Abstract
To assess the role of time-intensity curves (TICs) of the normal peripheral zone (PZ) in the identification of biopsy-proven prostate nodules using contrast-enhanced transrectal ultrasound (CETRUS). This study included 132 patients with 134 prostate PZ nodules. Arrival time (AT), peak intensity (PI), mean transit time (MTT), area under the curve (AUC), time from peak to one half (TPH), wash in slope (WIS) and time to peak (TTP) were analyzed using multivariate linear logistic regression and receiver operating characteristic (ROC) curves to assess whether combining nodule TICs with normal PZ TICs improved the prediction of prostate cancer (PCa) aggressiveness. The PI, AUC (p < 0.001 for both), MTT and TPH (p = 0.011 and 0.040 respectively) values of the malignant nodules were significantly higher than those of the benign nodules. Incorporating the PI and AUC values (both, p < 0.001) of the normal PZ TIC, but not the MTT and TPH values (p = 0.076 and 0.159 respectively), significantly improved the AUC for prediction of malignancy (PI: 0.784–0.923; AUC: 0.758–0.891) and assessment of cancer aggressiveness (p < 0.001). Thus, all these findings indicate that incorporating normal PZ TICs with nodule TICs in CETRUS readings can improve the diagnostic accuracy for PCa and cancer aggressiveness assessment.
Highlights
Prostate cancer (PCa) generally exhibits altered angiogenic microvascular structures and blood flow patterns, which characterize the aggressiveness of this cancer and form the basis of diagnosis based on CETRUS7,8
The discriminative power of these indices depends in part on the “background” variability of tissue heterogeneity, which when eliminated improves the diagnostic accuracy of magnetic resonance imaging (MRI) for PCa detection[11]
Several studies have reported that CETRUS has high diagnostic sensitivity and specificity for the prediction of PCa9,10
Summary
PCa generally exhibits altered angiogenic microvascular structures and blood flow patterns, which characterize the aggressiveness of this cancer and form the basis of diagnosis based on CETRUS7,8. TICs include many crucial parameters, such as arrival time (AT)[9], mean transit time (MTT) and rise time[10], time to peak (TTP) and peak intensity (PI)[9], among others. These quantitative indices are reported to have high diagnostic accuracy and lesser user dependency. The aim of this study was to evaluate the role of normal PZ TICs for the detection of PCa and assessment of cancer aggressiveness, and to determine whether the diagnostic accuracy improves significantly, compared to the biopsy findings, when normal PZ quantitative parameters are incorporated
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