Abstract
PurposeTo evaluate which mathematical model (monoexponential, biexponential, statistical, kurtosis) fits best to the diffusion-weighted signal in prostate magnetic resonance imaging (MRI). Materials and Methods24 prostate 3-T MRI examinations of young volunteers (YV, n=8), patients with biopsy proven prostate cancer (PC, n=8) and an aged matched control group (AC, n=8) were included. Diffusion-weighted imaging was performed using 11 b-values ranging from 0 to 800 s/mm2. ResultsMonoexponential apparent diffusion coefficient (ADC) values were significantly (P<.001) lower in the peripheral (PZ) zone (1.18±0.16 mm2/s) and the central (CZ) zone (0.73±0.13 mm2/s) of YV compared to AC (PZ 1.92±0.17 mm2/s; CZ 1.35±0.21 mm2/s). In PC ADCmono values (0.61±0.06 mm2/s) were significantly (P<.001) lower than in the peripheral of central zone of AC. Using the statistical analysis (Akaike information criteria) in YV most pixels were best described by the biexponential model (82%), the statistical model, respectively kurtosis (93%) each compared to the monoexponential model. In PC the majority of pixels was best described by the monoexponential model (57%) compared to the biexponential model. ConclusionAlthough a more complex model might provide a better fitting when multiple b-values are used, the monoexponential analyses for ADC calculation in prostate MRI is sufficient to discriminate prostate cancer from normal tissue using b-values ranging from 0 to 800 s/mm2.
Published Version
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