1056 Correlation of diffusion-weighted imaging findings of prostate cancer with Gleason scores

You have accessJournal of UrologyProstate Cancer: Detection & Screening II1 Apr 2014MP53-11 CORRELATION OF DIFFUSION-WEIGHTED IMAGING FINDINGS OF PROSTATE CANCER WITH GLEASON SCORES Xiaobo Ding, Dianbo Cao, and Meizi Cui Xiaobo DingXiaobo Ding More articles by this author , Dianbo CaoDianbo Cao More articles by this author , and Meizi CuiMeizi Cui More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.1642AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail Introduction and Objectives The purpose of our study was to compare the apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging (DWI) of prostate cancer (PCa) patients with three classes of pathological Gleason scores (GS). Methods Patients whose GS met these criteria (GS 3 + 3, GS 3 + 4, and GS 4 + 3) were included in this study. The DWI was performed using b values of 0, 50, and 400 s/mm(2) in 40 patients using an endorectal coil on a 1.5T MRI scanner. The apparent diffusion coefficient (ADC) values were calculated from the DWI data of patients with three different Gleason scores. Results In patients with a high-grade Gleason score (4 + 3), the ADC values were lower in the peripheral gland tissue, pathologically determined as tumor compared to low grade (3 + 3 and 3 + 4). The mean and standard deviation of the ADC values for patients with GS 3 + 3, GS 3 + 4, and GS 4 + 3 were 1.12 ± 0.12, 0.98 ± 0.11 and 0.84 ± 0.08 mm(2)/sec. The ADC values were statistically significant (P < 0.05) between the three different scores with a trend of decreasing ADC values with increasing Gleason scores by one-way ANOVA method. Conclusions This study shows that the DWI-derived ADC values may help differentiate aggressive from low-grade PCa. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e592 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Xiaobo Ding More articles by this author Dianbo Cao More articles by this author Meizi Cui More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...