Faculty Bibliography

PURPOSE: The objectives of this study were to: 1) describe the patterns of repeat prostate biopsy utilization in men with previous negative biopsy, and 2) identify predictors of prostate cancer (CaP) diagnosis in these men on repeat biopsy. MATERIALS & METHODS: 1,837 men who underwent prostate biopsy between January 1, 1995 - January 1, 2010 were identified from a university faculty group practice. Characteristics of repeat biopsy were examined including indication for biopsy, number of repeat biopsies performed, # of cores obtained, and total PSA prior to biopsy. Features of CaP diagnosed on repeat biopsy were examined including Gleason score (GS), # of positive cores, %tumor, and treatment choice. Multivariable logistic regression was utilized to identify predictors of CaP. RESULTS: Initial biopsy was negative in 1,213 men. In 255 men, 798 repeat biopsies were performed. 63 men were diagnosed with CaP, of whom 33 (52%) had age 70, biopsies including > 20 cores, and 4th repeat biopsy were associated with an elevated likelihood of CaP diagnosis. CONCLUSION: In men selected for multiple repeat biopsy, clinically significant cancer is found at each round of sampling. Given the continued likelihood of cancer detection, even by the fifth biopsy, early consideration of saturation or image-guided biopsy in the repeat biopsy population may be warranted.

PURPOSE: Dynamic FDG imaging for prostate cancer characterization is limited by generally small size and low uptake in prostate tumors. Our aim in this pilot study was to explore feasibility of simultaneous PET/MRI to guide localization of prostate lesions for dynamic FDG analysis using a graphical approach. METHODS: Three patients with biopsy-proven prostate cancer underwent simultaneous FDG PET/MRI, incorporating dynamic prostate imaging. Histology and multiparametric MRI findings were used to localize tumors, which in turn guided identification of tumors on FDG images. Regions of interest were manually placed on tumor and benign prostate tissue. Blood activity was extracted from a region of interest placed on the femoral artery on PET images. FDG data were analyzed by graphical analysis using the influx constant Ki (Patlak analysis) when FDG binding seemed irreversible and distribution volume VT (reversible graphical analysis) when FDG binding seemed reversible given the presence of washout. RESULTS: Given inherent coregistration, simultaneous acquisition facilitated use of MRI data to localize small lesions on PET and subsequent graphical analysis in all cases. In 2 cases with irreversible binding, tumor had higher Ki than benign using Patlak analysis (0.023 vs 0.006 and 0.019 vs 0.008 mL/cm per minute). In 1 case appearing reversible, tumor had higher VT than benign using reversible graphical analysis (0.68 vs 0.52 mL/cm). CONCLUSIONS: Simultaneous PET/MRI allows localization of small prostate tumors for dynamic PET analysis. By taking advantage of inclusion of the femoral arteries in the FOV, we applied advanced PET data analysis methods beyond conventional static measures and without blood sampling.

OBJECTIVE. The purpose of this study was to retrospectively evaluate the impact of multiparametric prostate MRI, including diffusion-weighted imaging (DWI) performed using different b values as well as dynamic contrast-enhanced MRI (DCE-MRI) on the accuracy, sensitivity, and specificity for transition zone (TZ) tumor detection and localization. MATERIALS AND METHODS. We included 106 prostate cancer patients (mean age [+/- SD], 62 +/- 7 years) who underwent 3-T MRI with a pelvic phased-array coil before radical prostatectomy. Three radiologists independently reviewed cases to record the likelihood of tumor in each of six TZ regions. Scores were initially assigned using T2-weighted imaging alone, reassigned after integration of DWI at b = 1000 s/mm(2) and corresponding apparent diffusion coefficient (ADC) maps, reassigned again after integration of DWI at b = 2000 s/mm(2), and reassigned a final time after integration of DCE-MRI. Generalized estimating equations based on binary logistic regression were used to compare sessions for TZ tumor detection, using prostatectomy findings as reference standard. RESULTS. Of the TZ sextants, 9.7% (62/636) contained tumor. All readers had higher sensitivity for T2-weighted imaging integrated with DWI at b = 1000 s/mm(2) and ADC compared with T2-weighted imaging alone (reader 1, 54.8% vs 33.9%; reader 2, 53.2% vs 22.6%; and reader 3, 50.0% vs 19.4% [p /= 0.054). Other measures were similar across the four sessions (reader 1, specificity 97.4-98.3% and accuracy 91.2-95.9%; reader 2, specificity 95.8-98.4% and accuracy 91.0-92.6%; reader 3, specificity 90.9-96.7% and accuracy 88.1-89.2%). CONCLUSION. DWI assists TZ tumor detection through higher sensitivity, particularly when using a very high b value; DCE-MRI lacks further additional benefit.

PURPOSE: To retrospectively compare standard and BLADE T2-weighted imaging (T2WI) sequences of the prostate in terms of image quality and tumor assessment. METHODS: 49 prostate cancer patients (64 +/- 6 years) who underwent 3 T phased-array coil MRI before prostatectomy were included. T2WI was acquired using standard rectilinear and BLADE techniques. Two readers (R1, R2) independently localized the dominant lesion using T2WI alone and using multi-parametric imaging; recorded presence of extraprostatic extension (EPE) in each lobe; and scored lesion conspicuity and absence of motion artifact (1-5 scale; 5 = highest quality). A third reader, unblinded to pathology, placed ROIs to record tumor-to-peripheral-zone contrast. Standard and BLADE T2WI were compared using paired Wilcoxon tests. RESULTS: BLADE showed a trend toward improved motion artifact for R1 (3.4 +/- 1.3 vs. 2.9 +/- 1.5; p = 0.054) but not R2 (4.0 +/- 1.0 vs. 3.9 +/- 1.1; p = 0.880). Dominant lesions showed significantly lower conspicuity using BLADE for R1 (2.8 +/- 2.0 vs. 3.2 +/- 2.0; p = 0.011) but not R2 (2.3 +/- 1.6 vs. 2.4 +/- 1.7; p = 0.353), and significantly lower tumor-to-peripheral-zone contrast using BLADE (0.35 +/- 0.13 vs. 0.42 +/- 0.15; p