Reducing the influence of b-value selection on diffusion-weighted imaging of the prostate: Evaluation of a revised monoexponential model within a clinical setting

摘要

Purpose: To compare the accuracy of standard and revised monoexponential models of diffusion-weighted magnetic resonance imaging (DW-MRI) data for differentiating malignant from benign prostate tissue, using surgical pathology as the reference standard. Materials and Methods: The Institutional Review Board waived informed consent for this Health Insurance Portability and Accountability Act (HIPAA)-compliant, retrospective study of 46 patients (median age = 61 years; range: 42-85 years) who underwent DW-MRI between May and December 2008 before radical prostatectomy for biopsy-proven prostate cancer, had no prior treatment, and had whole-mount step-section pathology maps available showing at least one peripheral zone (PZ) lesion 0.1 cm 3. DW-MRI data were obtained for b-values of 0, 400, and 700 s/mm 2. Apparent diffusion coefficients (ADCs) were estimated from PZ regions of interest (ROIs) on b = 0, 700 and b = 0, 400 s/mm 2 images, using a standard monoexponential model. The true diffusion coefficient (D) and perfusion fraction (f) were measured using a revised monoexponential model incorporating all three b-values. Areas under receiver operating characteristic curves (AUCs) were calculated to assess the accuracy of individual parameters and a logistic regression model combining D and f (D+f) in distinguishing malignant ROIs; P 0.05 denoted significance. Results: ADC 400 (AUC = 0.81, P 0.0001), ADC 700 (AUC = 0.79, P 0.0001), D (AUC = 0.71, P = 0.0001) and D + f distinguished malignant from benign ROIs (AUC = 0.82, P 0.0001), but f did not (AUC = 0.56, P = 0.28); D + f was significantly more accurate than D (P = 0.016) but not more accurate than ADC 400 (P = 0.26) or ADC 700 (P = 0.12). Conclusion: The true diffusion coefficient provides an additional DW-MRI parameter for distinguishing prostate cancer that is less influenced than the ADC by b-value selection.