Diffusion-weighted MRI for early detection and characterization of @entity263 in the transgenic @entity420 of the XXXX prostate model.

@entity263 @entity19989 @entity19 @entity146 @entity5 @entity420
PURPOSE: To improve early diagnosis of @entity263 to aid clinical decision-making. Diffusion-weighted magnetic resonance imaging (DW-MRI) is sensitive to water diffusion throughout tissues, which correlates with Gleason score, a histological measure of @entity263 @entity146 . In this study the ability of DW-MRI to @entity263 onset and development was evaluated in transgenic @entity420 of the @entity19 prostate ( @entity19989 ) @entity19 . MATERIALS AND METHODS: T2 -weighted and DW-MRI were acquired using a 7T MR scanner, 200   mm bore diameter; 10 @entity19989 and 6 C57BL/6 control @entity19 were scanned every 4 weeks from 8 weeks of age until sacrifice at 28-30 weeks. After sacrifice, the genitourinary tract was excised and sectioned for histological analysis. Histology slides registered with DW-MR images allowed for validation of DW-MR images and the apparent diffusion coefficient (ADC) as tools for @entity5 detection and disease stratification. An automated early assessment tool based on ADC threshold values was developed to aid @entity5 detection and progression monitoring. RESULTS: The ADC differentiated between control prostate ((1.86        0.20)   *   10(-3) mm(2) /s) and normal @entity19989 prostate ((1.38        0.10)   *   10(-3) mm(2) /s) (P   =   0.0001), between @entity19989 prostate and well-differentiated @entity5 ((0.93        0.18)   *   10(-3) mm(2) /s) (P   =   0.0006), and between well-differentiated @entity5 and poorly differentiated @entity5 ((0.63        0.06)   *   10(-3) mm(2) /s) (P   =   0.02). CONCLUSION: DW-MRI is a tool for early detection of @entity5 , and discrimination between @entity5 stages in the @entity19989 model. The incorporation of DW-MRI-based @entity263 stratification and monitoring could increase the accuracy of preclinical trials using @entity19989 @entity19 . J. Magn. Reson. Imaging 2016;43:1207-1217.
