Nomogram using transrectal ultrasound-derived information predicting the detection of high grade prostate cancer on initial biopsy

Predicting prostate cancer in men with PSA levels of 4-10 ng/mL: MRI-based radiomics can help junior radiologists improve the diagnostic performance

To develop MRI-based radiomics model for predicting prostate cancer (PCa) in men with prostate-specific antigen (PSA) levels of 4-10 ng/mL, to compare the performance of radiomics model and PI-RADS v2.1, and to further verify the predictive ability of radiomics model for lesions with different PI-RADS v2.1 score. 171 patients with PSA levels of 4-10 ng/mL were divided into training (n = 119) and testing (n = 52) groups. PI-RADS v2.1 score was assessed by two radiologists. All volumes of interest were segmented on T₂-weighted imaging, diffusion weighted imaging, and apparent diffusion coefficient sequences, from which quantitative radiomics features were extracted. Multivariate logistic regression analysis was performed to establish radiomics model for predicting PCa. The diagnostic performance was assessed using receiver operating characteristic curve analysis. The radiomics model exhibited the best performance in predicting PCa, which was better than the performance of PI-RADS v2.1 scoring by the junior radiologist in the training group [area under the curve (AUC): 0.932 vs 0.803], testing group (AUC: 0.922 vs 0.797), and the entire cohort (AUC: 0.927 vs 0.801) (P < 0.05). The radiomics model performed well for lesions with PI-RADS v2.1 score of 3 (AUC = 0.854, sensitivity = 84.62%, specificity = 84.34%) and PI-RADS v2.1 score of 4-5 (AUC = 0.967, sensitivity = 98.11%, specificity = 86.36%) assigned by junior radiologist. The radiomics model quantitatively outperformed PI-RADS v2.1 for noninvasive prediction of PCa in men with PSA levels of 4-10 ng/mL. The model can help improve the diagnostic performance of junior radiologists and facilitate better decision-making by urologists for management of lesions with different PI-RADS v2.1 score.

Ultrasound-based radiomics score for pre-biopsy prediction of prostate cancer to reduce unnecessary biopsies

BACKGROUND

Patients undergoing prostate biopsies (PBs) suffer from low positive rates and potential risk for complications. This study aimed to develop and validate an ultrasound (US)-based radiomics score for pre-biopsy prediction of prostate cancer (PCa) and subsequently reduce unnecessary PBs.

METHODS

Between December 2015 and March 2018, 196 patients undergoing initial transrectal ultrasound (TRUS)-guided PBs were retrospectively enrolled and randomly assigned to the training or validation cohort at a ratio of 7:3. A total of 1044 radiomics features were extracted from grayscale US images of each prostate nodule. After feature selection through the least absolute shrinkage and selection operator (LASSO) regression model, the radiomics score was developed from the training cohort. The prediction nomograms were developed using multivariate logistic regression analysis based on the radiomics score and clinical risk factors. The performance of the nomograms was assessed and compared in terms of discrimination, calibration, and clinical usefulness.

RESULTS

The radiomics score consisted of five selected features. Multivariate logistic regression analysis demonstrated that the radiomics score, age, total prostate-specific antigen (tPSA), and prostate volume were independent factors for prediction of PCa (all p < 0.05). The integrated nomogram incorporating the radiomics score and three clinical risk factors reached an area under the curve (AUC) of 0.835 (95% confidence interval [CI], 0.729-0.941), thereby outperforming the clinical nomogram which based on only clinical factors and yielded an AUC of 0.752 (95% CI, 0.618-0.886) (p = 0.04). Both nomograms showed good calibration. Decision curve analysis indicated that using the integrated nomogram would add more benefit than using the clinical nomogram.

CONCLUSION

The radiomics score was an independent factor for pre-biopsy prediction of PCa. Addition of the radiomics score to the clinical nomogram shows incremental prognostic value and may help clinicians make precise decisions to reduce unnecessary PBs.

Development and validation of a nomogram for predicting prostate cancer in men with prostate-specific antigen grey zone based on retrospective analysis of clinical and multi-parameter magnetic resonance imaging/transrectal ultrasound fusion-derived data

Background

Urologists face a dilemma when deciding whether prostate biopsy is required for patients with prostate-specific antigen (PSA) levels in the grey zone (4 to 10 ng/mL).

Methods

We retrospectively analyzed data from consecutive patients with PSA levels in grey zone, who underwent targeted multiparametric magnetic resonance imaging (MP-MRI)/transrectal ultrasound (TRUS) fusion biopsy with elastography between November 2017 and December 2019 in our hospital. The patientse data including age, PSA, fPSA (free PSA), fPSA/PSA, PSA density (PSAD), prostate volume, elastography Q-analysis score (EQS), and prostate imaging-reporting and data system (PI-RADS) score were collected. The nomogram was built using logistic regression and the final cohort of patients was randomly divided into a training cohort (70%) and a validation cohort (30%) by R software. The models were evaluated by receiver operating characteristic curve (ROC) analysis and calibration curve analysis. The nomogram was constructed from the best model.

Results

The final study cohort consisted of 155 patients (training cohort, 109 patients; validation cohort, 46 patients) with PSA in the grey zone, of which 36 patients were pathologically diagnosed with PCa. The EQS model, -EQS model, +EQS model were built. The +EQS model that consisted of fPSA/PSA, EQS, and PI-RADS score had the best PCa diagnostic accuracy (development and validation, 0.783 and 0.781) and probability score (development and validation, 0.939 vs. 0.622). The new nomogram based on this model was constructed, in which fPSA/PSA ratio had the largest impact, followed by PI-RADS and EQS.

Conclusions

Elastography and pre-biopsy MP-MRI has clinical significance for patients with PSA in the grey zone. The new nomogram, which is based on pre biopsy data including serological analysis, PI-RADS score, and EQS, can be helpful for clinical decision-making to avoid unnecessary biopsy.

Prostate-Specific Antigen Density: A Measurement to Differentiate Benign Hypertrophy of Prostate from Prostate Carcinoma

Background  Determination of isolated prostate-specific antigen (PSA) in asymptomatic individuals has not demonstrated sufficient sensitivity and specificity to be useful in the routine evaluation of prostate disease. To enhance the accuracy of serum PSA we have used a proportion of serum PSA and prostate volume, which we refer to as prostate-specific antigen density (PSAD). Prostate volume in this study was calculated using transrectal ultrasonography (TRUS). Materials and Methods  A total of 106 patients with prostatic disease clinically confined to the prostate glands were evaluated. Results and Observation  The mean PSAD for prostate cancer was 0.15 ± 0.01 while that for benign hypertrophy of the prostate (BPH) was 0.11 ± 0.02 ( p < 0.05). Significant difference ( p < 0.05) was noted in the prostate volume in these two groups with the mean prostate volume measured by TRUS in the BPH to be 53.85 ± 9.71 mL compared with 58.14 ± 7.48 mL in the carcinoma. PSA density of 0.13 ng/mL can be used as a cutoff for the individual in our set-up who should go for prostate biopsy with sensitivity and specificity of over 90%. Conclusion  These results suggest that PSAD may be useful in distinguishing BPH and prostate cancer.

The roles of MRI-based prostate volume and associated zone-adjusted prostate-specific antigen concentrations in predicting prostate cancer and high-risk prostate cancer

Prostate biopsies are frequently performed to screen for prostate cancer (PCa) with complications such as infections and bleeding. To reduce unnecessary biopsies, here we designed an improved predictive model of MRI-based prostate volume and associated zone-adjusted prostate-specific antigen (PSA) concentrations for diagnosing PCa and risk stratification. Multiparametric MRI administered to 422 consecutive patients before initial transrectal ultrasonography-guided 13-core prostate biopsies from January 2012 to March 2018 at Fujian Medical University Union Hospital. Univariate and multivariate logistic regression analyses and determination of the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was performed to evaluate and integrate the predictors of PCa and high-risk prostate cancer (HR-PCa). The detection rates of PCa was 43.84% (185/422). And the detection rates of HR-PCa was 71.35% (132/185) in PCa patients. Multivariate analysis revealed that prostate volume(PV), PSA density(PSAD), transitional zone volume(TZV), PSA density of the transitional zone(PSADTZ), and MR were independent predictors of PCa and HR-PCa. PSA, peripheral zone volume(PZV) and PSA density of the peripheral zone(PSADPZ) were independent predictors of PCa but not HR-PCa. The AUC of our best predictive model including PSA + PV + PSAD + MR + TZV or PSA + PV + PSAD + MR + PZV was 0.906 for PCa. The AUC of the best predictive model of PV + PSAD + MR + TZV was 0.893 for HR-PCa. In conclusion, our results will likely improve the detection rate of prostate cancer, avoiding unnecessary prostate biopsies, and for evaluating risk stratification.

Surface-enhanced Raman spectroscopy of serum accurately detects prostate cancer in patients with prostate-specific antigen levels of 4-10 ng/mL

The surface-enhanced Raman spectroscopy (SERS) of blood serum was investigated to differentiate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) in males with a prostate-specific antigen level of 4-10 ng/mL, so as to reduce unnecessary biopsies. A total of 240 SERS spectra from blood serum were acquired from 40 PCa subjects and 40 BPH subjects who had all received prostate biopsies and were given a pathological diagnosis. Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA) diagnostic algorithms, were used to analyze the spectra data of serum from patients in control (CTR), PCa and BPH groups; results offered a sensitivity of 97.5%, a specificity of 100.0%, a precision of 100.0% and an accuracy of 99.2% for CTR; a sensitivity of 90.0%, a specificity of 97.5%, a precision of 94.7% and an accuracy of 98.3% for BPH; a sensitivity of 95.0%, a specificity of 93.8%, a precision of 88.4% and an accuracy of 94.2% for PCa. Similarly, this technique can significantly differentiate low- and high-risk PCa with an accuracy of 92.3%, a specificity of 95% and a sensitivity of 89.5%. The results suggest that analyzing blood serum using SERS combined with PCA-LDA diagnostic algorithms is a promising clinical tool for PCa diagnosis and assessment.

Could Magnetic Resonance Imaging Help to Identify the Presence of Prostate Cancer Before Initial Biopsy? The Development of Nomogram Predicting the Outcomes of Prostate Biopsy in the Chinese Population

PURPOSE

This study was designed to investigate the effectiveness of magnetic resonance imaging (MRI) in diagnosing prostate cancer (PCa) and high-grade prostate cancer (HGPCa) before transrectal ultrasound (TRUS)-guided biopsy.

METHODS

The clinical data of 894 patients who received TRUS-guided biopsy and prior MRI test from a large Chinese center was reviewed. Based on Prostate Imaging Reporting and Data System (PI-RADS) scoring, all MRIs were re-reviewed and assigned as Grade 0-2 (PI-RADS 1-2; PI-RADS 3; PI-RADS 4-5). We constructed two models both in predicting PCa and HGPCa (Gleason score ≥ 4 + 3): Model 1 with MRI and Model 2 without MRI. Other clinical factors include age, digital rectal examination, PSA, free-PSA, volume, and TRUS.

RESULTS

PCa and HGPCa were present in 434 (48.5 %) and 218 (24.4 %) patients. An MRI Grade 0, 1, and 2 were assigned in 324 (36.2 %), 193 (21.6 %) and 377 (42.2 %) patients, which was associated with the presence of PCa (p < 0.001) and HGPCa (p < 0.001). Particularly in patients aged ≤55 years, the assignment of MRI Grade 0 was correlated with extremely low rate of PCa (1/27) and no HGPCa. The c-statistic of Model 1 and Model 2 for predicting PCa was 0.875 and 0.841 (Z = 4.2302, p < 0.001), whereas for predicting HGPCa was 0.872 and 0.850 (Z = 3.265, p = 0.001). Model 1 exhibited higher sensitivity and specificity at same cutoffs, and decision-curve analysis also suggested the favorable clinical utility of Model 1.

CONCLUSIONS

Prostate MRI before biopsy could predict the presence of PCa and HGPCa, especially in younger patients. The incorporation of MRI in nomograms could increase predictive accuracy.

Prevalence and Risk Factors of Prostate Cancer in Chinese Men with PSA 4-10 ng/mL Who Underwent TRUS-Guided Prostate Biopsy: The Utilization of PAMD Score

Purpose. To elucidate the characteristics and risk factors for positive biopsy outcomes in Chinese patients with prostate specific antigen (PSA) 4–10 ng/mL and develop a risk-stratification score model. Methods. The data of 345 patients who underwent transrectal ultrasound-guided prostate biopsy between 2011 and 2013 was retrospectively analyzed. Digital rectal examination (DRE), prostate volume (PV), magnetic resonance imaging (MRI), and smoking status were also collected. Positive biopsy outcomes were defined as prostate cancer (PCa) and high grade PCa (HGPCa, Gleason Score ≥ 7). Results. The median PSA was 7.15 (IQR 5.91–8.45) ng/mL. Overall 138 patients (40.0%) were shown to have PCa, including 100 patients (29.0%) with HGPCa. Smaller PV, elder age, MRI results, and positive DRE were proved to be predictive factors for positive biopsy outcomes in both univariate and multivariate analysis. We developed a “PAMD” score which combined the four factors to categorize patients into three risk groups, and the model performed good predictive sensitivity and specificity. Conclusion. The prevalence of prostate cancer in Chinese patients with PSA 4–10 ng/mL was 40%, including 29% patients with high grade disease. DRE, age, MRI, and PV were predictive factors for positive biopsy outcomes, and the PAMD score model could be utilized for risk-stratification and decision-making.

Differences in the aggressiveness of prostate cancer among Korean, Caucasian, and African American men: A retrospective cohort study of radical prostatectomy

PURPOSE

We aimed to compare the pathologic aggressiveness of clinically localized prostate cancer (PCa) treated by radical prostatectomy in Korean and Western (Caucasian and African American [AA]) men by analyzing data from representative hospitals in the capitals of Korea (Seoul) and the United States (Washington, DC).

METHODS

We performed a retrospective cohort study of 1,939 patients who underwent radical prostatectomy for clinically localized PCa in the Asan Medical Center and Washington Hospital Center. After adjusting for confounding clinical variables, we used multivariate logistic regression analysis to assess differences in the aggressiveness of PCa.

RESULTS

We analyzed 1,152 Korean, 473 Caucasian, and 314 AA patients. There were significant differences between Korean and Western patients in terms of age at surgery, preoperative levels of prostate-specific antigen, and clinical stage (P<0.001). Overall, high-grade PCa (Gleason score≥8) was more common in Korean (19.4%) than in AA (6.1%) or Caucasian (5.5%) patients (P<0.001). The incidence of advanced-stage PCa (pT3 or higher) was higher in Korean (34.8%) than in AA (18.2%) or Caucasian (13.3%) patients (P<0.001). After adjusting for age, prostate-specific antigen, prostate volume, and clinical stage, multivariate logistic regression analysis showed that Korean men had a high risk of high-grade PCa (Korean vs. Caucasian, odds ratio [OR] = 3.48, P<0.001; Korean vs. AA, OR=3.14, P<0.001) or advanced-stage PCa (Korean vs. Caucasian, OR=2.40, P<0.001; Korean vs. AA, OR = 1.59, P = 0.009) than Western men.

CONCLUSIONS

There are differences in PCa aggressiveness between Korean and Western men. The incidence of high-grade or advanced-stage PCa is higher in Korean men.

Configuration and validation of a novel prostate disease nomogram predicting prostate biopsy outcome: A prospective study correlating clinical indicators among Filipino adult males with elevated PSA level

Objective

To configure and validate a novel prostate disease nomogram providing prostate biopsy outcome probabilities from a prospective study correlating clinical indicators and diagnostic parameters among Filipino adult male with elevated serum total prostate specific antigen (PSA) level.

Methods

All men with an elevated serum total PSA underwent initial prostate biopsy at our institution from January 2011 to August 2014 were included. Clinical indicators, diagnostic parameters, which include PSA level and PSA-derivatives, were collected as predictive factors for biopsy outcome. Multiple logistic-regression analysis involving a backward elimination selection procedure was used to select independent predictors. A nomogram was developed to calculate the probability of the biopsy outcomes. External validation of the nomogram was performed using separate data set from another center for determination of sensitivity and specificity. A receiver-operating characteristic (ROC) curve was used to assess the accuracy in predicting differential biopsy outcome.

Results

Total of 552 patients was included. One hundred and ninety-one (34.6%) patients had benign prostatic hyperplasia, and 165 (29.9%) had chronic prostatitis. The remaining 196 (35.5%) patients had prostate adenocarcinoma. The significant independent variables used to predict biopsy outcome were age, family history of prostate cancer, prior antibiotic intake, PSA level, PSA-density, PSA-velocity, echogenic findings on ultrasound, and DRE status. The areas under the receiver-operating characteristic curve for prostate cancer using PSA alone and the nomogram were 0.688 and 0.804, respectively.

Conclusion

The nomogram configured based on routinely available clinical parameters, provides high predictive accuracy with good performance characteristics in predicting the prostate biopsy outcome such as presence of prostate cancer, high Gleason prostate cancer, benign prostatic hyperplasia, and chronic prostatitis.

Trans-rectal ultrasound visibility of prostate lesions identified by magnetic resonance imaging increases accuracy of image-fusion targeted biopsies

PURPOSE

To compare the diagnostic yield of targeted prostate biopsy using image-fusion of multi-parametric magnetic resonance (mp-MR) with real-time trans-rectal ultrasound (TRUS) for clinically significant lesions that are suspicious only on mp-MR versus lesions that are suspicious on both mp-MR and TRUS.

METHODS

Pre-biopsy MRI and TRUS were each scaled on a 3-point score: highly suspicious, likely, and unlikely for clinically significant cancer (sPCa). Using an MR-TRUS elastic image-fusion system (Koelis), a 127 consecutive patients with a suspicious clinically significant index lesion on pre-biopsy mp-MR underwent systematic biopsies and MR/US-fusion targeted biopsies (01/2010-09/2013). Biopsy histological outcomes were retrospectively compared with MR suspicion level and TRUS-visibility of the MR-suspicious lesion. sPCa was defined as biopsy Gleason score ≥7 and/or maximum cancer core length ≥5 mm.

RESULTS

Targeted biopsies outperformed systematic biopsies in overall cancer detection rate (61 vs. 41 %; p = 0.007), sPCa detection rate (43 vs. 23 %; p = 0.0013), cancer core length (7.5 vs. 3.9 mm; p = 0.0002), and cancer rate per core (56 vs. 12 %; p < 0.0001), respectively. Highly suspicious lesions on mp-MR correlated with higher positive biopsy rate (p < 0.0001), higher Gleason score (p = 0.018), and greater cancer core length (p < 0.0001). Highly suspicious lesions on TRUS in corresponding to MR-suspicious lesion had a higher biopsy yield (p < 0.0001) and higher sPCa detection rate (p < 0.0001). Since majority of MR-suspicious lesions were also suspicious on TRUS, TRUS-visibility allowed selection of the specific MR-visible lesion which should be targeted from among the multiple TRUS suspicious lesions in each prostate.

CONCLUSIONS

MR-TRUS fusion-image-guided biopsies outperformed systematic biopsies. TRUS-visibility of a MR-suspicious lesion facilitates image-guided biopsies, resulting in higher detection of significant cancer.

The role of biomarkers in the assessment of prostate cancer risk prior to prostate biopsy: which markers matter and how should they be used?

Prostate cancer (PCa) screening has been substantially influenced by the clinical implementation of serum prostate-specific antigen (PSA). In this context, improvement of early PCa detection and stage migration as well as reduced PCa mortality were achieved, and up-to-date PSA represents the gold standard biomarker of PCa diagnosis together with clinical findings. Nonetheless, PSA shows weakness in discriminating between malign and benign prostatic disease or indolent and aggressive cancers. As a result, the expansion of PSA screening is extensively debated with regard to overdetection and ultimately overtreatment, keeping in mind that PCa is still the third leading cause of cancer-specific mortality in the Western male population. Consequently, today's task is to increase the accuracy of PCa detection and furthermore to allow stratification for indolent PCa that might permit active surveillance and to filter out aggressive cancers necessitating treatment. Thus, novel biomarkers, especially in combination with approved clinical risk factors (e.g., age or family history of PCa), within multivariable prediction models carry the potential to improve many aspects of PCa diagnosis and to enable risk classification in clinical practice. Multivariable models lead to superior accuracy for PCa prediction instead of the use of a single risk factor. The aim of this article was to present an overview of known risk factors for PCa together with new promising blood- and urine-based biomarkers and their application within risk models that may allow risk stratification for PCa prior to prostate biopsy. Risk models may optimize PCa detection and classification with regard to improved PCa risk assessment and avoidance of unnecessary prostate biopsies.

Peripheral zone prostate-specific antigen density: an effective parameter for prostate cancer prediction in men receiving 5α-reductase inhibitors

Purpose:

To evaluate the predictive performance of various parameters derived from volume-adjusted prostate-specific antigen (PSA) values in detecting prostate cancer (PCa) and high-grade (Gleason score≥7) PCa according to treatment with a 5α-reductase inhibitor (5ARI).

Methods:

The results of 3,520 prostate biopsies performed between May 2006 and January 2013 were retrospectively assessed. With adjustment for age, 291 patients who had received 5ARI treatment for more than 6 months were identified and matched 1:3 to patients naïve to 5ARIs, resulting in a total of 873 patients. Peripheral zone (PZ) and transition zone (TZ) volumes were determined by transrectal ultrasonography. Receiver-operating characteristic (ROC) curve analysis was used to compare predictive performances of PSA, PSA density (PSAD; PSA/prostate volume), PZPSAD (PSA/PZ volume), and TZPSAD (PSA/TZ volume) for detecting PCa and high-grade PCa for each group.

Results:

The area under the ROC curve (AUC) was higher for PSAD than for PSA in the 5ARI group (0.751 vs. 0.677) and in the 5ARI-naïve group (0.649 vs. 0.582), respectively (P<0.001). In the 5ARI group, the AUC for PZPSAD was even higher than that for PSAD (0.781 vs. 0.751, P=0.038); in the 5ARI-naïve group, however, PZPSAD failed to achieve significant superiority (0.652 vs. 0.649, P=0.321). All volume-adjusted PSA indexes showed higher predictive accuracies for detecting PCa than did PSA in both groups. For detecting high-grade cancer, PZPSAD also revealed the highest predictive value in the 5ARI group, whereas PSA revealed the highest predictive value in the 5ARI-naïve group.

Conclusions:

The diagnostic performance of PSAD in the detection of PCa is superior to that of PSA. For patients receiving 5ARI for more than 6 months, PZPSAD confers additional benefits for detecting both PCa and high-grade PCa.