OBJECTIVES: To investigate the usefulness of Apparent Diffusion Coefficients (ADC) in predicting prostatectomy Gleason Grades (pGG) and Scores (GS), compared with ultrasound-guided biopsy Gleason Grades (bGG). METHODS: Twenty-four patients with biopsy-proven prostate cancer were included in the study. Diffusion-weighted images were obtained using 1.5-T MR with a pelvic phased-array coil. Median ADC values (b0,500,1000 s/mm²) were measured at the most suspicious areas in the peripheral zone. The relationship between ADC values and pGG or GS was assessed using Pearson's coefficient. The relationship between bGG and pGG or GS was also evaluated. Receiver operating characteristic (ROC) curve analysis was performed to assess the performance of each method on a qualitative level. RESULTS: A significant negative correlation was found between mean ADCs of suspicious lesions and their pGG (r = -0.55; p < 0.01) and GS (r = -0.63; p < 0.01). No significant correlation was found between bGG and pGG (r = 0.042; p > 0.05) or GS (r = 0.048; p > 0.05). ROC analysis revealed a discriminatory performance of AUC = 0.82 for ADC and AUC = 0.46 for bGG in discerning low-grade from intermediate/high-grade lesions. CONCLUSIONS: The ADC values of suspicious areas in the peripheral zone perform better than bGG in the correlation with prostate cancer aggressiveness, although with considerable intra-subject heterogeneity. KEY POINTS: • Prostate cancer aggressiveness is probably underestimated and undersampled by routine ultrasound-guided biopsies. • Diffusion-weighted MR images show good linear correlation with prostate cancer aggressiveness. • DWI information may be used to improve risk-assessment in prostate cancer.
OBJECTIVES: To investigate the usefulness of Apparent Diffusion Coefficients (ADC) in predicting prostatectomy Gleason Grades (pGG) and Scores (GS), compared with ultrasound-guided biopsy Gleason Grades (bGG). METHODS: Twenty-four patients with biopsy-proven prostate cancer were included in the study. Diffusion-weighted images were obtained using 1.5-T MR with a pelvic phased-array coil. Median ADC values (b0,500,1000 s/mm²) were measured at the most suspicious areas in the peripheral zone. The relationship between ADC values and pGG or GS was assessed using Pearson's coefficient. The relationship between bGG and pGG or GS was also evaluated. Receiver operating characteristic (ROC) curve analysis was performed to assess the performance of each method on a qualitative level. RESULTS: A significant negative correlation was found between mean ADCs of suspicious lesions and their pGG (r = -0.55; p < 0.01) and GS (r = -0.63; p < 0.01). No significant correlation was found between bGG and pGG (r = 0.042; p > 0.05) or GS (r = 0.048; p > 0.05). ROC analysis revealed a discriminatory performance of AUC = 0.82 for ADC and AUC = 0.46 for bGG in discerning low-grade from intermediate/high-grade lesions. CONCLUSIONS: The ADC values of suspicious areas in the peripheral zone perform better than bGG in the correlation with prostate cancer aggressiveness, although with considerable intra-subject heterogeneity. KEY POINTS: • Prostate cancer aggressiveness is probably underestimated and undersampled by routine ultrasound-guided biopsies. • Diffusion-weighted MR images show good linear correlation with prostate cancer aggressiveness. • DWI information may be used to improve risk-assessment in prostate cancer.
Authors: T Sugahara; Y Korogi; M Kochi; I Ikushima; Y Shigematu; T Hirai; T Okuda; L Liang; Y Ge; Y Komohara; Y Ushio; M Takahashi Journal: J Magn Reson Imaging Date: 1999-01 Impact factor: 4.813
Authors: Junqian Xu; Peter A Humphrey; Adam S Kibel; Abraham Z Snyder; Vamsidhar R Narra; Joseph J H Ackerman; Sheng-Kwei Song Journal: Magn Reson Med Date: 2009-04 Impact factor: 4.668
Authors: Anthony V D'Amico; Judd Moul; Peter R Carroll; Leon Sun; Deborah Lubeck; Ming-Hui Chen Journal: J Clin Oncol Date: 2003-06-01 Impact factor: 44.544
Authors: N M deSouza; S F Riches; N J Vanas; V A Morgan; S A Ashley; C Fisher; G S Payne; C Parker Journal: Clin Radiol Date: 2008-04-18 Impact factor: 2.350
Authors: Jinxing Yu; Ann S Fulcher; Sarah G Winks; Mary A Turner; Ryan D Clayton; Michael Brooks; Sean Li Journal: Br J Radiol Date: 2017-03-29 Impact factor: 3.039
Authors: Alice C Yu; Chaitra Badve; Lee E Ponsky; Shivani Pahwa; Sara Dastmalchian; Matthew Rogers; Yun Jiang; Seunghee Margevicius; Mark Schluchter; William Tabayoyong; Robert Abouassaly; Debra McGivney; Mark A Griswold; Vikas Gulani Journal: Radiology Date: 2017-02-10 Impact factor: 11.105
Authors: K C McCammack; C J Kane; J K Parsons; N S White; N M Schenker-Ahmed; J M Kuperman; H Bartsch; R S Desikan; R A Rakow-Penner; D Adams; M A Liss; R F Mattrey; W G Bradley; D J A Margolis; S S Raman; A Shabaik; A M Dale; D S Karow Journal: Prostate Cancer Prostatic Dis Date: 2016-01-12 Impact factor: 5.554
Authors: Leonardo K Bittencourt; Ulrike I Attenberger; Daniel Lima; Ralph Strecker; Andre de Oliveira; Stefan O Schoenberg; Emerson L Gasparetto; Daniel Hausmann Journal: World J Radiol Date: 2014-06-28
Authors: Graham Sommer; Donna Bouley; Harcharan Gill; Bruce Daniel; Kim Butts Pauly; Chris Diederich Journal: Can J Urol Date: 2013-04 Impact factor: 1.344
Authors: Joe H Chang; Daryl Lim Joon; Sze Ting Lee; Chee-Yan Hiew; Stephen Esler; Sylvia J Gong; Morikatsu Wada; David Clouston; Richard O'Sullivan; Yin P Goh; Henri Tochon-Danguy; J Gordon Chan; Damien Bolton; Andrew M Scott; Vincent Khoo; Ian D Davis Journal: Eur Radiol Date: 2013-11-06 Impact factor: 5.315