Prostate specific antigen velocity per prostate volume: a novel tool for prostate biopsy prediction.
ABSTRACT To investigate whether altered prostate specific antigen (PSA) levels due to individual prostate growth may affect the PSA velocity (PSAV).
Between January 2000 and December 2009, a total of 159 men with at least 2 transrectal ultrasonography (TRUS) procedures and concurrent PSA measurements underwent prostate biopsy because of suspicion of prostate cancer. We measured PSAV, prostate volume velocity (PVV), PSA density (PSAD), PSAD velocity (PSADV), and PSAV per initial volume. We then classified the total group into a prostate cancer (PC) group and non-PC group, and compared the 2 groups. We investigated which variables were exact to predict prostate biopsy using univariate and multivariate analyses, and assessed the diagnostic performance using the receiver operating characteristic (ROC) curve.
PVV showed a positive correlation with initial prostate volume in the total and non-PC group; PVV showed a positive correlation with PSAV, and initial prostate volume correlated with PSAV in the non-PC group. The PC group showed smaller prostate volumes, higher PSAD, higher PSADV, higher PSAV per initial volume, and longer follow-up periods. After adjusting for confounding factors, the odds ratios of prostate cancer across the quartile of PSAVD were 1, 1.889, 3.226, and 7.125 (P for trend = .007), and PSAV per initial volume were 1, 2.924, 2.937, and 7.536 (P for trend = .031). On the ROC curve, the areas under the curves (AUC) of PSAV per initial volume were higher than for PSAV and PSADV.
Altered PSA levels due to individual prostate growth may affect the use of PSAV to predict prostate biopsy outcomes in follow-up.
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ABSTRACT: Aim: To investigate the utility of prostate-specific antigen velocity (PSAV) and PSAV per initial volume (PSAVD) for early detection of prostate cancer (PCa) in Chinese men. Methods: Between January 2009 and June 2012, a total of 193 men (aged 49-84 years, median 67 years) with at least 2 transrectal ultrasonography (TRUS) procedures and concurrent serum PSA measurements underwent prostate biopsy because of suspicion of PCa. The total group were classified into PCa and non-PCa groups, and the variables of the two groups were compared. Univariate and multivariate analyses were used to investigate which variables were predictove. The diagnostic values of PSAV, PSAVD and prostate-specific antigen density (PSAD) were compared using receiver operating characteristic (ROC) analysis. Results: Prostate cancer was diagnosed in 44 (22.8%) of the 193 men. There were significant differences between the groups in last and initial prostate volumes determined by TRUS, initial age, last serum PSA levels, PSAV, PSAD and PSAVD. After adjusting for confounding factors, the odds ratios of PCa across the quartile of PSAVD were 1, 4.06, 10.6, and 18.9 (P for trend <0.001).The area under the ROC curves (AUCs) of PSAD (0.779) and PSAVD (0.776) were similar and both significantly greater than that of PSA (AUC 0.667). PSAVD was a significantly better indicator of PCa than PSAV (AUC 0.736). There was no statistical significant difference between the AUC of PSAV and that of last serum PSA level. The sensitivity and specificity of PSAVD at a cutoff of 0.023ng in participants with last serum PSA levels of 4.0ng/mL-10.0ng was 73.7% and 70.7%, respectively. Conclusions: The results of this study demonstrated PSAVD may be a useful tool in PCa detection, especially in those undergoing previous TRUS examination.Asian Pacific journal of cancer prevention: APJCP 01/2012; 13(11):5529-33. · 1.50 Impact Factor
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ABSTRACT: OBJECTIVE. The objective of our study was to compare calculated prostate volumes derived from tridimensional MR measurements (ellipsoid formula), manual segmentation, and a fully automated segmentation system as validated by actual prostatectomy specimens. MATERIALS AND METHODS. Ninety-eight consecutive patients (median age, 60.6 years; median prostate-specific antigen [PSA] value, 6.85 ng/mL) underwent triplane T2-weighted MRI on a 3-T magnet with an endorectal coil while undergoing diagnostic workup for prostate cancer. Prostate volume estimates were determined using the formula for ellipsoid volume based on tridimensional measurements, manual segmentation of triplane MRI, and automated segmentation based on normalized gradient fields cross-correlation and graph-search refinement. Estimates of prostate volume based on ellipsoid volume, manual segmentation, and automated segmentation were compared with prostatectomy specimen volumes. Prostate volume estimates were compared using the Pearson correlation coefficient and linear regression analysis. The Dice similarity coefficient was used to quantify spatial agreement between manual segmentation and automated segmentation. RESULTS. The Pearson correlation coefficient revealed strong positive correlation between prostatectomy specimen volume and prostate volume estimates derived from manual segmentation (R = 0.89-0.91, p < 0.0001) and automated segmentation (R = 0.88-0.91, p < 0.0001). No difference was observed between manual segmentation and automated segmentation. Mean partial and full Dice similarity coefficients of 0.92 and 0.89, respectively, were achieved for axial automated segmentation. CONCLUSION. Prostate volume estimates obtained with a fully automated 3D segmentation tool based on normalized gradient fields cross-correlation and graph-search refinement can yield highly accurate prostate volume estimates in a clinically relevant time of 10 seconds. This tool will assist in developing a broad range of applications including routine prostate volume estimations, image registration, biopsy guidance, and decision support systems.American Journal of Roentgenology 11/2013; 201(5):W720-9. · 2.90 Impact Factor