The AUC was 0.776 for Emean; with a cutoff point of 71 kPa, sensitivity and specificity were 78.1% and 76.5%. For Emin, the AUC was 0.739; with a cutoff point of 60 kPa, sensitivity and specificity were 68.8% and 70.6%. For SD, the AUC was 0.681; with a cutoff point of 8.3 kPa, sensitivity and specificity were 46.9% and 94.1%. There were no significant differences between the four SWE parameters (p < 0.05 for all). SWE features were correlated with GGs, and this correlation may have excellent diagnostic performance in predicting high GG in PCa.
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