Can Prostate Imaging Reporting and Data System Version 2 reduce unnecessary prostate biopsies in men with PSA levels of 4–10 ng/ml?

Xu, Ning; Wu, Yupeng; Chen, Dong‐Ning; Ke, Zhi‐Bin; Cai, Hai; Wei, Yong; Zheng, Qing‐Shui; Huang, Jiaofeng; Li, Xiaodong; Xue, Xue-Yi

doi:10.1007/s00432-018-2616-6

Cited by 23 publications

(28 citation statements)

References 35 publications

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“…We indicated the significance of abnormal rectal examination with a coexisting PI-RADS ≥4 lesion in csPCa detection. Concerning these variables and their importance in assessing the risk of csPCa, we confirmed the correlations shown in the literature [ 17 , 18 ]. Similarly, to the available calculators, we demonstrated the PSA and prostate volume parameters' statistical significance in overall PCa detection [ 9 , 15 , 18 ].…”

Section: Discussionsupporting

confidence: 88%

“…Concerning these variables and their importance in assessing the risk of csPCa, we confirmed the correlations shown in the literature [ 17 , 18 ]. Similarly, to the available calculators, we demonstrated the PSA and prostate volume parameters' statistical significance in overall PCa detection [ 9 , 15 , 18 ]. We also indicated that the location of the IL in the peripheral zone is an independent predictor of the risk of total PCa and csPCa.…”

Section: Discussionsupporting

confidence: 88%

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Analysis of the usefulness of magnetic resonance imaging and clinical parameters in the detection of prostate cancer in the first systematic biopsy combined with targeted cognitive biopsy

Majchrzak¹,

Cieśliński²,

Milecki

et al. 2021

Cent european J Urol

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Introduction The study aimed to assess the suitability of multiparametric magnetic resonance prostate imaging (mpMRI) in combination with clinical parameters [prostate-specific antigen (PSA), digital rectal examination (DRE)] in the identification of men at risk of the presence of prostate cancer (PCa) and clinically significant prostate cancer (csPCa, Gleason Score ≥3+4) in the cognitive fusion with systematic prostate biopsy. Material and methods We retrospectively evaluated a population of 215 biopsy – naive patients with a clinical suspicion of prostate cancer. The results of mpMRI, DRE, PSA and biopsy were analyzed. MpMRI of the prostate according to the Prostate Imaging Reporting and Data System (PI-RADS) v.2.0 scheme preceded cognitive fusion and systematic transrectal prostate biopsy. Uni- and multivariable logistic regression analysis (MVA) was used to identify the variables determining the risk of detecting PCa overall and csPCa. Results In MVA, it was established that the combination of variables such as PSA level [odds ratio (OR) 1.195; p = 0.002], PI-RADS ≥3 (OR 7.7; p = 0.002), prostate volume (OR 0.98; p = 0.017) significantly determines the probability of PCa detection in biopsy, while for csPCa it is PSA level (OR 1.14; p = 0.004), DRE (+) (OR 5.75; p <0.001), PI-RADS ≥4 (OR 6.5; p <0.001). Analysis of mpMRI diagnostic value for PI-RADS ≥4 revealed better sensitivity (88.9% vs 82.6%) and better negative predictive value (NPV) (94.5% vs 82.4%) for detection of csPCa than for PCa overall. Conclusions MpMRI results combining with DRE and PSA parameters help to identify men at high – or low risk of csPCa detection in the first – time biopsy.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 88%

Analysis of the usefulness of magnetic resonance imaging and clinical parameters in the detection of prostate cancer in the first systematic biopsy combined with targeted cognitive biopsy

Majchrzak¹,

Cieśliński²,

Milecki

et al. 2021

Cent european J Urol

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“…Compared to vascular permeability parameters, ADC showed better diagnostic performance in detecting PCa, with an AUC of 0.999, sensitivity of 0.998, and specificity of 0.999. PI-RADS v2 is a noninvasive method to predict PCa with low specificity (28), which was confirmed in our study. To improve sensitivity and specificity, we constructed an imagingbased model combining PI-RADS score, ADC, K trans , K ep , and V p that was visualized as a nomogram and had a sensitivity of 0.983 and specificity of 0.999; these were higher than the corresponding values for PI-RADS score and vascular permeability parameters.…”

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confidence: 86%

DCE-MRI and DWI can differentiate benign from malignant prostate tumors when serum PSA is ≥10 ng/ml

Sun

Liu

et al. 2022

Front. Oncol.

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BackgroundThis study investigated the diagnostic utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters for distinguishing between benign and malignant prostate tumors when serum prostate-specific antigen (PSA) level is ≥10 ng/ml.MethodsPatients with prostate cancer (PCa) and benign prostatic hyperplasia (BPH) with serum PSA ≥10 ng/ml before treatment were recruited. Transrectal ultrasound-guided biopsy or surgery was performed for tumor classification and patients were stratified accordingly into PCa and BPH groups. Patients underwent DCE-MRI and DWI scanning and the transfer constant (Ktrans), rate constant (Kep), fractional volume of the extravascular extracellular space, plasma volume (Vp), and Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2) score were determined. The apparent diffusion coefficient (ADC) was calculated from DWI. The diagnostic performance of these parameters was assessed by receiver operating characteristic (ROC) curve analysis, and those showing a significant difference between the PCa and BPH groups were combined into a multivariate logistic regression model for PCa diagnosis. Spearman’s correlation was used to analyze the relationship between Gleason score and imaging parameters.ResultsThe study enrolled 65 patients including 32 with PCa and 33 with BPH. Ktrans (P=0.006), Kep (P=0.001), and Vp (P=0.009) from DCE-MRI and ADC (P<0.001) from DWI could distinguish between the 2 groups when PSA was ≥10 ng/ml. PI-RADS score (area under the ROC curve [AUC]=0.705), Ktrans (AUC=0.700), Kep (AUC=0.737), Vp (AUC=0.688), and ADC (AUC=0.999) showed high diagnostic performance for discriminating PCa from BPH. A combined model based on PI-RADS score, Ktrans, Kep, Vp, and ADC had a higher AUC (1.000), with a sensitivity of 0.998 and specificity of 0.999. Imaging markers showed no significant correlation with Gleason score in PCa.ConclusionDCE-MRI and DWI parameters can distinguish between benign and malignant prostate tumors in patients with serum PSA ≥10 ng/ml.

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“…Owing to the predictive value of mpMRI and PSAD in PCa diagnosis, some new multivariate risk prediction tools haver ecently been constructed. To improve their predictive value, some used extra input variables such as age, PV, free PSA, family history, race, and prior negative biopsy [18][19][20][21]. A systematic review revealed that all of these MRI risk prediction models exhibited high accuracy relative to baseline models, with AUC values ranging from 0.78 to 0.93 [22].…”

Section: External Validationmentioning

confidence: 99%

Developing a predictive model for clinically significant prostate cancer by combining age, PSA density and mpMRI

Wang

Zhang

et al. 2022

Preprint

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Purpose The study aimed to construct a predictive model for clinically significant prostate cancer (csPCa) and to investigate its clinical efficacy to reduce unnecessary prostate biopsies. Methods A total of 847 patients from institute 1 were included in Cohort 1 for model development. Cohort 2 included a total of 208 patients from institute 2 for external validation of the model. The data obtained were used for retrospective analysis. The results of magnetic resonance imaging were obtained using Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). Univariate and multivariate analyses were performed to determine significant predictors of csPCa. The diagnostic performances were compared using the receiver operating characteristic (ROC) curve analysis and decision curve analyses. Results Age, prostate-specific antigen density (PSAD) and PI-RADS v2.1 scores were used as predictors of the model. In the development cohort, the areas under the ROC curve (AUC) for csPCa about age, PSAD, PI-RADS v2.1 scores, and the model were 0.675, 0.823, 0.875, and 0.938, respectively. In the external validation cohort, the AUC values predicted by the four were 0.619, 0.811, 0.863, and 0.914, respectively. Decision curve analysis revealed that the clear net benefit of the model was higher than PI-RADS v2.1 scores and PSAD. The model significantly reduced unnecessary prostate biopsies within the risk threshold greater than 10%. Conclusions In both internal and external validation, the model constructed by combining age, PSAD, and PI-RADS v2.1 scores exhibited excellent clinical efficacy and can be utilized to reduce unnecessary prostate biopsies.

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Can Prostate Imaging Reporting and Data System Version 2 reduce unnecessary prostate biopsies in men with PSA levels of 4–10 ng/ml?

Abstract: PI-RADS v2 could be used to reduce unnecessary prostate biopsies in patients with PSA levels of 4-10 ng/ml.

Cited by 23 publications

References 35 publications

Analysis of the usefulness of magnetic resonance imaging and clinical parameters in the detection of prostate cancer in the first systematic biopsy combined with targeted cognitive biopsy

Analysis of the usefulness of magnetic resonance imaging and clinical parameters in the detection of prostate cancer in the first systematic biopsy combined with targeted cognitive biopsy

DCE-MRI and DWI can differentiate benign from malignant prostate tumors when serum PSA is ≥10 ng/ml

Developing a predictive model for clinically significant prostate cancer by combining age, PSA density and mpMRI

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