ObjectivesTo determine the sensitivity and specificity of multiparametric magnetic resonance imaging (mpMRI) for significant prostate cancer with transperineal sector biopsy (TPSB) as the reference standard.
Patients and MethodsThe study included consecutive patients who presented for TPSB between July 2012 and November 2013 after mpMRI (T2-and diffusion-weighted images, 1.5 Tesla scanner, 8-channel body coil). A specialist uro-radiologist, blinded to clinical details, assigned qualitative prostate imaging reporting and data system (PI-RADS) scores on a Likert-type scale, denoting the likelihood of significant prostate cancer as follows: 1, highly unlikely; 3, equivocal; and 5, highly likely. TPSBs sampled 24-40 cores (depending on prostate size) per patient. Significant prostate cancer was defined as the presence of Gleason pattern 4 or cancer core length ≥6 mm.
ResultsA total of 201 patients were included in the analysis. Indications were: a previous negative transrectal biopsy with continued suspicion of prostate cancer (n = 103); primary biopsy (n = 83); and active surveillance (n = 15). Patients' mean (±SD) age, prostate-specific antigen and prostate volumes were 65 (±7) years, 12.8 (±12.4) ng/mL and 62 (±36) mL, respectively. Overall, biopsies were benign, clinically insignificant and clinically significant in 124 (62%), 20 (10%) and 57 (28%) patients, respectively. Two of 88 men with a PI-RADS score of 1 or 2 had significant prostate cancer, giving a sensitivity of 97% (95% confidence interval [CI] 87-99) and a specificity of 60% (95% CI 51-68) at this threshold. Receiver-operator curve analysis gave an area under the curve of 0.89 (95% CI 0.82-0.92). The negative predictive value of a PI-RADS score of ≤2 for clinically significant prostate cancer was 97.7%
ConclusionWe found that PI-RADS scoring performs well as a predictor for biopsy outcome and could be used in the decision-making process for prostate biopsy.
espite the merits of the apparent diffusion coefficient (ADC), reporting quantitative ADC values is not a routine part of clinical practice. This is partially due to lack of biologic specificity (1). Recently, our group presented the feasibility of Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumors (VERDICT) MRI as a quantitative microstructural imaging tool for prostate cancer (2). VERDICT combines a diffusion-weighted MRI acquisition with a mathematical model and assigns the diffusion-weighted MRI signal to three principal components: (a) intracellular water, (b) water in the extracellular extravascular space, and (c) water in the microvasculature. Because the fraction of each of these compartments differs between each Gleason grade (3), we hypothesized that
Purpose: PSA testing results in unnecessary biopsy and over-diagnosis with consequent overtreatment. Tissue biopsy is an invasive procedure, associated with significant morbidity. More accurate non-or minimum-invasive diagnostic approaches should be developed to avoid unnecessary prostate biopsy and over-diagnosis. We investigated the potential of using circulating tumor cell analysis in cancer diagnosis, particularly in predicting clinically significant prostate cancer in pre-biopsy patients. Material and methods: We enrolled 155 treatment naïve prostate cancer patients and 98 pre-biopsy patients for circulating tumor cell numeration. RNA was extracted from circulating tumor cells from 184 patients for gene expression analysis. Kruskal-Wallis, Spearman's rank, multivariate logistic regression and random forest were applied to assess the association of circulating tumor cells with aggressive prostate cancer. Results: In localized prostate cancer patients, 54% were scored as circulating tumor cell positive, which was associated with higher Gleason score (p=0.0003), risk group (p<0.0001) and clinically significant prostate cancer (p<0.0001). In pre-biopsy group, positive circulating tumor cell score in combination with PSA predicted clinically significant prostate cancer with AUC=0.869. A 12-gene panel prognostic for clinically significant prostate cancer was also identified. Combining PSA level, circulating tumor cell-score and the 12-gene panel, AUC for clinically significant prostate cancer prediction was 0.927 and in cases with multi-parametric MRI data, adding these to multi-parametric MRI significantly increased the prediction accuracy (AUC 0.936 vs 0.629). Conclusions: Circulating tumor cell analysis has the potential to significantly improve patient stratification by PSA and/or multi-parametric MRI for biopsy and treatment.
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