• Jussi Toivonen, Harri Merisaari, Marko Pesola, Pekka Taimen, Peter J Boström, Tapio Pahikkala, Hannu J Aronen, and Ivan Jambor.
• Department of Diagnostic Radiology, University of Turku, Turku, Finland.
• Magn Reson Med. 2015 Oct 1; 74 (4): 1116-24.

PurposeTo evaluate four mathematical models for diffusion weighted imaging (DWI) of prostate cancer (PCa) in terms of PCa detection and characterization.MethodsFifty patients with histologically confirmed PCa underwent two repeated 3 Tesla DWI examinations using 12 equally distributed b values, the highest b value of 2000 s/mm(2) . Normalized mean signal intensities of regions-of-interest were fitted using monoexponential, kurtosis, stretched exponential, and biexponential models. Tumors were classified into low, intermediate, and high Gleason score groups. Areas under receiver operating characteristic curve (AUCs) were estimated to evaluate performance in PCa detection and Gleason score classifications. The fitted parameters were correlated with Gleason score groups by using the Spearman correlation coefficient (ρ). Coefficient of repeatability and intraclass correlation coefficient [specifically ICC(3,1)], were calculated to evaluate repeatability of the fitted parameters.ResultsThe AUC and ρ values were similar between parameters of monoexponential, kurtosis, and stretched exponential (with the exception of the α parameter) models. The absolute ρ values for ADCm , ADCk , K, and ADCs were in the range from 0.31 to 0.53 (P < 0.01). Parameters of the biexponential model demonstrated low repeatability.ConclusionIn region-of-interest based analysis, the monoexponential model for DWI of PCa using b values up to 2000 s/mm(2) was sufficient for PCa detection and characterization.© 2014 Wiley Periodicals, Inc.

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